loss aversion

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pages: 654 words: 191,864

Thinking, Fast and Slow by Daniel Kahneman

Albert Einstein, Atul Gawande, availability heuristic, Bayesian statistics, Black Swan, Cass Sunstein, Checklist Manifesto, choice architecture, cognitive bias, complexity theory, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, delayed gratification, demand response, endowment effect, experimental economics, experimental subject, Exxon Valdez, feminist movement, framing effect, hedonic treadmill, hindsight bias, index card, information asymmetry, job satisfaction, John von Neumann, Kenneth Arrow, libertarian paternalism, loss aversion, medical residency, mental accounting, meta analysis, meta-analysis, nudge unit, pattern recognition, Paul Samuelson, pre–internet, price anchoring, quantitative trading / quantitative finance, random walk, Richard Thaler, risk tolerance, Robert Metcalfe, Ronald Reagan, Shai Danziger, Supply of New York City Cabdrivers, The Chicago School, The Wisdom of Crowds, Thomas Bayes, transaction costs, union organizing, Walter Mischel, Yom Kippur War

The outside view and the risk policy are remedies against two distinct biases that affect many decisions: the exaggerated optimism of the planning fallacy and the exaggerated caution induced by loss aversion. The two biases oppose each other. Exaggerated optimism protects individuals and organizations from the paralyzing effects of loss aversion; loss aversion protects them from the follies of overconfident optimism. The upshot is rather comfortable for the d ecision maker. Optimists believe that the decisions they make are more prudent than they really are, and loss-averse decision makers correctly reject marginal propositions that they might otherwise accept. There is no guarantee, of course, that the biases cancel out in every situation. An organization that could eliminate both excessive optimism and excessive loss aversion should do so. The combination of the outside view with a risk policy should be the goal.

We concluded from many such observations that “losses loom larger than gains” and that people are loss averse. You can measure the extent of your aversion to losses by asking yourself a question: What is the smallest gain that I need to balance an equal chance to lose $100? For many people the answer is about $200, twice as much as the loss. The “loss aversion ratio” has been estimated in several experiments and is usually in the range of 1.5 to 2.5. This is an average, of course; some people are much more loss averse than others. Professional risk takers in the financial markets are more tolerant of losses, probably because they do not respond emotionally to every fluctuation. When participants in an experiment were instructed to “think like a trader,” they became less loss averse and their emotional reaction to losses (measured by a physiological index of emotional arousal) was sharply reduced.

The three principles: Writing this sentence reminded me that the graph of the value function has already been used as an emblem. Every Nobel laureate receives an individual certificate with a personalized drawing, which is presumably chosen by the committee. My illustration was a stylized rendition of figure 10. “loss aversion ratio”: The loss aversion ratio is often found to be in the range of 1. 5 and 2.5: Nathan Novemsky and Daniel Kahneman, “The Boundaries of Loss Aversion,” Journal of Marketing Research 42 (2005): 119–28. emotional reaction to losses: Peter Sokol-Hessner et al., “Thinking Like a Trader Selectively Reduces Individuals’ Loss Aversion,” PNAS 106 (2009): 5035–40. Rabin’s theorem: For several consecutive years, I gave a guest lecture in the introductory finance class of my colleague Burton Malkiel. I discussed the implausibility of Bernoulli’s theory each year.


pages: 302 words: 87,776

Dollars and Sense: How We Misthink Money and How to Spend Smarter by Dr. Dan Ariely, Jeff Kreisler

accounting loophole / creative accounting, Airbnb, Albert Einstein, bitcoin, Burning Man, collateralized debt obligation, Daniel Kahneman / Amos Tversky, delayed gratification, endowment effect, experimental economics, hedonic treadmill, IKEA effect, invisible hand, loss aversion, mental accounting, mobile money, placebo effect, price anchoring, Richard Thaler, sharing economy, Silicon Valley, Snapchat, Stanford marshmallow experiment, Steve Jobs, TaskRabbit, the payments system, Uber for X, ultimatum game, Walter Mischel, winner-take-all economy

IT’S IN THE WAY THAT YOU LOSE IT The endowment effect is deeply connected to LOSS AVERSION. The principle of loss aversion, first proposed by Daniel Kahneman and Amos Tversky,6 holds that we value gains and losses differently. We feel the pain of losses more strongly than we do the same magnitude of pleasure. And it’s not just a small difference—it’s about twice as much. In other words, we feel the pain of losing $10 about twice as strongly as we do the pleasure of winning $10. Or, if we tried to make the emotional impact the same, it would take winning $20 to counteract the feeling of losing $10. Loss aversion works hand in hand with the endowment effect. We don’t want to give up what we own partly because we overvalue it, and we overvalue it partly because we don’t want to give it up. Because of loss aversion, we weigh potential losses much more than we do potential gains.

Owners of an item, like the Bradleys with their home, value the potential loss of ownership much more than nonowners value the potential gain of the same item. This gap—fueled by loss aversion—gets us into all kinds of financial mistakes. We saw loss aversion at work when the Bradleys referenced the rising and falling real estate market. They thought about the price of their home in terms of its highest point, years ago, before the market slowed down. They thought about what they could have sold it for back then. They focused on the loss relative to the price during that previous historical moment. Retirement savings and investments are other areas where loss aversion and endowment effect can wreak havoc on our ability to see the world in an objective way. If loss aversion seems like something we would never fall prey to, consider your initial reactions to these two questions: 1.Could we live on 80 percent of our current income?

They were told how much the company prefunded in the account, how much the employee contributed, and how much money the company took back. The statement might say, “We prefunded the account with $500, you contributed $100, and the company took back $400.” That made the loss very clear. It also triggered loss aversion in participants, who quickly began maximizing their 401(k) contributions. Once we understand loss aversion and that many things can be framed as either gains or losses—and that the loss framework is more motivating—maybe we can reframe choices, such as how much to contribute to retirement savings, in a way that will persuade us to act in ways that are more consistent with our long-term well-being. Speaking of long-term well-being, loss aversion also clouds our ability to gauge long-term risks. This problem specifically impacts investment planning. When risk is involved and the amount of our investment fluctuates up and down, we have a hard time seeing beyond our potential immediate losses to imagine future gains.


pages: 184 words: 35,076

Irrationally Yours: On Missing Socks, Pickup Lines, and Other Existential Puzzles by Dan Ariely, William Haefeli

endowment effect, financial independence, Google Hangouts, loss aversion, sealed-bid auction, Skype

The basic principle behind this emotional reaction to the elimination of these movies is loss aversion. Loss aversion is one of the most basic and well-understood principles in social science. The basic finding is that losing something has a stronger emotional impact than gaining something of the same value. Going back to Netflix, the implication is that having movies taken away from your account is perceived as a loss and because of that, it feels much more painful. The impact of loss aversion could be so strong that losing the not-so-great movies can still be more upsetting than the joy of getting movies that are objectively better. One other implication of loss aversion is that while old Netflix users, such as yourself, will view the new collection of movies on Netflix in a somewhat negative and loss-aversive way, new users who just see the new set of movies without the experience of having anything taken away from them will view the updated offering in a much more positive way.

Workplace, Language, Misery ON LOSS AVERSION AND SPORTS Dear Dan, You have mentioned many times the principle of loss aversion, where the pain of losing is much higher than the joy of winning. The recent World Cup was most likely the largest spectator event in the history of the world and fans from across the globe were clearly very involved. If indeed, as suggested by loss aversion, people suffer more from losing than they are elated by winning, why would anyone become a fan of a team? After all, as fans we have about an equal chance of losing (which you claim is very painful) and of winning (which you claim does not provide the same extreme emotional impact). So in total, across many games, the outcome for fans is not a good deal. Am I missing something in my application of loss aversion? Is loss aversion not relevant to sports?

The problem with this part of your argument is that predicting our emotional reactions to losses is something we are not very good at, which means that we are not very likely to accurately take the full effect of loss aversion into account when we make choices. In your question you also raised the possibility that loss aversion might not apply to sporting events. This is a very interesting possibility, and I would like to speculate why you are (partially) correct. Sporting events are not just about the outcome. If anything, they are more about the ways in which we experience the games as they unfold over time (even the 7–1 Germany versus Brazil game). Unlike monetary gambles, games take some time and the duration of the game itself is arguably what provides the largest part of the enjoyment. To illustrate this idea, consider two individuals: N (Not-Caring) and F (Fan). What loss aversion implies is that N will end up with a neutral feeling regardless of the game’s outcome, while F has about an equal chance of being somewhat happy or very upset (and the expected value of these two potential outcomes is negative).


pages: 348 words: 83,490

More Than You Know: Finding Financial Wisdom in Unconventional Places (Updated and Expanded) by Michael J. Mauboussin

Albert Einstein, Andrei Shleifer, Atul Gawande, availability heuristic, beat the dealer, Benoit Mandelbrot, Black Swan, Brownian motion, butter production in bangladesh, buy and hold, capital asset pricing model, Clayton Christensen, clockwork universe, complexity theory, corporate governance, creative destruction, Daniel Kahneman / Amos Tversky, deliberate practice, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, dogs of the Dow, Drosophila, Edward Thorp, en.wikipedia.org, equity premium, Eugene Fama: efficient market hypothesis, fixed income, framing effect, functional fixedness, hindsight bias, hiring and firing, Howard Rheingold, index fund, information asymmetry, intangible asset, invisible hand, Isaac Newton, Jeff Bezos, Kenneth Arrow, Laplace demon, Long Term Capital Management, loss aversion, mandelbrot fractal, margin call, market bubble, Menlo Park, mental accounting, Milgram experiment, Murray Gell-Mann, Nash equilibrium, new economy, Paul Samuelson, Pierre-Simon Laplace, quantitative trading / quantitative finance, random walk, Richard Florida, Richard Thaler, Robert Shiller, Robert Shiller, shareholder value, statistical model, Steven Pinker, stocks for the long run, survivorship bias, The Wisdom of Crowds, transaction costs, traveling salesman, value at risk, wealth creators, women in the workforce, zero-sum game

And since humans have a hard time relating to all but the easiest probabilities, we often fail to see the significance of streaks. 8 Time Is on My Side Myopic Loss Aversion and Portfolio Turnover The attractiveness of the risky asset depends on the time horizon of the investor. An investor who is prepared to wait a long time before evaluating the outcome of the investment as a gain or a loss will find the risky asset more attractive than another investor who expects to evaluate the outcome soon. —Richard H. Thaler, Amos Tversky, Daniel Kahneman, and Alan Schwartz, “The Effect of Myopia and Loss Aversion on Risk Taking: An Experimental Test” Loss aversion . . . can be considered a fact of life. In contrast, the frequency of evaluations is a policy choice that presumably could be altered, at least in principle. —Shlomo Benartzi and Richard H. Thaler, “Myopic Loss Aversion and the Equity Premium Puzzle” One or One Hundred In the early 1960s, economist Paul Samuelson offered his lunch colleagues a bet where he would pay $200 for a correct call of a fair coin toss and he would collect $100 for an incorrect call.

Other developed countries around the world have seen similar results.4 In a trailblazing 1995 paper, Shlomo Benartzi and Richard Thaler suggested a solution to the equity risk premium puzzle based on what they called “myopic loss aversion.” Their argument rests on two conceptual pillars:5 1. Loss aversion. We regret losses two to two and a half times more than similar-sized gains. Since the stock price is generally the frame of reference, the probability of loss or gain is important. Naturally, the longer the holding period in a financial market the higher the probability of a positive return. (Financial markets must have a positive expected return to lure capital, since investors must forgo current consumption.) 2. Myopia. The more frequently we evaluate our portfolios, the more likely we are to see losses and hence suffer from loss aversion. Inversely, the less frequently investors evaluate their portfolios, the more likely they are to see gains.

But I’ll take you on if you promise to let me make 100 such bets” (emphasis added). This response prompted Samuelson to prove a theorem showing that “no sequence is acceptable if each of its single plays is not acceptable.” According to economic theory, his learned colleague’s answer was irrational.1 Even though the lunch bet has a positive expected value, Samuelson’s proof doesn’t feel quite right to most people. The concept of loss aversion explains why. One of prospect theory’s main findings, loss aversion says that given a choice between risky outcomes we are about two times as averse to losses than to comparable gains.2 So Samuelson’s theoretical proof notwithstanding, most people intuitively agree with his lunch partner: The prospective regret of losing $100 on a single toss exceeds the pleasure of winning $200. An opportunity to take the bet repeatedly, on the other hand, seems sensible because there are lower odds of suffering regret.


pages: 500 words: 145,005

Misbehaving: The Making of Behavioral Economics by Richard H. Thaler

"Robert Solow", 3Com Palm IPO, Albert Einstein, Alvin Roth, Amazon Mechanical Turk, Andrei Shleifer, Apple's 1984 Super Bowl advert, Atul Gawande, Berlin Wall, Bernie Madoff, Black-Scholes formula, business cycle, capital asset pricing model, Cass Sunstein, Checklist Manifesto, choice architecture, clean water, cognitive dissonance, conceptual framework, constrained optimization, Daniel Kahneman / Amos Tversky, delayed gratification, diversification, diversified portfolio, Edward Glaeser, endowment effect, equity premium, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, George Akerlof, hindsight bias, Home mortgage interest deduction, impulse control, index fund, information asymmetry, invisible hand, Jean Tirole, John Nash: game theory, John von Neumann, Kenneth Arrow, Kickstarter, late fees, law of one price, libertarian paternalism, Long Term Capital Management, loss aversion, market clearing, Mason jar, mental accounting, meta analysis, meta-analysis, money market fund, More Guns, Less Crime, mortgage debt, Myron Scholes, Nash equilibrium, Nate Silver, New Journalism, nudge unit, Paul Samuelson, payday loans, Ponzi scheme, presumed consent, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, random walk, randomized controlled trial, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Coase, Silicon Valley, South Sea Bubble, Stanford marshmallow experiment, statistical model, Steve Jobs, Supply of New York City Cabdrivers, technology bubble, The Chicago School, The Myth of the Rational Market, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, transaction costs, ultimatum game, Vilfredo Pareto, Walter Mischel, zero-sum game

The endowment effect experiments show that people have a tendency to stick with what they have, at least in part because of loss aversion. Once I have that mug, I think of it as mine. Giving it up would be a loss. And the endowment effect can kick in very fast. In our experiments, the subjects had “owned” that mug for a few minutes before the trading started. Danny liked to call this the “instant endowment effect.” And while loss aversion is certainly part of the explanation for our findings, there is a related phenomenon: inertia. In physics, an object in a state of rest stays that way, unless something happens. People act the same way: they stick with what they have unless there is some good reason to switch, or perhaps despite there being a good reason to switch. Economists William Samuelson and Richard Zeckhauser have dubbed this behavior “status quo bias.” Loss aversion and status quo bias will often work together as forces that inhibit change.

It is just a collection of papers, most of them already published. I just have to get a few stragglers to finish their new papers and complete the introduction.” The book came out, shortly after the last paper arrived and the introduction was finished, in 2000, almost four years later. The “timid choices” part of the Kahneman and Lovallo story is based on loss aversion. Each manager is loss averse regarding any outcomes that will be attributed to him. In an organizational setting, the natural feeling of loss aversion can be exacerbated by the system of rewards and punishment. In many companies, creating a large gain will lead to modest rewards, while creating an equal-sized loss will get you fired. Under those terms, even a manager who starts out risk neutral, willing to take any bet that will make money on average, will become highly risk averse.

They are especially keen to eliminate a loss altogether because of the third feature captured in figure 3: loss aversion. Examine the value function in this figure at the origin, where both curves begin. Notice that the loss function is steeper than the gain function: it decreases more quickly than the gain function goes up. Roughly speaking, losses hurt about twice as much as gains make you feel good. This feature of the value function left me flabbergasted. There, in that picture, was the endowment effect. If I take away Professor Rosett’s bottle of wine, he will feel it as a loss equivalent to twice the gain he would feel if he acquired a bottle; that is why he would never buy a bottle worth the same market price as one in his cellar. The fact that a loss hurts more than an equivalent gain gives pleasure is called loss aversion. It has become the single most powerful tool in the behavioral economist’s arsenal.


No Slack: The Financial Lives of Low-Income Americans by Michael S. Barr

active measures, asset allocation, Bayesian statistics, business cycle, Cass Sunstein, conceptual framework, Daniel Kahneman / Amos Tversky, financial exclusion, financial innovation, Home mortgage interest deduction, income inequality, information asymmetry, labor-force participation, late fees, London Interbank Offered Rate, loss aversion, market friction, mental accounting, Milgram experiment, mobile money, money market fund, mortgage debt, mortgage tax deduction, New Urbanism, p-value, payday loans, race to the bottom, regulatory arbitrage, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, the payments system, transaction costs, unbanked and underbanked, underbanked

In addition, individuals may be loss averse to the point that they will overwithhold their taxes to avoid having to write a check to the IRS. We defer a detailed discussion of these competing explanations to the next two sections. 12864-10_CH10_3rdPgs.indd 223 3/23/12 11:57 AM 224 michael s. barr and jane k. dokko Similarly, for loss aversion to color the interpretation of the relationship between portfolio allocation and wanting to overwithhold, the groups that are most likely to want overwithholding must also be the most loss averse. While the study provides no direct measure of loss aversion, the tax filers who are more likely to owe tax liability are identifiable by the size of their refunds. If loss aversion influences tax filers to want to overwithhold, then loss aversion may be manifested more strongly among those with a higher probability of writing a check to the IRS.

That is, this finding suggests an inverse relationship between the likelihood of owing taxes at the time of filing and a preference for overwithholding, which is the opposite of what a model of loss aversion predicts. Furthermore, those with mainly illiquid assets and those with one liquid asset are shown to be the groups most likely to want excess withholding. They are 18 and 13 percentage points, respectively, more likely to want to overwithhold than the group with no assets. These point estimates are well within a standard error of what table 10-4 shows, so the likelihood of owing taxes at the time of filing, and thus loss aversion, does not affect the interpretation of tax filers’ preference for overwithholding.18 Loss aversion can be an important motivation for some households to prefer overwithholding. Given the importance of framing in influencing individuals’ 16.

The rich data on tax-filing behaviors and attitudes in the DAHFS data set permit an analysis of whether individuals’ loss aversion, mental accounting, status quo bias, risk aversion, and negative personal discount rates are also related to their preference for overwithholding. We find a correlation between a preference for overwithholding and portfolio allocation choices that is consistent with present-biased preferences and selfcontrol problems. That a large majority of individuals express a preference for overwithholding is not consistent with the permanent-income hypothesis or precautionary behavior. Instead, the DAHFS study indicates that dynamic inconsistency motivates certain types of individuals to use the commitment device of overwithholding to constrain their consumption. Mental accounting and loss aversion explanations are less likely to explain the patterns in our data.


pages: 254 words: 79,052

Evil by Design: Interaction Design to Lead Us Into Temptation by Chris Nodder

4chan, affirmative action, Amazon Mechanical Turk, cognitive dissonance, crowdsourcing, Daniel Kahneman / Amos Tversky, Donald Trump, en.wikipedia.org, endowment effect, game design, haute couture, jimmy wales, Jony Ive, Kickstarter, late fees, loss aversion, Mark Zuckerberg, meta analysis, meta-analysis, Milgram experiment, Netflix Prize, Nick Leeson, Occupy movement, pets.com, price anchoring, recommendation engine, Rory Sutherland, Silicon Valley, Stanford prison experiment, stealth mode startup, Steve Jobs, telemarketer, Tim Cook: Apple, trickle-down economics, upwardly mobile

People feel loss more powerfully than gain, so it’s easier to manipulate them through doubt about negative outcomes. The magic of loss aversion will do all the rest. How to instill doubt Loss aversion is strongest when people have recently experienced the benefits of the product or service. If customers are canceling after a period of inactivity, find a way to convince them to use the product again (for instance by offering a free month of service, or access to a premium feature) so that they will feel the loss more keenly. At select points in your product, remind users of what they might lose by not choosing your preferred option. Be subtle, but remember to phrase in terms of loss. Save fear tactics for high-stakes interactions. People don’t like being scared on a regular basis, and the effect is diminished with over-use. On cancellation forms, invoke loss aversion by asking, “Which of these features will you miss the most?”

Table of Contents Cover Credits About the Author About the Technical Editor Acknowledgments Foreword Introduction Evil designs and their virtuous counterparts Pride Misplaced pride causes cognitive dissonance Social proof: Using messages from friends to make it personal and emotional Closure: The appeal of completeness and desire for order Manipulating pride to change beliefs Sloth Sloth: Is it worth the effort? Gluttony Deserving our rewards Escalating commitment: foot-in-the-door, door-in-the-face Invoking gluttony with scarcity and loss aversion Anger Avoiding anger Embracing anger Using anger safely in your products Envy Manufacturing envy through desire and aspiration Status envy: demonstrating achievement and importance Manufacturing and maintaining envy in your products Lust Creating lust: Using emotion to shape behavior Controlling lust: Using desire to get a commitment Lustful behavior Greed Learning from casinos: Luck, probability, and partial reinforcement schedules Anchoring and arbitrary coherence Evil by Design Should you feel bad about deception?

Historically gluttony was seen as a major sin (it distracted people from their religious observances), but today it’s almost as if gluttony is expected in Western culture. We demonstrate our wealth by showing an overabundance of “stuff.” Companies encourage this overabundance by making us feel like we deserve to be rewarded and by escalating our level of commitment beyond what we first intended, drawing us in from early engagement through to full-on compliance. Sites also make us fearful of missing out—scarcity, exclusivity, and loss aversion play on the fears behind gluttony. Deserving our rewards We are easily fooled into gluttony. Just having healthy options available on menus or among the selections from a vending machine is sometimes enough to make our brains think we’ve satisfied our health and nutrition goals, and therefore have permission to choose less honorable options. The average restaurant meal in the United States is four times larger now than it was in the 1950s, yet we might still be fitting into the same size clothes as we always have—not because we’ve stayed slim, but because our clothes have grown.


pages: 324 words: 93,175

The Upside of Irrationality: The Unexpected Benefits of Defying Logic at Work and at Home by Dan Ariely

Alvin Roth, assortative mating, Burning Man, business process, cognitive dissonance, corporate governance, Daniel Kahneman / Amos Tversky, end world poverty, endowment effect, Exxon Valdez, first-price auction, Frederick Winslow Taylor, George Akerlof, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, knowledge economy, knowledge worker, loss aversion, Peter Singer: altruism, placebo effect, Richard Thaler, Saturday Night Live, second-price auction, software as a service, The Wealth of Nations by Adam Smith, ultimatum game, Upton Sinclair, young professional

We chose to do this by adding the force of loss aversion to the mix.* Loss aversion is the simple idea that the misery produced by losing something that we feel is ours—say, money—outweighs the happiness of gaining the same amount of money. For example, think about how happy you would be if one day you discovered that due to a very lucky investment, your portfolio had increased by 5 percent. Contrast that fortunate feeling to the misery that you would feel if, on another day, you discovered that due to a very unlucky investment, your portfolio had decreased by 5 percent. If your unhappiness with the loss would be higher than the happiness with the gain, you are susceptible to loss aversion. (Don’t worry; most of us are.) To introduce loss aversion into our experiment, we prepaid participants in the small-bonus condition 24 rupees (6 times 4).

After all, who could blame the poor guy? This incident made us realize that including loss aversion might not work in this experiment, so we switched to paying people at the end. There was another reason why we wanted to prepay participants: we wanted to try to capture the psychological reality of bonuses in the marketplace. We thought that paying up front was analogous to the way many professionals think about their expected bonuses every year. They come to think of the bonuses as largely given and as a standard part of their compensation. They often even make plans for spending it. Perhaps they eye a new house with a mortgage that would otherwise be out of reach or plan a trip around the world. Once they start making such plans, I suspect that they might be in the same loss aversion mind-set as the prepaid participants. Thinking versus Doing We were certain that there would be some limits to the negative effect of high reward on performance—after all, it seemed unlikely that a significant bonus would reduce performance in all situations.

Given the arm’s limited functionality, the pain I experienced and am still experiencing, and what I now know about flawed decision making, I suspect that keeping my arm was, in a cost/benefit sense, a mistake. Let’s look at the biases that affected me. First, it was difficult for me to accept the doctors’ recommendation because of two related psychological forces we call the endowment effect and loss aversion. Under the influence of these biases, we commonly overvalue what we have and we consider giving it up to be a loss. Losses are psychologically painful, and, accordingly, we need a lot of extra motivation to be willing to give something up. The endowment effect made me overvalue my arm, because it was mine and I was attached to it, while loss aversion made it difficult for me to give it up, even when doing so might have made sense. A second irrational influence is known as the status quo bias. Generally speaking, we tend to want to keep things as they are; change is difficult and painful, and we’d rather not change anything if we can help it.


pages: 168 words: 46,194

Why Nudge?: The Politics of Libertarian Paternalism by Cass R. Sunstein

Affordable Care Act / Obamacare, Andrei Shleifer, availability heuristic, Cass Sunstein, choice architecture, clean water, Daniel Kahneman / Amos Tversky, Edward Glaeser, endowment effect, energy security, framing effect, invisible hand, late fees, libertarian paternalism, loss aversion, nudge unit, randomized controlled trial, Richard Thaler

You are far more likely to have that operation if you are told that of a hundred people who have the operation, ninety are alive after five years than if you are told that after five years, ten are dead. The purely semantic reframing has a major effect on people’s judgments. Similarly, people are “loss averse,” in the sense that they dislike losses more than they like corresponding gains. If people face a five-cent tax for using a plastic bag (a loss), they are much more likely to be affected than if they are given a five-cent bonus (a gain) for bringing their own bag.8 In response to questions, people persistently show both framing effects and loss aversion. (There is a nice lesson here for policymakers. If you want to have an impact, choose effective frames and enlist loss aversion. Is it paternalistic for policymakers to heed that lesson? Before you answer “yes,” note that some kind of framing is inevitable.) Now assume that people are answering those same questions in a foreign language—that is, a language that they speak, but in which they are not entirely comfortable.

There are strong theoretical reasons why this might be so: —Consumers might be myopic and hence undervalue the long-term. —Consumers might lack information or a full appreciation of information even when it is presented. —Consumers might be especially averse to the short-term losses associated with the higher prices of energy-efficient products relative to the uncertain future fuel savings, even if the expected present value of those fuel savings exceeds the cost (the behavioral phenomenon of “loss aversion”). —Even if consumers have relevant knowledge, the benefits of energy-efficient vehicles might not be sufficiently salient to them at the time of purchase, and the lack of salience might lead consumers to neglect an attribute that it would be in their economic interest to consider. —U.S. Environmental Protection Agency, Final Rule on Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards Contents INTRODUCTION Behaviorally Informed Paternalism ONE Occasions for Paternalism TWO The Paternalist’s Toolbox THREE Paternalism and Welfare FOUR Paternalism and Autonomy FIVE Soft Paternalism and Its Discontents EPILOGUE The Lives We Save May Be Our Own Notes Acknowledgments Index Why Nudge?

Now assume that people are answering those same questions in a foreign language—that is, a language that they speak, but in which they are not entirely comfortable. Here is the key finding: It turns out that they do not show either framing effects or loss aversion.9 Asked to resolve problems in a language that is not their own, people are less likely to depart from standard accounts of rationality. In an unfamiliar language, they are more likely to get the right answer. How can this be? The answer is straightforward. When people are using their own language, they think quickly and effortlessly, so System 1 has the upper hand. But when people are using another tongue, System 1 gets a bit overwhelmed and may even be rendered inoperative, while System 2 is given a serious boost. Our rapid, intuitive reactions are slowed down when we are using a language with which we are not entirely familiar.


pages: 519 words: 104,396

Priceless: The Myth of Fair Value (And How to Take Advantage of It) by William Poundstone

availability heuristic, Cass Sunstein, collective bargaining, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, East Village, en.wikipedia.org, endowment effect, equal pay for equal work, experimental economics, experimental subject, feminist movement, game design, German hyperinflation, Henri Poincaré, high net worth, index card, invisible hand, John von Neumann, Kenneth Arrow, laissez-faire capitalism, Landlord’s Game, loss aversion, market bubble, mental accounting, meta analysis, meta-analysis, Nash equilibrium, new economy, Paul Samuelson, payday loans, Philip Mirowski, Potemkin village, price anchoring, price discrimination, psychological pricing, Ralph Waldo Emerson, RAND corporation, random walk, RFID, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, rolodex, social intelligence, starchitect, Steve Jobs, The Chicago School, The Wealth of Nations by Adam Smith, ultimatum game, working poor

Prospect Theory 97 “I would go batty”: Barbara Tversky interview, July 8, 2008. 97 “interesting choices”: Kahneman Nobel autobiography, nobelprize.org/nobel_prizes/economics/laureates/2002/kahneman=autobio.html. 97 Tversky’s idea to put a negative sign on amounts: Kahneman Nobel autobiography. 98 “We reasoned that”: Ibid. 98 “Our perceptual apparatus”: Kahneman and Tversky 1979, 277. 99 “extends to the domain of moral intuitions”: Kahneman Nobel autobiography. 101 Loss aversion in real estate: Ibid. 101 Loss aversion their greatest contribution: Ibid. 102 “The major points of prospect theory”: Lambert 2006. 102 the most cited article ever to appear in Econometrica: Laibson and Zeckhauser 1998, 8, which finds 1,703 citations. 102 Merckle suicide: Moulson 2009. 102 “Humans did not evolve to be happy”: Camerer, Loewenstein, and Prelec 2005, 27. 103 “Many of the losses people fear most”: Camerer n.d. (“Three cheers—psychological, theoretical, empirical—for loss-aversion”), 9–10. 17. Rules of Fairness 104 “spend a lot of money honestly”: Kahneman, Nobel autobiography, nobelprize.org/nobel_prizes/economics/laureates/2002/kahneman=autobio.html. 104 Russell Sage biography: Sarnoff 1965.

You are apt to feel you’ve “lost” $975 rather than gained $25. In Kahneman and Tversky’s terminology, the anticipated $1,000 is a reference point. This is much like the “adaptation level” of psychophysics. The reference point determines whether something is entered as a gain or a loss on the mental ledger. That can make a huge difference in behavior. A second key idea of prospect theory is loss aversion. Losing money (anything of value) hurts more than gaining that same thing delights. You can demonstrate loss aversion by offering a bet on a coin toss. Tails you lose $100, and heads you win X. How big does X have to be for you to take the bet? Surveys show that few want to accept a “fair” bet with X = $100. Few accept X = $110, which offers a nice expected profit. (Those who do accept at this price tend to be gamblers, arbitrageurs, or economists.)

In the summer, the same animal has plenty of food, and its strategy should change. It should not bet its life on finding berries it doesn’t need. Replace “food” with “money” or any other gain, and you have prospect theory. We act as if losing $500 at poker is a life-or-death issue. Camerer suggests that loss aversion is a form of unreasoning fear, like that an acrophobic experiences looking out the window of a penthouse. “Many of the losses people fear most are not life-threatening, but there is no telling that to an emotional system overadapted to conveying fear signals,” Camerer wrote. “Thinking of loss-aversion as fear also implies the possibility that inducing emotions can push around buying and selling prices.” Seventeen Rules of Fairness Kahneman and Tversky spent the 1977–78 academic year at Stanford, polishing their prospect theory paper.


pages: 624 words: 127,987

The Personal MBA: A World-Class Business Education in a Single Volume by Josh Kaufman

Albert Einstein, Atul Gawande, Black Swan, business cycle, business process, buy low sell high, capital asset pricing model, Checklist Manifesto, cognitive bias, correlation does not imply causation, Credit Default Swap, Daniel Kahneman / Amos Tversky, David Heinemeier Hansson, David Ricardo: comparative advantage, Dean Kamen, delayed gratification, discounted cash flows, Donald Knuth, double entry bookkeeping, Douglas Hofstadter, en.wikipedia.org, Frederick Winslow Taylor, George Santayana, Gödel, Escher, Bach, high net worth, hindsight bias, index card, inventory management, iterative process, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Kickstarter, Lao Tzu, lateral thinking, loose coupling, loss aversion, Marc Andreessen, market bubble, Network effects, Parkinson's law, Paul Buchheit, Paul Graham, place-making, premature optimization, Ralph Waldo Emerson, rent control, side project, statistical model, stealth mode startup, Steve Jobs, Steve Wozniak, subscription business, telemarketer, the scientific method, time value of money, Toyota Production System, tulip mania, Upton Sinclair, Vilfredo Pareto, Walter Mischel, Y Combinator, Yogi Berra

If that’s true, why don’t more people start businesses? Loss Aversion keeps them from acting: the threat of losing a steady (and somewhat predictable) job commands more Attention than the opportunity to create a new self-sustaining business. Starting a business involves the specter of potential loss, which prevents people from getting started in the first place. Loss Aversion is particularly pronounced in recessions and depressions. Losing a job, a home, or a significant percentage of your retirement fund isn’t life threatening, but it feels horrible all the same. As a result, people tend to become more conservative, avoiding risks that could make things worse. Unfortunately, some of those risks—like starting a new business—may actually present a major opportunity to make things better. The best way to overcome Loss Aversion is to Reinterpret the risk of loss as “no big deal.”

Save your Willpower: focus on using it to change your Environment, and you’ll have more available to use whenever Inhibition is necessary. SHARE THIS CONCEPT: http://book.personalmba.com/willpower-depletion/ Loss Aversion Our doubts are traitors, and make us lose the good we oft might win, by fearing to attempt. —WILLIAM SHAKESPEARE, MEASURE FOR MEASURE Recently, my wife, Kelsey, decided to withdraw some funds from an investment account. When the brokerage deposited the money into her bank account, they deposited an additional $10,000 by mistake. Rationally, it shouldn’t have been a big deal—it was a simple mistake that was easily corrected. Emotionally, however, Kelsey felt like she was “losing” the extra money, even though it wasn’t really hers at all. Loss Aversion is the idea that people hate to lose things more than they like to gain them. There are very few relationships that psychology is able to quantify, but this is one of them: people respond twice as strongly to potential loss as they do to the opportunity of an equivalent gain.

If you look at your investment portfolio and notice that it’s increased by 100 percent, you’ll feel pretty good. If you notice that your portfolio went down 100 percent, you’ll feel horrible. Loss Aversion explains why threats typically take precedence over opportunities when it comes to Motivation. The threat of loss used to require immediate attention, because losses were extremely costly—even life threatening. Dying or losing a loved one to a predator, sickness, exposure, or starvation is universally a horrible experience, so we’re built to do everything in our power to prevent that from happening. The potential losses we typically face now are rarely as serious, but our minds still give them automatic priority. Loss Aversion also explains why uncertainty appears risky. Depending on the study you look at, anywhere between 80 and 90 percent of adults think it would be great to own their own business and work for themselves.


pages: 249 words: 77,342

The Behavioral Investor by Daniel Crosby

affirmative action, Asian financial crisis, asset allocation, availability heuristic, backtesting, bank run, Black Swan, buy and hold, cognitive dissonance, colonial rule, compound rate of return, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, Donald Trump, endowment effect, feminist movement, Flash crash, haute cuisine, hedonic treadmill, housing crisis, IKEA effect, impulse control, index fund, Isaac Newton, job automation, longitudinal study, loss aversion, market bubble, market fundamentalism, mental accounting, meta analysis, meta-analysis, Milgram experiment, moral panic, Murray Gell-Mann, Nate Silver, neurotypical, passive investing, pattern recognition, Ponzi scheme, prediction markets, random walk, Richard Feynman, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, science of happiness, Shai Danziger, short selling, South Sea Bubble, Stanford prison experiment, Stephen Hawking, Steve Jobs, stocks for the long run, Thales of Miletus, The Signal and the Noise by Nate Silver, tulip mania, Vanguard fund

Asking someone built for short-term survival to become a long-term investor is a bit like trying to paint a room with a hammer. You can do it, but it’s not pretty. One consequence of being wired to live is loss aversion; an asymmetric fear of bad stuff happening to you. Loss aversion is driven by the amygdalae, two tiny almond-shaped structures that are the seat of all of your emotional responses. Evolutionarily, loss aversion makes a lot of sense and many scientists believe it is why Homo sapiens outlasted other human species on the way to the top of the food chain. As McDermott, Fowler and Smirnov (2008) point out, running out of food was fatal and so a disposition toward avoiding loss is what prompted our ancient ancestors to pack up and forage in a new spot.19 While loss aversion is derided as being irrational in an investment context, those with a genetic predisposition against it didn’t live to see a time when their even-headedness could prevail.

And the sunk cost fallacy is rooted in a fear of wasting time and resources. All paths to conservatism, it would seem, run through some form of loss aversion. It is perhaps the most widely disseminated finding of behavioral finance that our risk and reward preferences are asymmetrical and that we care far more about avoiding loss than we do about achieving gain. What is less understood is the brain science behind this phenomenon As reported in Scientific American, Dr. Russell Poldrack and his colleagues found that, “…the brain regions that process value and reward may be silenced more when we evaluate a potential loss than they are activated when we assess a similar sized gain.” Loss aversion is as much a physiological construct as it is a psychological one. Poldrack found enhanced activity in the reward circuitry of the brain as gains were made, but even stronger responses to potential losses – something the researchers dubbed “neural loss aversion.”40 The fear of loss and the attendant behavioral paralysis that can accompany that fear have biological roots that run deep, but they must be shaken if we are to achieve our true potential as people and investors.

Investigation – Ask yourself what stories you are telling yourself and examine what thoughts are present. Non-identification – Now that you have recognized, accepted and investigated your stress, you must realize that you are more than your emotions. You can feel something without being defined by it. What’s the big idea? Physical states can impact emotion just as surely as the reverse is true. Loss aversion kept our ancestors alive. It keeps you from being a successful investor. The body longs for homeostasis. Thinking about money disrupts homeostasis. Stress is as much a physical as it is a psychic phenomenon. Taking financial risk causes real bodily pain. Fear is impossible to extinguish since the body stores it for a rainy day. Bad news in the stock market is more regular than your birthday.


pages: 397 words: 109,631

Mindware: Tools for Smart Thinking by Richard E. Nisbett

affirmative action, Albert Einstein, availability heuristic, big-box store, Cass Sunstein, choice architecture, cognitive dissonance, correlation coefficient, correlation does not imply causation, cosmological constant, Daniel Kahneman / Amos Tversky, dark matter, endowment effect, experimental subject, feminist movement, fixed income, fundamental attribution error, glass ceiling, Henri Poincaré, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, job satisfaction, Kickstarter, lake wobegon effect, libertarian paternalism, longitudinal study, loss aversion, low skilled workers, Menlo Park, meta analysis, meta-analysis, quantitative easing, Richard Thaler, Ronald Reagan, selection bias, Shai Danziger, Socratic dialogue, Steve Jobs, Steven Levy, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, William of Occam, Zipcar

This chapter deals with several other anomalies, and it shows how we can avoid them, protecting ourselves against our tendencies to make uneconomical decisions. We don’t always behave in the fully rational way demanded by cost-benefit theory, but we can arrange the world so that we don’t have to in order to get the same benefits we would if we were professional economists. Loss Aversion We have a general tendency to avoid giving up what we already have, even in situations where the cost-benefit considerations say that we should relinquish what we have for the clear prospect of getting something better. The tendency is called loss aversion. Across a wide range of situations, it appears that gaining something only makes you about half as happy as losing the same thing makes you unhappy.1 We pay dearly for our aversion to loss. Many people would be reluctant to sell a stock that’s been going down rather than a stock that’s been going up.

But few people have an attachment to a bottle of Château de Something-or-Other that they would describe as sentimental. Changing the Status Quo Loss aversion produces inertia. Changing our behavior usually involves a cost of some kind. “Shall I change the channel? I have to get up to find the remote. I have to decide what would be a more interesting program to watch. Or maybe I would enjoy reading a book more. What book? Oh, well, I haven’t watched Jeopardy! in quite a while. Might be fun.” TV networks are well aware of this sort of sluggishness in our behavior and schedule their most popular programs early in prime time, with the expectation that many watchers will stay tuned to their channel after the popular program is over. The biggest problem with loss aversion is that it prompts a status quo bias.6 I continue to receive several newsletters that I long ago stopped reading because the time is never right to figure out how to stop the darn things from coming.

Half the students in the class are given a coffee mug with the university logo prominently displayed on it. Unlucky students who did not get a mug are asked to examine one and say how much they would pay for a mug just like it. Mug owners are asked how much they would sell their mugs for. There is a heavy discrepancy between the two amounts. On average, owners are willing to sell only when the price is double what the average nonowner is willing to pay.2 Loss aversion lies behind this endowment effect. People don’t want to give up things they own, even for more than they originally considered a fair price. Imagine you bought a ticket to a football game for two hundred dollars but would have been willing to pay five hundred dollars. Then a couple of weeks later you discover on the Internet that there are lots of desperate people willing to pay up to two thousand dollars for a ticket.


pages: 304 words: 22,886

Nudge: Improving Decisions About Health, Wealth, and Happiness by Richard H. Thaler, Cass R. Sunstein

Al Roth, Albert Einstein, asset allocation, availability heuristic, call centre, Cass Sunstein, choice architecture, continuous integration, Daniel Kahneman / Amos Tversky, desegregation, diversification, diversified portfolio, endowment effect, equity premium, feminist movement, fixed income, framing effect, full employment, George Akerlof, index fund, invisible hand, late fees, libertarian paternalism, loss aversion, Mahatma Gandhi, Mason jar, medical malpractice, medical residency, mental accounting, meta analysis, meta-analysis, Milgram experiment, money market fund, pension reform, presumed consent, price discrimination, profit maximization, rent-seeking, Richard Thaler, Right to Buy, risk tolerance, Robert Shiller, Robert Shiller, Saturday Night Live, school choice, school vouchers, transaction costs, Vanguard fund, Zipcar

But if I don’t have one, I don’t feel an urgent need to buy one. What this means is that people do not assign specific values to objects. When they have to give something up, they are hurt more than they are pleased if they acquire the very same thing. It is also possible to measure loss aversion with gambles. Suppose I ask you whether you want to make a bet. Heads you win $X, tails you lose $100. How much does X have to be for you to take the bet? For most people, the answer to this question is somewhere around $200. This implies that the prospect of winning $200 just offsets the prospect of losing $100. Loss aversion helps produce inertia, meaning a strong desire to stick with your current holdings. If you are reluctant to give up what you have because you do not want to incur losses, then you will turn down trades you might have otherwise made.

In another experiment, half the students in a class received coffee mugs (of course) and half got large chocolate bars. The mugs and the chocolate cost about the same, and in pretests students were as likely to choose one as the other. Yet when offered the opportunity to switch from a mug to a candy bar or vice versa, only one in ten switched. As we will see, loss aversion operates as a kind of cognitive nudge, pressing us not to make changes, even when changes are very much in our interests. Status Quo Bias Loss aversion is not the only reason for inertia. For lots of reasons, people have a more general tendency to stick with their current situation. This phenomenon, which William Samuelson and Richard Zeckhauser (1988) have dubbed the “status quo bias,” has been demonstrated in numerous situations. Most teachers know that students tend to sit in the same seats in class, even without a seating chart.

Louis Germany, organ donations in Gilovich, Tom Give More Tomorrow Goldstein, Dan Goolsbee, Austan Gore, Al Gould, Stephen Jay government: distrust of, libertarian paternalism of, neutrality in, paternalism of, and RECAP, and retirement plans, and slippery slope, starting points provided by, transparency in government bonds greenhouse gas emissions Greenhouse Gas Inventory (GGI), proposed Green Lights, EPA program, Gross, David, group norms, gut feelings Hackman, Gene Halloween night experiment H&R Block, and FAFSA software Harvard School of Public Health Hazard Communication Standard (HCS) health care, birth control pills, choosing, costs of, defensive medicine, Destiny Health Plan, deterrent effect of tort liability in, drug compliance, framing in, freedom of contract in, incentive conflicts in, ineffective lawsuits in, libertarian paternalists on, medical malpractice liability, negligence defined in, “no-fault” system in some countries, organ donations, prescription drug plan, right to sue for negligence, social influences in, treatment options “heuristics and biases” approach Hoffman, Dustin home-building industry home equity loans Home Ownership and Equity Protection Act homo economicus (economic man) “hot-cold empathy gap,” hot-hand theory hot states Houston Natural Gas Howell, William Hoxby, Carolyn Humans: Automatic Systems used by, conformity of, difficult choices for, influenced by a nudge, loss aversion of, and money, social pressures on, use of term Hurricane Katrina Illinois First Person Consent registry imitation incentives, conflicts of, in free markets, in investments, and salience income tax: Automatic Tax Return, compliance in, refunds from index funds inertia: and default option, and loss aversion, and organ donations, power of, and status quo bias, “yeah, whatever,” information, spread of Informed Decisions inheritance INSEAD School of Business, France insurance: costs of, fraught choices in, health Internal Revenue Service (IRS) intuitive thinking, test of investment goods investments, asset allocation in, in company stock, default options, and ERISA, error expected in, feedback in, incentives in, index funds, “lifestyle” funds, mappings in, and market timing, mental accounting in, mutual funds, past performance of, portfolio management, portfolio theory, rates of return, risk in, rules of thumb for, stocks and bonds, structuring complex choices, “target maturity funds,” iPhone and iPod IRAs Johnson, Eric Johnson, Samuel Jones, Rev.


Stocks for the Long Run, 4th Edition: The Definitive Guide to Financial Market Returns & Long Term Investment Strategies by Jeremy J. Siegel

addicted to oil, asset allocation, backtesting, Black-Scholes formula, Bretton Woods, business cycle, buy and hold, buy low sell high, California gold rush, capital asset pricing model, cognitive dissonance, compound rate of return, correlation coefficient, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, dividend-yielding stocks, dogs of the Dow, equity premium, Eugene Fama: efficient market hypothesis, Everybody Ought to Be Rich, fixed income, German hyperinflation, implied volatility, index arbitrage, index fund, Isaac Newton, joint-stock company, Long Term Capital Management, loss aversion, market bubble, mental accounting, Myron Scholes, new economy, oil shock, passive investing, Paul Samuelson, popular capitalism, prediction markets, price anchoring, price stability, purchasing power parity, random walk, Richard Thaler, risk tolerance, risk/return, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, South Sea Bubble, stocks for the long run, survivorship bias, technology bubble, The Great Moderation, The Wisdom of Crowds, transaction costs, tulip mania, Vanguard fund

This tendency to base decisions on the short-term fluctuations in the market has been referred to as myopic loss aversion. Since over longer periods, the probability of stocks showing a loss is much smaller, investors influenced by loss aversion would be more likely to hold stocks if they monitored their performance less frequently. Dave: That’s so true. When I look at stocks in the very short run, they seem so risky that I wonder why anyone holds them. But over the long run, the superior performance of equities is so overwhelming, I wonder why anyone doesn’t hold stocks! IC: Exactly. Shlomo Bernartzi and Richard Thaler claim that myopic loss aversion is the key to solving the equity premium puzzle.27 For years, econ26 Shlomo Bernartzi and Richard Thaler, “Myopic Loss Aversion and the Equity Premium Puzzle,” Quarterly Journal of Economics, 1995, pp. 73–91. 27 See Chapter 8 for a further description of the equity premium puzzle.

262 Index Options 264 Buying Index Options 266 Selling Index Options 267 The Importance of Indexed Products 267 Chapter 16 Market Volatility 269 The Stock Market Crash of October 1987 271 The Causes of the October 1987 Crash 273 Exchange-Rate Policies 274 The Futures Market 275 Circuit Breakers 276 The Nature of Market Volatility 277 Historical Trends of Stock Volatility 278 The Volatility Index (VIX) 281 Recent Low Volatility 283 The Distribution of Large Daily Changes 283 The Economics of Market Volatility 285 The Significance of Market Volatility 286 Chapter 17 Technical Analysis and Investing with the Trend 289 The Nature of Technical Analysis 289 Charles Dow, Technical Analyst 290 The Randomness of Stock Prices 291 Simulations of Random Stock Prices 292 Trending Markets and Price Reversals 294 Moving Averages 295 Testing the Dow Jones Moving-Average Strategy 296 Back-Testing the 200-Day Moving Average 297 The Nasdaq Moving-Average Strategy 300 CONTENTS CONTENTS xiii Distribution of Gains and Losses 301 Momentum Investing 302 Conclusion 303 Chapter 18 Calendar Anomalies 305 Seasonal Anomalies 306 The January Effect 306 Causes of the January Effect 309 The January Effect Weakened in Recent Years 310 Large Monthly Returns 311 The September Effect 311 Other Seasonal Returns 315 Day-of-the-Week Effects 316 What’s an Investor to Do? 318 Chapter 19 Behavioral Finance and the Psychology of Investing 319 The Technology Bubble, 1999 to 2001 320 Behavioral Finance 322 Fads, Social Dynamics, and Stock Bubbles 323 Excessive Trading, Overconfidence, and the Representative Bias 325 Prospect Theory, Loss Aversion, and Holding On to Losing Trades 328 Rules for Avoiding Behavioral Traps 331 Myopic Loss Aversion, Portfolio Monitoring, and the Equity Risk Premium 332 Contrarian Investing and Investor Sentiment: Strategies to Enhance Portfolio Returns 333 Out-of-Favor Stocks and the Dow 10 Strategy 335 PART 5 BUILDING WEALTH THROUGH STOCKS Chapter 20 Fund Performance, Indexing, and Beating the Market 341 The Performance of Equity Mutual Funds 342 Finding Skilled Money Managers 346 xiv Persistence of Superior Returns 348 Reasons for Underperformance of Managed Money 348 A Little Learning Is a Dangerous Thing 349 Profiting from Informed Trading 349 How Costs Affect Returns 350 The Increased Popularity of Passive Investing 351 The Pitfalls of Capitalization-Weighted Indexing 351 Fundamentally Weighted versus Capitalization-Weighted Indexation 353 The History of Fundamentally Weighted Indexation 356 Conclusion 357 Chapter 21 Structuring a Portfolio for Long-Term Growth 359 Practical Aspects of Investing 360 Guides to Successful Investing 360 Implementing the Plan and the Role of an Investment Advisor 363 Concluding Comment 364 Index 367 CONTENTS F O R E W O R D Some people find the process of assembling data to be a deadly bore.

We all display a natural tendency to minimize this discomfort, which makes it difficult for us to recognize our overconfidence. Prospect Theory, Loss Aversion, and Holding On to Losing Trades Dave: I see. Can we talk about individual stocks? Why do I end up holding so many losers in my portfolio? IC: Remember I said before that Kahneman and Tversky had kicked off behavioral finance with prospect theory? A key point in their theory was that individuals form a reference point from which they judge their performance. They found that from that reference point individuals are much more upset about losing a given amount of money than they are from gaining the same amount. They called this behavior loss aversion, and they suggested that the decision to hold or sell an investment will be dramatically influenced by whether your stock has gone up or down— in other words, whether you have had a gain or loss.


pages: 517 words: 139,477

Stocks for the Long Run 5/E: the Definitive Guide to Financial Market Returns & Long-Term Investment Strategies by Jeremy Siegel

Asian financial crisis, asset allocation, backtesting, banking crisis, Black-Scholes formula, break the buck, Bretton Woods, business cycle, buy and hold, buy low sell high, California gold rush, capital asset pricing model, carried interest, central bank independence, cognitive dissonance, compound rate of return, computer age, computerized trading, corporate governance, correlation coefficient, Credit Default Swap, Daniel Kahneman / Amos Tversky, Deng Xiaoping, discounted cash flows, diversification, diversified portfolio, dividend-yielding stocks, dogs of the Dow, equity premium, Eugene Fama: efficient market hypothesis, eurozone crisis, Everybody Ought to Be Rich, Financial Instability Hypothesis, fixed income, Flash crash, forward guidance, fundamental attribution error, housing crisis, Hyman Minsky, implied volatility, income inequality, index arbitrage, index fund, indoor plumbing, inflation targeting, invention of the printing press, Isaac Newton, joint-stock company, London Interbank Offered Rate, Long Term Capital Management, loss aversion, market bubble, mental accounting, money market fund, mortgage debt, Myron Scholes, new economy, Northern Rock, oil shock, passive investing, Paul Samuelson, Peter Thiel, Ponzi scheme, prediction markets, price anchoring, price stability, purchasing power parity, quantitative easing, random walk, Richard Thaler, risk tolerance, risk/return, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, stocks for the long run, survivorship bias, technology bubble, The Great Moderation, the payments system, The Wisdom of Crowds, transaction costs, tulip mania, Tyler Cowen: Great Stagnation, Vanguard fund

This was because the short-term volatility of stocks dissuaded people from choosing that asset class, even though over longer periods it was clearly a better choice. This tendency to base decisions on the short-term fluctuations in the market has been referred to as myopic loss aversion. Since over longer periods, the probability of stocks showing a loss is much smaller, investors influenced by loss aversion would be more likely to hold stocks if they monitored their performance less frequently. Dave: That’s so true. When I look at stocks in the very short run, they seem so risky that I wonder why anyone holds them. But over the long run, the superior performance of equities is so overwhelming, I wonder why anyone doesn’t hold stocks! IC: Exactly. Bernartzi and Thaler claim that myopic loss aversion is the key to solving the equity premium puzzle29 For years, economists have been trying to figure out why stocks have returned so much more than fixed-income investments.

Index Options Buying Index Options Selling Index Options The Importance of Indexed Products Chapter 19 Market Volatility The Stock Market Crash of October 1987 The Causes of the October 1987 Crash Exchange Rate Policies The Futures Market Circuit Breakers Flash Crash—May 6, 2010 The Nature of Market Volatility Historical Trends of Stock Volatility The Volatility Index The Distribution of Large Daily Changes The Economics of Market Volatility The Significance of Market Volatility Chapter 20 Technical Analysis and Investing with the Trend The Nature of Technical Analysis Charles Dow, Technical Analyst The Randomness of Stock Prices Simulations of Random Stock Prices Trending Markets and Price Reversals Moving Averages Testing the Dow Jones Moving-Average Strategy Back-Testing the 200-Day Moving Average Avoiding Major Bear Markets Distribution of Gains and Losses Momentum Investing Conclusion Chapter 21 Calendar Anomalies Seasonal Anomalies The January Effect Causes of the January Effect The January Effect Weakened in Recent Years Large Stock Monthly Returns The September Effect Other Seasonal Returns Day-of-the-Week Effects What’s an Investor to Do? Chapter 22 Behavioral Finance and the Psychology of Investing The Technology Bubble, 1999 to 2001 Behavioral Finance Fads, Social Dynamics, and Stock Bubbles Excessive Trading, Overconfidence, and the Representative Bias Prospect Theory, Loss Aversion, and the Decision to Hold on to Losing Trades Rules for Avoiding Behavioral Traps Myopic Loss Aversion, Portfolio Monitoring, and the Equity Risk Premium Contrarian Investing and Investor Sentiment: Strategies to Enhance Portfolio Returns Out-of-Favor Stocks and the Dow 10 Strategy PART V BUILDING WEALTH THROUGH STOCKS Chapter 23 Fund Performance, Indexing, and Beating the Market The Performance of Equity Mutual Funds Finding Skilled Money Managers Persistence of Superior Returns Reasons for Underperformance of Managed Money A Little Learning Is a Dangerous Thing Profiting from Informed Trading How Costs Affect Returns The Increased Popularity of Passive Investing The Pitfalls of Capitalization-Weighted Indexing Fundamentally Weighted Versus Capitalization-Weighted Indexation The History of Fundamentally Weighted Indexation Conclusion Chapter 24 Structuring a Portfolio for Long-Term Growth Practical Aspects of Investing Guides to Successful Investing Implementing the Plan and the Role of an Investment Advisor Concluding Comment Notes Index FOREWORD In July 1997 I called Peter Bernstein and said I was going to be in New York and would love to lunch with him.

We all display a natural tendency to minimize this discomfort, which makes it difficult for us to recognize our overconfidence. Prospect Theory, Loss Aversion, and the Decision to Hold on to Losing Trades Dave: I see. Can we talk about individual stocks? Why do I end up holding so many losers in my portfolio? IC: Remember I said before that Kahneman and Tversky had kicked off behavioral finance with prospect theory? A key concept in their theory was that individuals form a reference point from which they judge their performance. Kahneman and Tversky found that from that reference point individuals are much more upset about losing a given amount of money than about gaining the same amount. The researchers called this behavior loss aversion, and they suggested that the decision to hold or sell an investment will be dramatically influenced by whether your stock has gone up or down—in other words, whether you have had a gain or loss.


pages: 482 words: 121,672

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition) by Burton G. Malkiel

accounting loophole / creative accounting, Albert Einstein, asset allocation, asset-backed security, beat the dealer, Bernie Madoff, bitcoin, butter production in bangladesh, buttonwood tree, buy and hold, capital asset pricing model, compound rate of return, correlation coefficient, Credit Default Swap, Daniel Kahneman / Amos Tversky, Detroit bankruptcy, diversification, diversified portfolio, dogs of the Dow, Edward Thorp, Elliott wave, Eugene Fama: efficient market hypothesis, experimental subject, feminist movement, financial innovation, financial repression, fixed income, framing effect, George Santayana, hindsight bias, Home mortgage interest deduction, index fund, invisible hand, Isaac Newton, Long Term Capital Management, loss aversion, margin call, market bubble, money market fund, mortgage tax deduction, new economy, Own Your Own Home, passive investing, Paul Samuelson, pets.com, Ponzi scheme, price stability, profit maximization, publish or perish, purchasing power parity, RAND corporation, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, short selling, Silicon Valley, South Sea Bubble, stocks for the long run, survivorship bias, the rule of 72, The Wisdom of Crowds, transaction costs, Vanguard fund, zero-coupon bond, zero-sum game

Note that the expected value of the gain from such a gamble is $75, so this is a very favorable bet. Expected value = ½($250) + ½(–$100) = $75. Kahneman and Tversky concluded that losses were 2½ times as undesirable as equivalent gains were desirable. In other words, a dollar loss is 2½ times as painful as a dollar gain is pleasurable. People exhibit extreme loss aversion, even though a change of $100 of wealth would hardly be noticed for most people with substantial assets. We’ll see later how loss aversion leads many investors to make costly mistakes. Interestingly, however, when individuals faced a situation where sure losses were involved, the psychologists found that they were overwhelmingly likely to take the gamble. Consider the following two alternatives: 1. A sure loss of $750. 2. A 75 percent chance to lose $1,000 and a 25 percent chance to lose nothing.

During periods of falling prices, however, sales volumes decline and individuals let their homes sit on the market for long periods of time with asking prices well above market prices. Extreme loss aversion helps explain sellers’ reluctance to sell their properties at a loss. BEHAVIORAL FINANCE AND SAVINGS Behavioral-finance theory also helps explain why many people refuse to join a 401(k) savings plan at work, even when their company matches their contributions. If one asks an employee who has become used to a particular level of take-home pay to increase his allocation to a retirement plan by one dollar, he will view the resulting deduction (even though it is less than a dollar because contributions to retirement plans are deductible from taxable income up to certain generous amounts) as a loss of current spending availability. Individuals weigh these losses much more heavily than gains. When this loss aversion is coupled with the difficulty of exhibiting self-control, the ease of procrastinating, and the ease of making no changes (status quo bias), it becomes, as psychologists teach us, perfectly understandable why people tend to save too little.

REAPING REWARD BY INCREASING RISK Beta and Systematic Risk The Capital-Asset Pricing Model (CAPM) Let’s Look at the Record An Appraisal of the Evidence The Quant Quest for Better Measures of Risk: Arbitrage Pricing Theory The Fama-French Three-Factor Model A Summing Up 10. BEHAVIORAL FINANCE The Irrational Behavior of Individual Investors Overconfidence Biased Judgments Herding Loss Aversion Pride and Regret Behavioral Finance and Savings The Limits to Arbitrage What Are the Lessons for Investors from Behavioral Finance? 1. Avoid Herd Behavior 2. Avoid Overtrading 3. If You Do Trade: Sell Losers, Not Winners 4. Other Stupid Investor Tricks Does Behavioral Finance Teach Ways to Beat the Market? 11. IS “SMART BETA” REALLY SMART? What Is “Smart Beta”? Four Tasty Flavors: Their Pros and Cons 1.


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Never Split the Difference: Negotiating as if Your Life Depended on It by Chris Voss, Tahl Raz

banking crisis, Black Swan, clean water, cognitive bias, Daniel Kahneman / Amos Tversky, Donald Trump, framing effect, friendly fire, iterative process, loss aversion, market fundamentalism, price anchoring, telemarketer, ultimatum game, uranium enrichment

And people will take greater risks to avoid losses than to achieve gains. That’s called Loss Aversion. That’s why people who statistically have no need for insurance buy it. Or consider this: a person who’s told he has a 95 percent chance of receiving $10,000 or a 100 percent chance of getting $9,499 will usually avoid risk and take the 100 percent certain safe choice, while the same person who’s told he has a 95 percent chance of losing $10,000 or a 100 percent chance of losing $9,499 will make the opposite choice, risking the bigger 95 percent option to avoid the loss. The chance for loss incites more risk than the possibility of an equal gain. Over the next few pages I’ll explain a few prospect theory tactics you can use to your advantage. But first let me leave you with a crucial lesson about loss aversion: In a tough negotiation, it’s not enough to show the other party that you can deliver the thing they want.

Martin Parish, Louisiana, 162–63, 171 “proof of life” and, 34, 147, 148–49, 165, 170 Schilling case, 96, 98–105 terrorists and, 232 “that’s right” and, 101–5 “knowing their religion,” 225, 228–29, 244 offering reasons that reference counterpart’s religion, 231 power of hopes and dreams and, 230–31 similarity principle and, 229–30 Koresh, David, 13 labeling, 19, 50, 54–73, 112 accusation audit, 64–68, 73, 254–55 Assertive (bargaining style) and, 196 avoiding “I,” 56 cranky grandfather example, 59 deescalating angry confrontations with, 58–59 to discover source of incongruence, 176 empathy as a mood enhancer, 62 empathy building and, 239 to extract information, 239, 257–58 of fears, 61–62 fill-in-the-blank examples, 255, 258 Girl Scout fundraiser and, 62–63 intentionally mislabeling an emotion, 91, 94 key lessons of, 71–73 labeling and calming fear, 61, 63, 64, 67, 73 lawyers and “taking the sting out” technique, 65 Lieberman brain imaging study, 55 negativity and, 57–61, 64–68, 70 phrasing the label, 56 Rule of Three and, 177 rules about form and delivery, 55 Schilling kidnapping case and, 103 silences and, 56–57, 71, 72 step one: detecting the other person’s emotional state, 55–56 step two: labeling it aloud, 56 as transformative, 63 Washington Redskins ticket holder script, 60–61 “words, music, and dance” and, 55 Lanceley, Fred, 14–15 Langer, Ellen, 231 late-night FM DJ voice, 19, 31–33, 47 contract discussion and, 34 downward-inflecting statement, 32, 33 general demeanor and delivery, 32 Harlem fugitive stand-off negotiation and, 51 hostage negotiation and, 33–34, 38 lawyer-negotiators, 192–93 Leonsis, Ted, 231 “Lessons of Waco: Proposed Changes in Federal Law Enforcement” (Heymann), 14 leverage, 220–24 Black Swans as leverage multipliers, 220–21, 224, 244 in a kidnapping, 221 loss aversion and, 128 negative, 222–23, 226, 227, 244 normative, 224, 226, 244 personal negotiation styles and, 192 positive, 221–22, 226, 244 what it is, 220 liars. See falsehoods and liars Lieberman, Matthew, 55 listening. See active listening loss aversion, 12, 127–28, 139, 223, 257 Macapagal-Arroyo, Gloria, 140 Malhotra, Deepak, 178, 179, 233 Mehrabian, Albert, 176 Memphis Bar Association, 132 Middle Eastern merchants, 33 Miller, George A., 28 Miller, Winnie, 227 mindset finding and acting on Black Swans and, 218, 219 as key to successful negotiation, 43 multiple hypotheses approach, 25 positive, 33, 47 ready-to-walk, 204–5 win-win, 115 mirroring (isopraxism), 19, 35–36, 44, 48, 70, 71, 183 active listening and, 103 body language and, 36 to elicit information, 185 four step process for workplace negotiation, 44–46 reaction to use of “fair” in negotiations, 125 silences and, 37, 44, 72 use with Assertive bargainers, 196 use with assertive people, 191–92 verbal, 36 Wiseman waiter study, 36 Misino, Dominick, 41–42 Mnookin, Robert, 2–4, 5 Moore, Don A., 120 Moore, Margaret, 214–15, 217 Mousavian, Seyed Hossein, 124 MSU (making shit up) approach, 30 Mueller, Robert, 143 negotiation.

There’s the Framing Effect, which demonstrates that people respond differently to the same choice depending on how it is framed (people place greater value on moving from 90 percent to 100 percent—high probability to certainty—than from 45 percent to 55 percent, even though they’re both ten percentage points). Prospect Theory explains why we take unwarranted risks in the face of uncertain losses. And the most famous is Loss Aversion, which shows how people are statistically more likely to act to avert a loss than to achieve an equal gain. Kahneman later codified his research in the 2011 bestseller Thinking, Fast and Slow.3 Man, he wrote, has two systems of thought: System 1, our animal mind, is fast, instinctive, and emotional; System 2 is slow, deliberative, and logical. And System 1 is far more influential. In fact, it guides and steers our rational thoughts.


pages: 1,088 words: 228,743

Expected Returns: An Investor's Guide to Harvesting Market Rewards by Antti Ilmanen

Andrei Shleifer, asset allocation, asset-backed security, availability heuristic, backtesting, balance sheet recession, bank run, banking crisis, barriers to entry, Bernie Madoff, Black Swan, Bretton Woods, business cycle, buy and hold, buy low sell high, capital asset pricing model, capital controls, Carmen Reinhart, central bank independence, collateralized debt obligation, commoditize, commodity trading advisor, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, debt deflation, deglobalization, delta neutral, demand response, discounted cash flows, disintermediation, diversification, diversified portfolio, dividend-yielding stocks, equity premium, Eugene Fama: efficient market hypothesis, fiat currency, financial deregulation, financial innovation, financial intermediation, fixed income, Flash crash, framing effect, frictionless, frictionless market, G4S, George Akerlof, global reserve currency, Google Earth, high net worth, hindsight bias, Hyman Minsky, implied volatility, income inequality, incomplete markets, index fund, inflation targeting, information asymmetry, interest rate swap, invisible hand, Kenneth Rogoff, laissez-faire capitalism, law of one price, London Interbank Offered Rate, Long Term Capital Management, loss aversion, margin call, market bubble, market clearing, market friction, market fundamentalism, market microstructure, mental accounting, merger arbitrage, mittelstand, moral hazard, Myron Scholes, negative equity, New Journalism, oil shock, p-value, passive investing, Paul Samuelson, performance metric, Ponzi scheme, prediction markets, price anchoring, price stability, principal–agent problem, private sector deleveraging, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, random walk, reserve currency, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, riskless arbitrage, Robert Shiller, Robert Shiller, savings glut, selection bias, Sharpe ratio, short selling, sovereign wealth fund, statistical arbitrage, statistical model, stochastic volatility, stocks for the long run, survivorship bias, systematic trading, The Great Moderation, The Myth of the Rational Market, too big to fail, transaction costs, tulip mania, value at risk, volatility arbitrage, volatility smile, working-age population, Y2K, yield curve, zero-coupon bond, zero-sum game

These stories are especially relevant now that two major bear markets during the past decade may cast a long shadow on investor behavior. The two main behavioral explanations both require combining loss aversion with one other behavioral feature—a short time horizon (myopia) or the house money effect:• The myopic loss aversion model relies on a variant of mental accounting related to the investment time horizon (evaluation period). A given expected return advantage will attract investors more, the longer their investment horizon is. If investors evaluate their portfolios very frequently, the odds of risky assets outperforming riskless ones are close to 50/50 and loss aversion kicks in. Over longer horizons, the odds steadily improve. A typical degree of loss aversion applied to annual changes in financial wealth can justify an equity premium of 6.5%, suggesting that an annual portfolio evaluation period is plausible for the overall market

More risk preferences The house money effect is an important example of mental accounting. Gamblers tend to become less loss averse and more willing to take risks when they are ahead (“playing with house money)”. Greater willingness to gamble after recent gains suggests that losses are easier to take when they can be mentally added to earlier gains. At first blush, this may sound inconsistent with PT. However, PT as described above pertains to one-off gambles. Risk preferences in a sequence of gambles depend on how prior gains and losses influence loss aversion over time. An experimental study by Thaler and Johnson finds evidence in favor of the house money effect—more aggressive risk taking following successful trading, and cautiousness following losses. Such dynamic loss aversion is broadly consistent with wealth-dependent risk aversion. There is one interesting exception to caution after losses: if investors have a chance to fully recover a prior loss, they will accept gambles that they would normally reject.

A typical degree of loss aversion applied to annual changes in financial wealth can justify an equity premium of 6.5%, suggesting that an annual portfolio evaluation period is plausible for the overall market. • Yale’s Nicholas Barberis and co-authors develop an equilibrium model in which investors derive utility both from consumption and from annual changes in wealth. They too assume a typical degree of loss aversion (just above 2) but find that a model with constant loss aversion cannot fully explain the equity premium puzzle. However, they can resolve the puzzle if they include in their model the “house money effect”—the idea that the degree of loss aversion varies dynamically with prior gains and losses. The model thus implies that investors’ risk attitudes become more conservative in down-markets. The next section shows that estimates of the equity premium have edged lower since the 1990s. During the Great Moderation years, it was popular to argue that lower macro-volatility and investor learning about equities’ long-run return advantage could justify a sustained fall in the required equity premium.


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Retirementology: Rethinking the American Dream in a New Economy by Gregory Brandon Salsbury

Albert Einstein, asset allocation, buy and hold, carried interest, Cass Sunstein, credit crunch, Daniel Kahneman / Amos Tversky, diversification, estate planning, financial independence, fixed income, full employment, hindsight bias, housing crisis, loss aversion, market bubble, market clearing, mass affluent, Maui Hawaii, mental accounting, mortgage debt, mortgage tax deduction, negative equity, new economy, RFID, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, side project, Silicon Valley, Steve Jobs, the rule of 72, Yogi Berra

Kahneman in 2004, this pioneer in behavioral finance told me about how his discipline doesn’t assume perfect rationality, which is why perceptual bias, complexity, and emotions like pride and anger, illustrated in our exercise, can overshadow sound financial decisions. For example, research from Dr. Kahneman and Dr. Amos Tversky showed that investors are more sensitive to decreases in the value of their portfolio than to increases in value.41 Even in good times, many investors tend to suffer from what experts refer to as “myopic loss aversion”—a basic tenet from the field of behavioral finance, which holds that people psychologically weigh losses twice as heavily as gains. Here’s an example of myopic loss aversion. I flip a coin: Heads, you win $110. Tails, you lose $100. Will you take the bet? Behavioral finance shows us that there will be few takers of the gamble. How much would most people need to win before they would be willing to take the gamble? $120? $140? $180? The research reveals before the majority of people will be willing to take the risk, they would need to receive at least twice the amount of the possible loss.

Then...pre-meltdown • In November 2007, the Consumer Confidence Survey checked in at a rather robust score of 87.3.5 • On October 8, 2007, the Dow was at 14,043.6 Now...post-meltdown • In October 2008, the Consumer Confidence Survey had dropped to 38%, the most pessimistic number in more than 25 years.7 In fact, 62% of American adults now believe that today’s children will not be better off than their parents.8 • On September 15, 2008, the stock market would begin a three-week slide that would see the Dow lose 2,937 points, or 26% of its value.9 The Retirement Brain Game Regret and pride—People avoid actions that create regret and seek actions that cause pride. Regret is emotional pain. Pride is emotional joy. Is this causing us to buy high and sell low? Research indicates that two of the most troublesome emotions that plague investors are pride and regret. Myopic loss aversion—One type of event in particular has overwhelming, disproportional impact on investors—loss. As we discussed in the Introduction, research shows that, on average, before people would be willing to risk loss, they would need to see their gains reach at least 2.25 times the potential loss. This is what led Dr. Richard Thaler to conclude that losses hurt 2.25 times more than gains satisfy. When most investors experience loss, they spend the rest of their lives in fear of it.

Unfortunately, after a market downturn, many people fall into this pattern of buying high and selling low. Our fear, our confidence, and our emotions convince us to take irrational chances with our investments. We often pull money out of the market when the market goes down and wait until it gets back to its highs to buy again. We repeat the same pattern of buying high and selling low. If you’re doing this, you’re not alone. Loss: A Cautionary Tale What myopic loss aversion means is that we have become so short-sighted, so fearful of loss, so concerned with losing our money, that we often make no decision, or make the wrong decision—either of which may prove costly. For example, suppose your child just entered college and the $10,000 bill for his tuition is due. You can either sell Stock A, for which you paid $20,000 and is now worth $10,000. Or you can sell some of Stock B for which you paid $20,000 and is now worth $30,000.


pages: 306 words: 85,836

When to Rob a Bank: ...And 131 More Warped Suggestions and Well-Intended Rants by Steven D. Levitt, Stephen J. Dubner

Affordable Care Act / Obamacare, Airbus A320, airport security, augmented reality, barriers to entry, Bernie Madoff, Black Swan, Broken windows theory, Captain Sullenberger Hudson, creative destruction, Daniel Kahneman / Amos Tversky, deliberate practice, feminist movement, food miles, George Akerlof, global pandemic, information asymmetry, invisible hand, loss aversion, mental accounting, Netflix Prize, obamacare, oil shale / tar sands, Pareto efficiency, peak oil, pre–internet, price anchoring, price discrimination, principal–agent problem, profit maximization, Richard Thaler, Sam Peltzman, security theater, Ted Kaczynski, the built environment, The Chicago School, the High Line, Thorstein Veblen, transaction costs, US Airways Flight 1549

Unfortunately, his appearance on the PBA’s senior tour is unlikely: wanting to go out on top, he has vowed never to bowl again. True to his word, Levitt hasn’t touched a bowling ball since. Loss Aversion in the NFL (SJD) Football coaches are known for being extraordinarily conservative when it comes to calling risky plays, since a single bad decision (or even a good decision that doesn’t work out) can get you fired. In the jargon of behavioral economics, coaches are “loss-averse”; this concept, pioneered by Amos Tversky and Daniel Kahneman, holds that we experience more pain with a loss of x than we experience pleasure with a gain of x. Who experiences loss aversion? Well, just about everyone: day traders, capuchin monkeys, and especially football coaches. Which is why the last play of yesterday’s Chiefs-Raiders game was so interesting.

If instead we tell them we will pay them one month later, they don’t do any better than with no incentives at all. This is bad news for those who argue that payoffs that come years or decades in the future are sufficient to motivate students. The very best results come when we give the students the money before the test, and then we take the money back if they don’t meet the standards. This result is consistent with what psychologists call “loss aversion.” With young kids, it is a lot cheaper to bribe them with trinkets like trophies and whoopee cushions, but cash is the only thing that works for the older students. It is remarkable how offended people get when you pay students for doing well—so many negative e-mails and comments. Roland Fryer endured the same onslaught as he has experimented with financial incentives in cities around the U.S.

.”: “Brandon Adams . . . a great writer”: See Adams, Broke: A Poker Novel (iUniverse, 2006). 198 “WHAT ARE MY CHANCES OF MAKING THE CHAMPIONS TOUR . . .”: “My friend Anders Ericsson popularized the magic number of 10,000 hours of practice”: See Dubner and Levitt, “A Star is Made,” The New York Times Magazine, May 7, 2006; K. Anders Ericsson, Neil Charness, Paul J. Feltovich, and Robert R. Hoffman, The Cambridge Handbook of Expertise and Expert Performance, Cambridge University Press, 2006. 206 “LOSS AVERSION IN THE NFL”: “Just about everyone . . . capuchin monkeys”: See Dubner and Levitt, “Monkey Business,” The New York Times Magazine, June 5, 2005. 208 “BILL BELICHICK IS GREAT”: “Teams seem to punt way too much”: See David Romer, “Do Firms Maximize? Evidence from Professional Football,” Journal of Political Economy 118, no. 2 (2006). / 209 “I’ve seen the same thing in my research on penalty kicks in soccer”: Pierre-André Chiappori, Steven D.


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The Irrational Bundle by Dan Ariely

accounting loophole / creative accounting, air freight, Albert Einstein, Alvin Roth, assortative mating, banking crisis, Bernie Madoff, Black Swan, Broken windows theory, Burning Man, business process, cashless society, Cass Sunstein, clean water, cognitive dissonance, computer vision, corporate governance, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, end world poverty, endowment effect, Exxon Valdez, first-price auction, Frederick Winslow Taylor, fudge factor, George Akerlof, Gordon Gekko, greed is good, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, Kenneth Arrow, knowledge economy, knowledge worker, lake wobegon effect, late fees, loss aversion, Murray Gell-Mann, new economy, Peter Singer: altruism, placebo effect, price anchoring, Richard Feynman, Richard Thaler, Saturday Night Live, Schrödinger's Cat, second-price auction, Shai Danziger, shareholder value, Silicon Valley, Skype, software as a service, Steve Jobs, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, ultimatum game, Upton Sinclair, Walter Mischel, young professional

We chose to do this by adding the force of loss aversion to the mix.* Loss aversion is the simple idea that the misery produced by losing something that we feel is ours—say, money—outweighs the happiness of gaining the same amount of money. For example, think about how happy you would be if one day you discovered that due to a very lucky investment, your portfolio had increased by 5 percent. Contrast that fortunate feeling to the misery that you would feel if, on another day, you discovered that due to a very unlucky investment, your portfolio had decreased by 5 percent. If your unhappiness with the loss would be higher than the happiness with the gain, you are susceptible to loss aversion. (Don’t worry; most of us are.) To introduce loss aversion into our experiment, we prepaid participants in the small-bonus condition 24 rupees (6 times 4).

After all, who could blame the poor guy? This incident made us realize that including loss aversion might not work in this experiment, so we switched to paying people at the end. There was another reason why we wanted to prepay participants: we wanted to try to capture the psychological reality of bonuses in the marketplace. We thought that paying up front was analogous to the way many professionals think about their expected bonuses every year. They come to think of the bonuses as largely given and as a standard part of their compensation. They often even make plans for spending it. Perhaps they eye a new house with a mortgage that would otherwise be out of reach or plan a trip around the world. Once they start making such plans, I suspect that they might be in the same loss aversion mind-set as the prepaid participants. Thinking versus Doing We were certain that there would be some limits to the negative effect of high reward on performance—after all, it seemed unlikely that a significant bonus would reduce performance in all situations.

Given the arm’s limited functionality, the pain I experienced and am still experiencing, and what I now know about flawed decision making, I suspect that keeping my arm was, in a cost/benefit sense, a mistake. Let’s look at the biases that affected me. First, it was difficult for me to accept the doctors’ recommendation because of two related psychological forces we call the endowment effect and loss aversion. Under the influence of these biases, we commonly overvalue what we have and we consider giving it up to be a loss. Losses are psychologically painful, and, accordingly, we need a lot of extra motivation to be willing to give something up. The endowment effect made me overvalue my arm, because it was mine and I was attached to it, while loss aversion made it difficult for me to give it up, even when doing so might have made sense. A second irrational influence is known as the status quo bias. Generally speaking, we tend to want to keep things as they are; change is difficult and painful, and we’d rather not change anything if we can help it.


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Adaptive Markets: Financial Evolution at the Speed of Thought by Andrew W. Lo

"Robert Solow", Albert Einstein, Alfred Russel Wallace, algorithmic trading, Andrei Shleifer, Arthur Eddington, Asian financial crisis, asset allocation, asset-backed security, backtesting, bank run, barriers to entry, Berlin Wall, Bernie Madoff, bitcoin, Bonfire of the Vanities, bonus culture, break the buck, Brownian motion, business cycle, business process, butterfly effect, buy and hold, capital asset pricing model, Captain Sullenberger Hudson, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, corporate governance, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, Daniel Kahneman / Amos Tversky, delayed gratification, Diane Coyle, diversification, diversified portfolio, double helix, easy for humans, difficult for computers, Ernest Rutherford, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, Fall of the Berlin Wall, financial deregulation, financial innovation, financial intermediation, fixed income, Flash crash, Fractional reserve banking, framing effect, Gordon Gekko, greed is good, Hans Rosling, Henri Poincaré, high net worth, housing crisis, incomplete markets, index fund, interest rate derivative, invention of the telegraph, Isaac Newton, James Watt: steam engine, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Meriwether, Joseph Schumpeter, Kenneth Rogoff, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, Louis Pasteur, mandelbrot fractal, margin call, Mark Zuckerberg, market fundamentalism, martingale, merger arbitrage, meta analysis, meta-analysis, Milgram experiment, money market fund, moral hazard, Myron Scholes, Nick Leeson, old-boy network, out of africa, p-value, paper trading, passive investing, Paul Lévy, Paul Samuelson, Ponzi scheme, predatory finance, prediction markets, price discovery process, profit maximization, profit motive, quantitative hedge fund, quantitative trading / quantitative finance, RAND corporation, random walk, randomized controlled trial, Renaissance Technologies, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Robert Shiller, Robert Shiller, Sam Peltzman, Shai Danziger, short selling, sovereign wealth fund, Stanford marshmallow experiment, Stanford prison experiment, statistical arbitrage, Steven Pinker, stochastic process, stocks for the long run, survivorship bias, Thales and the olive presses, The Great Moderation, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Malthus, Thorstein Veblen, Tobin tax, too big to fail, transaction costs, Triangle Shirtwaist Factory, ultimatum game, Upton Sinclair, US Airways Flight 1549, Walter Mischel, Watson beat the top human players on Jeopardy!, WikiLeaks, Yogi Berra, zero-sum game

It became obvious to them that, when people were faced with economic choices with uncertain outcomes, they had peculiar but systematic biases in their behavior. Kahneman and Tversky set out to test these systematic biases in an experimental setting. From a financial perspective, one of the most important of these biases is called loss aversion. When we make choices involving risky outcomes, most of us place greater weight on losses than on gains. We’re much more averse to losing in a risky situation than simple mathematics would predict. Loss aversion is so embedded in our behavior that it can be difficult for us to see. Kahneman and Tversky brought it to light by ruthlessly stripping the behavior down to its bare minimum in an experimental setting. The following example is a slightly modified version of an experiment Kahneman and Tversky conducted at Stanford which I use in my own classes—in my version, the prizes have been increased by several orders of magnitude, since the pool of students I work with are mostly MBAs, and they’re used to dealing with bigger numbers.11 If You’re So Smart, Why Aren’t You Rich?

Some economists claim that regulatory forbearance is partly responsible for the recent financial crisis,14 offering elaborate explanations for why regulatory forbearance might occur, such as global competition among regulatory agencies and the political economy of regulation.15 But a more mundane explanation is loss aversion: a sure loss to the regulator if she calculates that a bank’s assets have declined, and a riskier but less psychologically painful alternative if she maintains the older, higher estimate. Although we still have much to learn about the behavior of bank supervisors and other financial regulators in the years leading up to the financial crisis,16 we shouldn’t dismiss the possibility that they didn’t react sooner simply because they were too human. PROBABILITY MATCHING AND MARCH MADNESS Loss aversion is only one of many behavioral biases discovered by psychologists like Tversky and Kahneman. Just as the human eye is susceptible to optical illusions, the human brain is susceptible to illusions about risk and probability.

What happened to “a bird in the hand is worth two in the bush”? When it comes to losses, most people are willing to take much greater risks to avoid losses, even if those risks aren’t compensated by higher expected payoffs. Apparently, a thorn in the hand is worth much less than the possibility of many thorns in the bush if that possibility also includes a chance of avoiding thorns altogether. Why should loss aversion be interesting to anyone other than academics? It’s because this behavior is especially counterproductive in a financial context. To see why, take the combination of Alfa and Delta, the two choices most people pick. This pair is equivalent to a single investment that pays $240,000 with 25 percent probability and loses $760,000 with 75 percent probability (Alfa yields $240,000 for sure, and with 25 percent probability Delta loses nothing in which case the $240,000 is yours to keep, but with 75 percent probability Delta loses $1 million in which case your total earnings are $240,000 minus $1 million for a net loss of $760,000).


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The Bogleheads' Guide to Investing by Taylor Larimore, Michael Leboeuf, Mel Lindauer

asset allocation, buy and hold, buy low sell high, corporate governance, correlation coefficient, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, Donald Trump, endowment effect, estate planning, financial independence, financial innovation, high net worth, index fund, late fees, Long Term Capital Management, loss aversion, Louis Bachelier, margin call, market bubble, mental accounting, money market fund, passive investing, Paul Samuelson, random walk, risk tolerance, risk/return, Sharpe ratio, statistical model, stocks for the long run, survivorship bias, the rule of 72, transaction costs, Vanguard fund, yield curve, zero-sum game

But when it comes to investing your hard-earned dollars, please keep this thought in mind: the stock market is a very expensive place to learn that neither you nor anyone else is endowed with the gift of investment prophecy. Loss Aversion Do you check your portfolio every day? Do you sell a stock or mutual fund when it earns a healthy return to lock in the profit? Do you sell stocks/mutual funds whenever you see them going down? Are you a young person who keeps most of your savings in bonds or safe, ultraconservative investments? If so, you may be hurting your potential returns through loss aversion. Loss aversion is the flip side of overconfidence. Although overconfidence tends to make us overly bold, loss aversion makes us overly timid about investing. Experiments have determined that at the emotional level, we feel the pain of a $100 loss twice as much as we enjoy the benefit of a $100 gain.

Perhaps you know people who lost a fortune in the stock market crash of 1929, the 1973 to 1974 bear market, or the tech wreck of 2000 who now keep all their money in bank certificates of deposit. They may think their investments are risk free. However, if you factor in the taxes due on the interest earned and inflation, many of them are actually losing purchasing power. What's perceived as safe isn't always as safe as those who are loss averse believe it to be. Paralysis by Analysis This investment trap is the first cousin to loss aversion. When it comes time to invest, we have literally thousands of funds to choose from and an abundance of noise telling us why we should invest in a certain way. The more choices people are given, the harder it becomes to choose one. As a result, some people don't make a choice and don't invest. The problem is that by failing to invest they incur an opportunity loss.

During those few minutes a day, we highly recommend not making any investment decisions. HOW TO ESCAPE THE EMOTIONAL TRAPS Finally, for the common emotional traps mentioned earlier, we offer the following tools for escape: • Recency bias. Never assume today's results predict tomorrow's. It's a changing world. • Overconfidence. No one can consistently predict short-term movements in the market. This means you and/or the person investing your money. • Loss aversion. Be a risk manager instead of a risk avoider. Believing you are avoiding risk can be a costly illusion. • Paralysis by analysis. Every day you don't invest is a day less you'll have the power of compounding working for you. Put together an intelligent investment plan and get started. If you need help, seek out a good financial planner to assist you. • The endowment effect. Just because you own it, or are a part of it, doesn't automatically mean it's worth more.


pages: 280 words: 79,029

Smart Money: How High-Stakes Financial Innovation Is Reshaping Our WorldÑFor the Better by Andrew Palmer

Affordable Care Act / Obamacare, algorithmic trading, Andrei Shleifer, asset-backed security, availability heuristic, bank run, banking crisis, Black-Scholes formula, bonus culture, break the buck, Bretton Woods, call centre, Carmen Reinhart, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Graeber, diversification, diversified portfolio, Edmond Halley, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, eurozone crisis, family office, financial deregulation, financial innovation, fixed income, Flash crash, Google Glasses, Gordon Gekko, high net worth, housing crisis, Hyman Minsky, implied volatility, income inequality, index fund, information asymmetry, Innovator's Dilemma, interest rate swap, Kenneth Rogoff, Kickstarter, late fees, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, margin call, Mark Zuckerberg, McMansion, money market fund, mortgage debt, mortgage tax deduction, Myron Scholes, negative equity, Network effects, Northern Rock, obamacare, payday loans, peer-to-peer lending, Peter Thiel, principal–agent problem, profit maximization, quantitative trading / quantitative finance, railway mania, randomized controlled trial, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, short selling, Silicon Valley, Silicon Valley startup, Skype, South Sea Bubble, sovereign wealth fund, statistical model, Thales of Miletus, transaction costs, Tunguska event, unbanked and underbanked, underbanked, Vanguard fund, web application

So the behavioralists have had to fight back with another clever technique known as “auto escalation,” an opt-in feature that automatically increases employees’ savings rates whenever they get a pay rise until they hit a maximum level of contributions.17 By synchronizing contribution increases and salary hikes, this “Save More Tomorrow” option also gets around another human foible known as “loss aversion,” which means that people weigh losses more heavily than gains. Loss aversion appears to have very deep neurological roots. In a 2005 study, a trio of academics from Yale introduced a colony of capuchin monkeys to the concept of money. The monkeys were first trained to understand that they could exchange a token for food. Having grasped its purpose, some familiar patterns of behavior emerged. The monkeys responded to price signals, buying more of one food than another when its relative price dropped.

People who are paid to think about the industry’s future wonder about the potential for an “old people’s bank” for the baby boomers, whose services would be explicitly based around budgeting, managed drawdowns of savings, and the like. In the meantime, the annuity is the obvious answer to the problem of not knowing when you are going to die, but it has its flaws. If you have a small pension pot, an annuity may deliver only a meager stream of income; fixed annuities offer no protection against the effect of inflation; and loss aversion means that people hate the idea of “losing out” to the annuity provider if they die early. Another option is to squeeze more juice out of the assets that older people do own. The biggest of those is likely to be their houses. In 2009 half of home owners aged sixty-two and older in the United States had at least 55 percent of their net worth tied up in home equity. The most obvious way for a retiree to monetize this investment is by selling the house and either renting or “downsizing” into a smaller house.

., 32 Keys, Benjamin, 48 Kharroubi, Enisse, 79 Kickstarter, 172 King, Stephen, 99 Klein, David, 182 Krugman, Paul, xv Lahoud, Sal, 166 Lang, Luke, 153, 161–162 Laplanche, Renaud, 179, 184, 188, 190, 193–194, 196–197 Latency, 53 Law of large numbers, 17 Layering, 57 Left-digit bias, 46 Lehman Brothers, x, 44, 65 Lending direct, 84 marketplace, 184 payday, 200 relationship-based, 11, 151, 206–208 secured, xiv, 76 unsecured, 206 See also Loans; Peer-to-peer lending Lending Club, 172, 179–180, 182–184, 187, 189, 194–195, 197 Leonardo of Pisa (Fibonacci), 19 Lerner, Josh, 59 Lethal pandemic, risk-modeling for demographic profile, 230 exceedance-probability curve, 231–232, 232 figure 3 historical data, 228–229 infectiousness and virulence, 229–230 location of outbreak, 230–231 Leverage, 51, 70–71, 80, 186, 188 Leverage ratio, 76–77 Lewis, Michael, 57 Liber Abaci or Book of Calculation (Fibonacci), 19 LIBOR (London Interbank Offered Rate), 41 Liebman, Jeffrey, 98 Life expectancy government reaction to, 128–129 projections of, 124–127, 126 figure 2 ratio of young to older people, 127–128 Life-insurance policies, 142 Life-settlements industry, 142–143 Life table, 20 Limited liability, 212 Liquidity, 12–14, 39, 185–186 List, John, 109 The Little Book of Behavioral Investing (Montier), 156 Lo, Andrew, 113–115, 117–123 Loans low-documentation, 48–49 secured, 76 small business, 181, 216 student, 164, 166–167, 169–171, 182 syndicated, 41 Victory Loans, 28 See also Lending; Peer-to-Peer lending Logistic regression, 201 London, early fire insurance in, 16–17 London, Great Fire of, 16 London Interbank Offered Rate (LIBOR), 41 Long-Term Capital Management, 123 Longevity, betting on, 143–144 Loss aversion, 136 Lotteries, 212, 213 Low-documentation loans, 48–49 Lumni, 165, 168, 175 Lustgarten, Anders, 111 Lynn, Jeff, 160–161 Mack, John, 180 Mahwah, New Jersey, 52, 53 Marginal borrowers assessment of, 216–217 behavioral finance and, 208–214 industrialization of credit, 206 microfinance and, 203 savings schemes, 209–214 small businesses, 215–219 unsecured lending to, 206 Wonga, 203, 205, 208 Marginal borrowers (continued) ZestFinance, 199, 202, 205–206 Maritime piracy, solutions to, 151–152 Maritime trade, role of in history of finance, 3, 7–8, 14, 17, 23 Market makers, 15–16, 55 MarketInvoice, 195, 207, 217–218 Marketplace lending, 184 Markowitz, Harry, 118 Massachusetts, use of inflation-protected bonds in, 26 Massachusetts, use of social-impact bonds in, 98 Matching engine, 52 Maturity transformation, 12–13, 187–188, 193 McKinsey & Company, ix, 42 Mercator Advisory Group, 203 Merrill, Charles, 28 Merrill, Douglas, 199, 201 Merrill Lynch, 28 Merton, Robert, 31, 113–114, 123–124, 129–132, 142, 145 Mian, Atif, 204 Michigan, University of, financial survey by, 134–135 Microfinance, 203 Micropayment model, 217 Microwave technology, 53 The Million Adventure, 213–214 Minsky, Hyman, 42 Minsky moment, 42 Mississippi scheme, 36 Mitchell, Justin, 166–167 Momentum Ignition, 57 Monaco, modeling risk of earthquake in, 227 Money, history of, 4–5 Money illusion, 73–74 Money laundering, 192 Money-market funds, 43, 44 Monkeys, Yale University study of loss aversion with, 136 Montier, James, 156–157 Moody, John, 24 Moody’s, 24, 235 Moore’s law, 114 Morgan Stanley, 188 Mortgage-backed securities, 49, 233 Mortgage credit by ZIP code, study of, 204 Mortgage debt, role of in 2007–2008 crisis, 69–70 Mortgage products, unsound, 36–37 Mortgage securitization, 47 Multisystemic therapy, 96 Munnell, Alicia, 129 Naked credit-default swaps, 143 Nature Biotechnology, on drug-development megafunds, 118 “Neglected Risks, Financial Innovation and Financial Fragility” (Gennaioli, Shleifer, and Vishny), 42 Network effects, 181 New York, skyscraper craze in, 74–75 New York City, prisoner-rehabilitation program in, 108 New York Stock Exchange (NYSE), 31, 52, 53, 61, 64 New York Times, Merrill Lynch ad in, 28 Noncorrelated assets, 122 Nonprofits, growth of in United States, 105–106 Northern Rock, x NYMEX, 60 NYSE Euronext, 52 NYSE (New York Stock Exchange), 31, 52, 53, 61, 64 OECD (Organization for Economic Co-operation and Development), 128, 147 Oldfield, Sean, 67–68, 80–84 OnDeck, 216–218 One Service, 94–95, 105, 112 Operating expense ratio, 188–189 Options, 15, 124 Order-to-trade ratios, 63 Oregon, interest in income-share agreements, 172, 176 Organization for Economic Co-operation and Development (OECD), 128, 147 Overtrading, 24 Packard, Norman, 60 Pandit, Vikram, 184 Park, Sun Young, 233 Partnership mortgage, 81 Pasion, 11 Pave, 166–168, 173, 175, 182 Payday lending Consumer Financial Protection Bureau, survey on, 200 information on applicants, acquisition of, 202 underwriting of, 201 PayPal, 219 Peak child, 127 Peak risk, 228 Peer-to-peer lending advantages of, 187–189 auction system, 195 big investors in, 183 borrowers, assessment of, 197 in Britain, 181 commercial mortgages, 181 CommonBond, 182, 184, 197 consumer credit, 181 diversification, 196 explained, 180 Funding Circle, 181–182, 189, 197 investors in, 195 Lending Club, 179–180, 182–184, 187, 189, 194–195, 197 network effects, 181 ordinary savers and, 184 Prosper, 181, 187, 195 RateSetter, 181, 187, 196 Relendex, 181 risk management, 195–197 securitization, 183–184, 196 Peer-to-peer lending (continued) small business loans, 181 SoFi, 184 student loans, 182 Zopa, 181, 187, 188, 195 Pensions, cost of, 125–126 Perry, Rick, 142–143 Peterborough, England, social-impact bond pilot in, 90–92, 94–95, 104–105, 112 Petri, Tom, 172 Pharmaceuticals, decline of investment in, 114–115 Piracy Reporting Centre, International Maritime Bureau, 151 Polese, Kim, 210 Poor, Henry Varnum, 24 “Portfolio Selection” (Markowitz), 118 Prediction Company, 60–61 Preferred shares, 25 Prepaid cards, 203 Present value of cash flows, 19 Prime borrowers, 197 Prince, Chuck, 50–51, 62 Principal-agent problem, 8 Prisoner rehabilitation programs, 90–91, 94–95, 98, 108, 112 Private-equity firms, 69, 85, 91, 105, 107 Projection bias, 72–73 Property banking crises and, xiv, 69 banking mistakes involving, 75–80 behavioral biases and, 72–75 dangerous characteristics of, 70–72 fresh thinking, need for, xvii, 80 investors’ systematic errors in, 74–75 perception of as safe investment, 76, 80 Prosper, 181, 187, 195 Provisioning funds, 187 Put options, 9, 82 Quants, 19, 63, 113 QuickBooks, 218 Quote stuffing, 57 Raffray, André-François, 144 Railways, affect of on finance, 23–25 Randomized control trials (RCTs), 101 Raphoen, Christoffel, 15–16 Raphoen, Jan, 15–16 RateSetter, 181, 187, 196 RCTs (randomized control trials), 101 Ready for Zero, 210–211 Rectangularization, 125, 126 figure 2 Regulation NMS, 61 Reinhart, Carmen, 35 Reinsurance, 224 Relendex, 181 Rentes viagères, 20 Repurchase “repo” transactions, 15, 185 Research-backed obligations, 119 Reserve Primary Fund, 44 Retirement, funding for anchoring effect, 137–138 annuities, 139 auto-enrollment in pension schemes, 135 auto-escalation, 135–136 conventional funding, 127–128 decumulation, 138–139 government reaction to increased longevity, 128–129 home equity, 139–140 life expectancy, projections of, 124–127, 126 figure 2 life insurance policies, cash-surrender value of, 142 personal retirement savings, 128–129, 132–133 replacement rate, 125 reverse mortgage, 140–142 savings cues, experiment with, 137 SmartNest, 129–131 Reverse mortgages, 140–142 Risk-adjusted returns, 118 Risk appetite, 116 Risk assessment, 24, 45, 77–78, 208 Risk aversion, 116, 215 Risk-based capital, 77 Risk-based pricing model, 176 Risk management, 55, 117–118, 123, 195–197 Risk Management Solutions, 222 Risk sharing, 8, 82 Risk-transfer instrument, 226 Risk weights, 77–78 Rogoff, Kenneth, 35 “The Role of Government in Education” (Friedman), 165 Roman Empire business corporation in, 7 financial crisis in, 36 forerunners of banks in, 11 maritime insurance in, 8 Rotating Savings and Credit Associations (ROSCAs), 209–210 Roulette wheel, use of in experiment on anchoring, 138 Royal Bank of Scotland, 186 Rubio, Marco, 172 Russia, mortgage market in, 67 S-curve, in diffusion of innovations, 45 Salmon, Felix, 155 Samurai bonds, 27 Satsuma Rebellion (1877), 27 Sauter, George, 58 Save to Win, 214 Savings-and-loan crisis in US (1990s), 30 Savings cues, experiment with, 137 Scared Straight social program, 101 Scholes, Myron, 31, 123–124 Science, Technology, and Industry Scoreboard of OECD, 147 Securities and Exchange Commission (SEC), 54, 56, 57, 58, 64 Securities markets, 14 Securitization, xi, 20, 37–38, 117–122, 183–184, 196, 236 Seedrs, 160–161 Sellaband, 159 Shared equity, 80–84 Shared-equity mortgage, 84 Shepard, Chris, xii–xiii Shiller, Robert, xv–xvi, 242 Shleifer, Andrei, 42, 44 Short termism, 58 SIBs.


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The Moral Landscape: How Science Can Determine Human Values by Sam Harris

Albert Einstein, banking crisis, Bayesian statistics, cognitive bias, end world poverty, endowment effect, energy security, experimental subject, framing effect, hindsight bias, impulse control, John Nash: game theory, longitudinal study, loss aversion, meta analysis, meta-analysis, out of africa, pattern recognition, placebo effect, Ponzi scheme, Richard Feynman, risk tolerance, scientific worldview, stem cell, Stephen Hawking, Steven Pinker, the scientific method, theory of mind, ultimatum game, World Values Survey

It is also an important impediment to conflict resolution through negotiation: for if each party values his opponent’s concessions as gains and his own as losses, each is bound to perceive his sacrifice as being greater.34 Loss aversion has been studied with functional magnetic resonance imaging (fMRI). If this bias were the result of negative feelings associated with potential loss, we would expect brain regions known to govern negative emotion to be involved. However, researchers have not found increased activity in any areas of the brain as losses increase. Instead, those regions that represent gains show decreasing activity as the size of the potential losses increases. In fact, these brain structures themselves exhibit a pattern of “neural loss aversion”: their activity decreases at a steeper rate in the face of potential losses than they increase for potential gains.35 There are clearly cases in which such biases seem to produce moral illusions—where a person’s view of right and wrong will depend on whether an outcome is described in terms of gains or losses.

The lone ranger of quantum mechanics. New York Times. Thompson, J. J. (1976). Letting die, and the trolley problem. The Monist, 59 (2), 204–217. Tiihonen, J., Rossi, R., Laakso, M. P., Hodgins, S., Testa, C., Perez, J., et al. (2008). Brain anatomy of persistent violent offenders: More rather than less. Psychiatry Res, 163 (3), 201–212. Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315 (5811), 515–518. Tomasello, M. (2007, January 13). For human eyes only. New York Times. Tomlin, D., Kayali, M. A., King-Casas, B., Anen, C., Camerer, C. F., Quartz, S. R., et al. (2006). Agent-specific responses in the cingulate cortex during economic exchanges. Science, 312 (5776), 1047–1050. Tononi, G., & Edelman, G. M. (1998). Consciousness and complexity.

., 228n61 beehive approach to morality, 89 belief: adoption of, for feeling better, 137–39 bias and, 122–26, 137, 226n36 brain science on, 11, 14, 116–22, 197n22 definitions of, 117 different categories of, 139–40 ethical beliefs, 14 extraneous information and/or context as influence on, 140–42 factual beliefs, 14 freedom of, 136–44 inseparability of reasoning and emotion, 126–31 internet’s influence on, 123 as intrinsically epistemic, 138 knowledge as, 115, 196–97n22 lie detection and, 133–36 meaning of, 115–18, 219–20n15 memory and, 116 mental properties of, 136–40 motivation for, 126 reasoning and, 122, 131–33 religious belief, 137–38, 148–54 science and, 144 wrong beliefs, 21 Benedict, Pope, 200n14 Benedict, Ruth, 20, 60–62 Bentham, Jeremy, 207n12 bias: adaptive fitness versus, 226–27n38 belief and, 122–26, 137, 226n36 decisional conflict, 231n75 definition of, 132 endowment effect and, 75 factors causing, 226n36 internet’s influence on, 123 knowledge and, 123–24 of liberals, 125–26 loss aversion, 75–77, 209n35 medical decisions and, 143, 231n75 of parents, 73 of political conservatives, 124–25 in reasoning, 132, 142–43 of science, 47 sins of commission versus sins of omission, 77 truth bias, 120, 223n26 unconscious and, 122–23 Bible, 3, 34, 38, 150, 166, 236–37n82 Biblical Creationism, 34, 37, 151, 202n19 Bin Laden, Osama, 5 Bingham, Roger, 5–6, 23 BioLogos Foundation, 169 birth control.


pages: 416 words: 118,592

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing by Burton G. Malkiel

accounting loophole / creative accounting, Albert Einstein, asset allocation, asset-backed security, backtesting, beat the dealer, Bernie Madoff, BRICs, butter production in bangladesh, buy and hold, capital asset pricing model, compound rate of return, correlation coefficient, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, dogs of the Dow, Edward Thorp, Elliott wave, Eugene Fama: efficient market hypothesis, experimental subject, feminist movement, financial innovation, fixed income, framing effect, hindsight bias, Home mortgage interest deduction, index fund, invisible hand, Isaac Newton, Long Term Capital Management, loss aversion, margin call, market bubble, money market fund, mortgage tax deduction, new economy, Own Your Own Home, passive investing, Paul Samuelson, pets.com, Ponzi scheme, price stability, profit maximization, publish or perish, purchasing power parity, RAND corporation, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, short selling, Silicon Valley, South Sea Bubble, stocks for the long run, survivorship bias, The Myth of the Rational Market, the rule of 72, The Wisdom of Crowds, transaction costs, Vanguard fund, zero-coupon bond

Note that the expected value of the gain from such a gamble is $75, so this is a very favorable bet. Expected value ½($250) + ½ (–$100) $75. Kahneman and Tversky concluded that losses were 2½ times as undesirable as equivalent gains were desirable. In other words, a dollar loss is 2½ times as painful as a dollar gain is pleasurable. People exhibit extreme loss aversion, even though a change of $100 of wealth would hardly be noticed for most people with substantial assets. We’ll see later how loss aversion leads many investors to make costly mistakes. Interestingly, however, when individuals faced a situation where sure losses were involved, the psychologists found that they were overwhelmingly likely to take the gamble. Consider the following two alternatives: 1. A sure loss of $750. 2. A 75% chance to lose $1,000 and a 25% chance to lose nothing.

During periods of falling prices, however, sales volumes decline and individuals let their homes sit on the market for long periods of time with asking prices well above market prices. Extreme loss aversion helps explain sellers’ reluctance to sell their properties at a loss. BEHAVIORAL FINANCE AND SAVINGS Behavioral-finance theory also helps explain why many people refuse to join a 401(k) savings plan at work, even when their company matches their contributions. If one asks an employee who has become used to a particular level of take-home pay to increase his allocation to a retirement plan by one dollar, he will view the resulting deduction (even though it is less than a dollar because contributions to retirement plans are deductible from taxable income up to certain generous amounts) as a loss of current spending availability. Individuals weigh these losses much more heavily than gains. When this loss aversion is coupled with the difficulty of exhibiting self-control, the ease of procrastinating, and the ease of making no changes (status quo bias), it becomes, as psychologists teach us, perfectly understandable why people tend to save too little.

REAPING REWARD BY INCREASING RISK Beta and Systematic Risk The Capital-Asset Pricing Model (CAPM) Let’s Look at the Record An Appraisal of the Evidence The Quant Quest for Better Measures of Risk: Arbitrage Pricing Theory The Fama-French Three-Factor Model A Summing Up 10. BEHAVIORAL FINANCE The Irrational Behavior of Individual Investors Overconfidence Biased Judgments Herding Loss Aversion Pride and Regret Behavioral Finance and Savings The Limits to Arbitrage What Are the Lessons for Investors from Behavioral Finance? 1. Avoid Herd Behavior 2. Avoid Overtrading 3. If You Do Trade: Sell Losers, Not Winners 4. Other Stupid Investor Tricks Does Behavioral Finance Teach Ways to Beat the Market? 11. POTSHOTS AT THE EFFICIENT-MARKET THEORY AND WHY THEY MISS What Do We Mean by Saying Markets Are Efficient?


pages: 207 words: 57,959

Little Bets: How Breakthrough Ideas Emerge From Small Discoveries by Peter Sims

Amazon Web Services, Black Swan, Clayton Christensen, complexity theory, David Heinemeier Hansson, deliberate practice, discovery of penicillin, endowment effect, fear of failure, Frank Gehry, Guggenheim Bilbao, Jeff Bezos, knowledge economy, lateral thinking, Lean Startup, longitudinal study, loss aversion, meta analysis, meta-analysis, PageRank, Richard Florida, Richard Thaler, Ruby on Rails, Silicon Valley, statistical model, Steve Ballmer, Steve Jobs, Steve Wozniak, theory of mind, Toyota Production System, urban planning, Wall-E

Steve Jobs calligraphy example taken from his 2005 Stanford Commencement speech. James Chanos reference: Interview with Chanos. Jerry Seinfeld: Drawn from The Comedian (DVD), Directed by Christian Charles, with Jerry Seinfeld (2002). John Legend and Kevin Brereton: Interviews with Legend and Brereton. Status quo bias and loss aversion: Origin of status quo bias terminology and research: “Status Quo Bias in Decision Making,” by William Samuelson and Richard Zeckhauser, Journal of Risk and Uncertainty, vol. 1, 1988, 7–59. Addition of loss aversion and endowment effect: “The Endowment Effect, Loss Aversion, and Status Quo Bias,” by Daniel Kahneman, Jack L. Knetsch, Richard H. Thaler, Journal of Economic Perspectives, vol. 5, 193–206. “Timid Choices and Bold Forecasts,” by Daniel Kahneman and Dan Lavallo, Management Science, 39, 17–31. Chet Pipkin: Interview with Pipkin.

The exemplars Dyer and Gregerson highlighted were also voracious questioners, regularly seeking to challenge the status quo by asking “what if?” “why?” and “why not?” The authors wrote that the innovators steer “entirely clear” of what’s called the status quo bias. This research demonstrates that people do not like to change unless there is a compelling reason to do so, such as an attractive incentive. Related research shows that people exhibit strong “loss aversion,” in that they are twice as likely to seek to avoid losses as they are to acquire gains. The researchers who discovered this phenomenon found that people wanted to be able to gain at least forty dollars on a coin toss before they risked losing twenty dollars, a roughly two to one (fear-of-loss to pleasure-of-gain) ratio. Dyer and Gregersen noted, for example, the idea for Dell Computer initially sprang from Michael Dell, founder and CEO, asking why a computer should cost five times as much as its parts.

., 99, 101 Lead users, 133–40 Legend, John, 109, 115, 134 Lehrer, Jonah, 66 Leibovitz, Annie, 126 Letterman, David, 3 Liker, Jeffrey, The Toyota Way, 167 Limb, Charles, 65–67 Lincoln Center, New York, 79, 80 Listening, 97–116 Little bets, 1, 8, 154 active users, 133–40 big bets vs., 19–33 failing quickly to learn fast, 51–64 growth mind-set and, 35–49 learning a lot from a little, 131–40 openness to experience and, 117–30 play and, 65–76 prototyping and, 52–64 questions and, 97–116 smallifying problems and, 77–95 small wins and, 141–52 London, 109 Los Angeles, 78–83, 111, 112, 161 Los Angeles Philharmonic, 80, 83 Loss aversion, 110 Lucas, George, 30, 31, 143 Lucasfilm, 30 Luck, 121–24, 129 making your own, 124–29 network of, 124 Luxo Jr. (film), 143–44 MacFarland, Sean, 94–95 Macintosh, 108 Maeda, John, The Laws of Simplicity, 170 Malaria, 9 Management by walking around, 120–21 Manufacturing, 15 Marketing, 4–5, 6, 20, 21 Market research, 21–22, 111, 135 Martin, Roger, 63 The Design of Business, 172 Mayer, Marissa, 78 McCain, John, 125 McEnroe, John, 37, 38 McGrath (Rita Gunther) and MacMillan (Ian C.), Discovery-Driven Growth, 174 McMaster, H.


pages: 229 words: 61,482

The Gig Economy: The Complete Guide to Getting Better Work, Taking More Time Off, and Financing the Life You Want by Diane Mulcahy

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, basic income, Clayton Christensen, cognitive bias, collective bargaining, creative destruction, David Brooks, deliberate practice, diversification, diversified portfolio, fear of failure, financial independence, future of work, gig economy, helicopter parent, Home mortgage interest deduction, housing crisis, job satisfaction, Kickstarter, loss aversion, low skilled workers, Lyft, mass immigration, mental accounting, minimum wage unemployment, mortgage tax deduction, negative equity, passive income, Paul Graham, remote working, risk tolerance, Robert Shiller, Robert Shiller, Silicon Valley, Snapchat, TaskRabbit, Uber and Lyft, uber lyft, universal basic income, wage slave, Y Combinator, Zipcar

As Beth said, “The worst-case scenario is that I’m homeless somewhere with no money.” Why does fear have such a stranglehold on our lives? Why does it hold us back and keep us small even when the opportunity for something bigger and better lies right in front of us? One reason is that we let our fears fester and grow, unchallenged, in our heads. We don’t examine them in the cold light of day and see what they’re made of. Another reason is that we are loss averse. We feel the pain of loss much more than the pleasure of gain. We pay greater attention to potential losses than gains, and we’re inclined to avoid possible setbacks more than we are to seek potential wins. Facing Fear It’s easiest to deconstruct our fears and identify our risks if we see them in front of us. Let’s return to the example of Beth and evaluate her fears of being homeless with no money.

But if she researched that assumption, she might find that (for example) 90 percent of restaurants fail after a year and 80 percent of retail establishments go out of business but only 30 percent of professional services firms fail in the first year. Just having better information can help Beth overcome some of her fear. We’re not very good at assessing our fears and risks accurately. Our assessment of risk is distorted by a series of cognitive biases like overconfidence (which researchers implicate in gambling), anchoring (we assess gains and losses depending on how they are framed), and loss aversion (we hate losses more than we love equivalent gains). These cognitive biases can cause us to either overestimate or underestimate risk and make (sometimes big) decisions based on our inaccurate perception. We tend to hold unfounded fears about events and outcomes that are unlikely yet seem oblivious to the very real risks in our everyday lives. Driving is an excellent example of our inability to accurately assess risk.

We’re much more likely to waste our time than our money because we have a higher level of pain over losing money than over “losing” or wasting time. For example, tossing a fifty-dollar bill into the fireplace to burn causes us pain over the loss of the fifty dollars, but if we waste an hour in front of that same fire watching cat videos on Facebook, we don’t feel the same level of pain. It doesn’t make sense that we feel less loss aversion to wasting time than money because, unlike money, our time here on Earth is so limited. Except for a few tweaks around the edges, like wearing our seatbelts, not smoking, and taking other life-prolonging steps, there’s not much we can do to create more of it. We can’t bank our time and save it for use later like we can our money. The fixed nature of time would seem to require us to treat it even more carefully and with even more intention than money, but often we don’t.


pages: 306 words: 82,765

Skin in the Game: Hidden Asymmetries in Daily Life by Nassim Nicholas Taleb

availability heuristic, Benoit Mandelbrot, Bernie Madoff, Black Swan, Brownian motion, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, cellular automata, Claude Shannon: information theory, cognitive dissonance, complexity theory, David Graeber, disintermediation, Donald Trump, Edward Thorp, equity premium, financial independence, information asymmetry, invisible hand, knowledge economy, loss aversion, mandelbrot fractal, mental accounting, microbiome, moral hazard, Murray Gell-Mann, offshore financial centre, p-value, Paul Samuelson, Ponzi scheme, price mechanism, principal–agent problem, Ralph Nader, random walk, rent-seeking, Richard Feynman, Richard Thaler, Ronald Coase, Ronald Reagan, Rory Sutherland, Silicon Valley, Steven Pinker, stochastic process, survivorship bias, The Nature of the Firm, transaction costs, urban planning, Yogi Berra

Cognitive dissonance (a psychological theory by Leon Festinger about sour grapes, by which people, in order to avoid inconsistent beliefs, rationalize that, say, the grapes they can’t reach got to be sour). It is seen first in Aesop, of course, repackaged by La Fontaine. But its roots look even more ancient, with the Assyrian Ahiqar of Nineveh. Loss aversion (a psychological theory by which a loss is more painful than a gain is pleasant): in Livy’s Annals (XXX, 21) Men feel the good less intensely than the bad.fn6 Nearly all the letters of Seneca have some element of loss aversion. Negative advice (via negativa): We know the wrong better than what’s right; recall the superiority of the Silver over the Golden Rule. The good is not as good as the absence of bad,fn7 Ennius, repeated by Cicero. Skin in the game (literally): We start with the Yiddish proverb: You can’t chew with somebody else’s teeth.

This can be quantified by recognizing that the probability of ruin approaches 1 as the number of exposures to individually small risks, say one in ten thousand, increases. The flaw in psychology papers is to believe that the subject doesn’t take any other tail risks anywhere outside the experiment and, crucially, will never again take any risk at all. The idea in social science of “loss aversion” has not been thought through properly—it is not measurable the way it has been measured (if it is at all measurable). Say you ask a subject how much he would pay to insure a 1 percent probability of losing $100. You are trying to figure out how much he is “overpaying” for “risk aversion” or something even more foolish, “loss aversion.” But you cannot possibly ignore all the other financial risks he is taking: if he has a car parked outside that can be scratched, if he has a financial portfolio that can lose money, if he has a bakery that may risk a fine, if he has a child in college who may cost unexpectedly more, if he can be laid off, if he may be unexpectedly ill in the future.

Languages The One-Way Street of Religions Decentralize, Again Imposing Virtue on Others Stability of the Minority Rule, a Probabilistic Argument Popper-Goedel’s Paradox Irreverence of Markets and Science Unus sed Leo: Only One but a Lion Summary and Next Appendix to Book 3: A Few More Counterintuitive Things About the Collective Zero-Intelligence Markets BOOK 4: WOLVES AMONG DOGS Chapter 3. How to Legally Own Another Person To Own a Pilot From the Company Man to the Companies Person Coase’s Theory of the Firm Complexity A Curious Form of Slave Ownership Freedom is Never Free Wolves Among the Dogs Loss Aversion Waiting for Constantinople Do Not Rock Bureaucristan Next Chapter 4. The Skin of Others in Your Game A Mortgage and Two Cats Finding Hidden Vulnerabilities How to Put Skin in the Game of Suicide Bombers Next BOOK 5: BEING ALIVE MEANS TAKING CERTAIN RISKS Chapter 5. Life in the Simulation Machine Jesus Was a Risk Taker Pascal’s Wager The Matrix The Donald Next Chapter 6. The Intellectual Yet Idiot Where to Find a Coconut Science and Scientism Intellectual Yet Philistine Never Gotten Drunk with Russians To Conclude Postscript Chapter 7.


Investment: A History by Norton Reamer, Jesse Downing

activist fund / activist shareholder / activist investor, Albert Einstein, algorithmic trading, asset allocation, backtesting, banking crisis, Berlin Wall, Bernie Madoff, break the buck, Brownian motion, business cycle, buttonwood tree, buy and hold, California gold rush, capital asset pricing model, Carmen Reinhart, carried interest, colonial rule, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, debt deflation, discounted cash flows, diversified portfolio, dogs of the Dow, equity premium, estate planning, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, family office, Fellow of the Royal Society, financial innovation, fixed income, Gordon Gekko, Henri Poincaré, high net worth, index fund, information asymmetry, interest rate swap, invention of the telegraph, James Hargreaves, James Watt: steam engine, joint-stock company, Kenneth Rogoff, labor-force participation, land tenure, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, margin call, means of production, Menlo Park, merger arbitrage, money market fund, moral hazard, mortgage debt, Myron Scholes, negative equity, Network effects, new economy, Nick Leeson, Own Your Own Home, Paul Samuelson, pension reform, Ponzi scheme, price mechanism, principal–agent problem, profit maximization, quantitative easing, RAND corporation, random walk, Renaissance Technologies, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, Sand Hill Road, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, spinning jenny, statistical arbitrage, survivorship bias, technology bubble, The Wealth of Nations by Adam Smith, time value of money, too big to fail, transaction costs, underbanked, Vanguard fund, working poor, yield curve

One of the most cited and well-regarded explanations, put forth by Shlomo Benartzi and Richard Thaler in 1995, is “myopic loss aversion,” a notion that borrows heavily from the concepts developed in prospect theory, including the fact that individuals tend to exhibit loss aversion and that they care about changes in wealth more keenly than about absolute levels of wealth. Investors who frequently look at the value of their equity portfolio—say, on a daily or weekly basis when the market behaves randomly over these short time frames, moving up and down—will thus experience more disutility on average, given that they derive greater pain from losses than pleasure from the same magnitude of gains. Over long evaluation periods, The Emergence of Investment Theory 253 however, where market movements have a general upward trend, this feeling of loss aversion is reduced because equities tend to appreciate over time, so it is more palatable to hold on to equities.

Over long evaluation periods, The Emergence of Investment Theory 253 however, where market movements have a general upward trend, this feeling of loss aversion is reduced because equities tend to appreciate over time, so it is more palatable to hold on to equities. The size of the equity premium, then, is really due to loss aversion experienced by investors whose frequency of evaluations is too great; if investors looked at their equities portfolios over longer time frames, they would demand lower premiums and this puzzle would be resolved.49 Other explanations that have been offered by behavioral economists focus on earnings uncertainty and how that influences investors’ willingness to bear risk, and yet others develop a dynamic loss aversion model where investors react differently to stocks that fall after a run-up compared to those that fall directly after purchase. Another place where this behavioral lens has been applied to financial markets beyond the equity premium puzzle is momentum.

Their pioneering paper noted many 252 Investment: A History of the known behaviors that represent aberrations from expected utility theory, including lottery problems (in which individuals tend to elect a lump-sum payment up front even if that is smaller than the expected value of receiving a larger amount or zero when a coin flip is involved) and probabilistic insurance (in which individuals have a more disproportionate dislike for a form of insurance that would cover losses based on a coin flip more than the math suggests they should). Prospect theory contends that individuals’ choices are more centered on changes in utility or wealth rather than end values; it also suggests that most people exhibit loss aversion in which losses cause more harm to one’s welfare than the benefit from happiness one receives from gaining the same amount of reward.46 This theory may seem intellectually interesting, but how does it relate precisely to finance and investing? Since Kahneman and Tversky’s seminal paper, subsequent work has made many connections to markets, one of which is the “equity premium puzzle.” The equity premium puzzle was described first in a 1985 paper by Rajnish Mehra and Edward Prescott.47 The central “puzzle” is that while investors should be compensated more for holding riskier equities than holding the risk-free instrument (Treasury bills), the amount by which they are compensated seems extremely excessive historically.


pages: 93 words: 24,584

Walk Away by Douglas E. French

business cycle, Elliott wave, forensic accounting, full employment, Home mortgage interest deduction, loss aversion, McMansion, mental accounting, mortgage debt, mortgage tax deduction, negative equity, New Journalism, Own Your Own Home, Richard Thaler, Robert Shiller, Robert Shiller, the market place, transaction costs, unbiased observer, wealth creators

Most all attempt to negotiate a modification with their lender and are turned away at the door because they are current on their payments or if they are invited to pursue a modification, the “process turns out, however, to be immensely frustrating and ultimately unsuccessful for many homeowners.” Research has shown that investment decisions are driven by biases locked in the human brain and humans are especially loss-averse and tend to rationalize bad investment decisions. David Genesove and Christopher Mayer write in a chapter entitled “Loss-Aversion and Seller Behavior: Evidence from the Housing Market” from Advances In Behavioral Economics, “housing professionals are not surprised that many sellers are reluctant to realize a loss on their house.” These authors found that during the boom and bust in the Boston downtown real estate market of 1990–97, sellers subject to losses set higher asking prices of 25–35% of the difference between the expected selling price of a property and their original purchase price.

“One especially successful broker even noted that she tried to avoid taking on clients who were facing ‘too large’ a potential loss on their property because such clients often had unrealistic target selling prices,” write Genesove and Mayer. And the cold, hard realities of the market are slow to change sellers’ minds according to Genesove and Mayer. According to their data, lower prices and increased time on the market do not significantly influence loss-aversion. Dražen Prelec and George Lowenstein believe that people do an accounting in their heads that affects their behavior. The linkages tying together specific acts of consumption with specific payments “generates pleasure or pain depending on whether the accounts are in the red or in the black.” In an article entitled “The Red and the Black: Mental Accounting of Savings and Debt” which appeared as a chapter in Exotic Preferences: Behavioral Economics and Human Motivation, the authors’ modeling predicts that most people are debt averse and show “that people generally like sequences of events that improve over time and dislike sequences that deteriorate.”


Bulletproof Problem Solving by Charles Conn, Robert McLean

active transport: walking or cycling, Airbnb, Amazon Mechanical Turk, asset allocation, availability heuristic, Bayesian statistics, Black Swan, blockchain, business process, call centre, carbon footprint, cloud computing, correlation does not imply causation, Credit Default Swap, crowdsourcing, David Brooks, Donald Trump, Elon Musk, endowment effect, future of work, Hyperloop, Innovator's Dilemma, inventory management, iterative process, loss aversion, meta analysis, meta-analysis, Nate Silver, nudge unit, Occam's razor, pattern recognition, pets.com, prediction markets, principal–agent problem, RAND corporation, randomized controlled trial, risk tolerance, Silicon Valley, smart contracts, stem cell, the rule of 72, the scientific method, The Signal and the Noise by Nate Silver, time value of money, transfer pricing, Vilfredo Pareto, walkable city, WikiLeaks

In conversations with our former colleague and Kahneman collaborator, Professor Dan Lovallo, he suggests that the most important to address are confirmation bias, anchoring bias, and loss aversion.4 We will add in availability bias and overoptimism as additional issues to address in your team processes. Indeed, as Exhibit 4.6 shows, many of the other biases described in the literature are forms of these five underlying issues. EXHIBIT 4.6 Confirmation bias is falling in love with your one‐day answer. It is the failure to seriously consider the antithesis to your thesis, ignoring dissenting views—essentially picking low hanging mental fruit. Anchoring bias is the mistaken mental attachment to an initial data range or data pattern that colors your subsequent understanding of the problem. Loss aversion, and its relatives, the sunk cost fallacy, book loss fear, and the endowment effect, are a failure to ignore costs already spent (sunk) or any asymmetric valuing of losses and gains.

This has been underscored by recent work on forecasting.8  Executives rank reducing decision bias as their number one aspiration for improving performance.9  For example, a food products company Rob was serving was trying to exit a loss‐making business. They could have drawn a line under the losses if they took an offer to exit when they had lost $125 million. But they would only accept offers to recover accounting book value (a measure of the original cost). Their loss aversion, a form of sunk‐cost bias, meant that several years later they finally exited with losses in excess of $500 million! Groupthink amongst a team of managers with similar backgrounds and traditional hierarchy made it hard for them see the real alternatives clearly; this is a common problem in business. Incomplete analytic tool set. Some issues can be resolved with back of the envelope calculations.

., 143 Kirkland, Jane, 199 Knee arthroscopy, election (question), 125e Knezevic, Bogdan, 143 Knock‐out analysis, 92–93 Known unknowns, 198 Koller, Tim, 214 Komm, Asmus, xvii L Labor market, 205e Leadership, team structure (relationship), 97–98 Lean project plans, 93, 94e Learning algorithms, 159 Leskovec, Jure, 143 Levels of uncertainty, 197–198 Levers impact, 65e profit lever tree, 23e strategies, 66 Lewis, Michael, 201 LIDAR, usage, 226 Linear regression, 159–160 Local school levy support (case study), 25–28 problem, 26 sample, 28e Logic trees, 14e, 127, 180 deductive logic trees, 58–59, 67 disaggregation, map basis, 232 inductive logic trees, 67–68 reduction, 71–73 sketching, 255 types, 51–53, 52e usage, 199–202 Logic, usage, 7 London air quality, case study, 141, 142e Longevity runway estimation, 209 sketching, 210–211 Long term. See Near term/long term Long‐term capital investment, 196 Long‐term investments case study, 213–219 growth options, 203 Long‐term strategy portfolio, management (case study), 226–233 Look backs, 218 Loss aversion, 101 Lovallo, Dan, 101, 107, 119, 123 M Machine learning (ML), 136, 140, 164 algorithms, usage, 226 case study, 141 function, 161 neural networks, impact, 163–164 solutions, 159–164 usage, 165 Mackenzie, Dana, 151 Madansky, Albert, 199 Magnitudes order of magnitude analysis, 114, 137 understanding, 112 Managerial skills, evolution, xv Manual tasks, xvi Manufacturers, shipments (breakup), 62 MAP.


pages: 543 words: 153,550

Model Thinker: What You Need to Know to Make Data Work for You by Scott E. Page

"Robert Solow", Airbnb, Albert Einstein, Alfred Russel Wallace, algorithmic trading, Alvin Roth, assortative mating, Bernie Madoff, bitcoin, Black Swan, blockchain, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Checklist Manifesto, computer age, corporate governance, correlation does not imply causation, cuban missile crisis, deliberate practice, discrete time, distributed ledger, en.wikipedia.org, Estimating the Reproducibility of Psychological Science, Everything should be made as simple as possible, experimental economics, first-price auction, Flash crash, Geoffrey West, Santa Fe Institute, germ theory of disease, Gini coefficient, High speed trading, impulse control, income inequality, Isaac Newton, John von Neumann, Kenneth Rogoff, knowledge economy, knowledge worker, Long Term Capital Management, loss aversion, low skilled workers, Mark Zuckerberg, market design, meta analysis, meta-analysis, money market fund, Nash equilibrium, natural language processing, Network effects, p-value, Pareto efficiency, pattern recognition, Paul Erdős, Paul Samuelson, phenotype, pre–internet, prisoner's dilemma, race to the bottom, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, school choice, sealed-bid auction, second-price auction, selection bias, six sigma, social graph, spectrum auction, statistical model, Stephen Hawking, Supply of New York City Cabdrivers, The Bell Curve by Richard Herrnstein and Charles Murray, The Great Moderation, The Rise and Fall of American Growth, the rule of 72, the scientific method, The Spirit Level, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, urban sprawl, value at risk, web application, winner-take-all economy, zero-sum game

More realistic models may require more sophisticated mathematics.13 None of these concerns is so persuasive to suggest abandoning models with psychologically realistic behaviors, but collectively they imply that we proceed with caution and emphasize well-documented behavioral regularities. Two deviations that have been replicated many times are loss aversion and hyperbolic discounting. Loss aversion states that people are risk-averse over gains and risk-loving over losses. Kahneman and Tversky refer to this general theory of behavior as prospect theory.14 Loss aversion does not at first appear irrational, but it implies that people choose different actions when an identical scenario is presented as a potential loss as opposed to a potential gain. For example, people prefer winning $400 for certain rather than entering a lottery with an even chance of winning $1,000.

The rational actor will be less successful at predicting human behavior than as a tool for communicating, evaluating actions, and designing policies. We then show how we can add psychological biases and altruistic preferences onto the standard rational-actor model. The choice of whether to include a bias or a concern for others rests again on what we are studying. Some human biases such as loss aversion and presentist bias—caring more about delays today than in the future—may be necessary to include in some instances. For example, those assumptions may be important for models of retirement savings or riots. The assumptions may be less important for models of driving behavior or disease transmission. In the fourth section, we describe rule-based behavior. This category of models has the advantage of being both flexible—any behavior we can write down as a rule is fair game—and tractable.

Psychological Biases The rational-actor model has been challenged by psychologists, economists, and neuroscientists, who note that it does not match up with how humans behave. Empirical findings from laboratory and natural experiments show that people suffer a variety of biases, including a status quo bias. We ignore base rates when making probability calculations, we attach too much significance to sure things, and we are loss-averse. As researchers begin to link behavior and beliefs to processes within the brain, evidence of hardwired biases becomes more compelling. For example, neuroeconomics uses brain imaging studies to study economically relevant behaviors such as attitudes toward risk, levels of confidence, and responses to information.9 Kahneman argues that what we know so far supports making a distinction between two types of thinking: quick, intuitive rules (fast thinking) and deliberate contemplation (slow thinking).


pages: 415 words: 125,089

Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein

"Robert Solow", Albert Einstein, Alvin Roth, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Big bang: deregulation of the City of London, Bretton Woods, business cycle, buttonwood tree, buy and hold, capital asset pricing model, cognitive dissonance, computerized trading, Daniel Kahneman / Amos Tversky, diversified portfolio, double entry bookkeeping, Edmond Halley, Edward Lloyd's coffeehouse, endowment effect, experimental economics, fear of failure, Fellow of the Royal Society, Fermat's Last Theorem, financial deregulation, financial innovation, full employment, index fund, invention of movable type, Isaac Newton, John Nash: game theory, John von Neumann, Kenneth Arrow, linear programming, loss aversion, Louis Bachelier, mental accounting, moral hazard, Myron Scholes, Nash equilibrium, Norman Macrae, Paul Samuelson, Philip Mirowski, probability theory / Blaise Pascal / Pierre de Fermat, random walk, Richard Thaler, Robert Shiller, Robert Shiller, spectrum auction, statistical model, stocks for the long run, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, Thomas Bayes, trade route, transaction costs, tulip mania, Vanguard fund, zero-sum game

This behavior, although understandable, is inconsistent with the assumptions of rational behavior. The answer to a question should be the same regardless of the setting in which it is posed. Kahneman and Tversky interpret the evidence produced by these experiments as a demonstration that people are not risk-averse: they are perfectly willing to choose a gamble when they consider it appropriate. But if they are not risk-averse, what are they? "The major driving force is loss aversion," writes Tversky (italics added). "It is not so much that people hate uncertainty-but rather, they hate losing."6 Losses will always loom larger than gains. Indeed, losses that go unresolved-such as the loss of a child or a large insurance claim that never gets settled-are likely to provoke intense, irrational, and abiding risk-aversion.? Tversky offers an interesting speculation on this curious behavior: Probably the most significant and pervasive characteristic of the human pleasure machine is that people are much more sensitive to negative than to positive stimuli....

When the question was put in terms of life expectancy, only about 20% favored radiation. One of the most familiar manifestations of the failure of invariance is in the old Wall Street saw, "You never get poor by taking a profit." It would follow that cutting your losses is also a good idea, but investors hate to take losses, because, tax considerations aside, a loss taken is an acknowledgment of error. Loss-aversion combined with ego leads investors to gamble by clinging to their mistakes in the fond hope that some day the market will vindicate their judgment and make them whole. Von Neumann would not approve. The failure of invariance frequently takes the form of what is known as "mental accounting," a process in which we separate the components of the total picture. In so doing we fail to recognize that a decision affecting each component will have an effect on the shape of the whole.

Worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally."4 Prospect Theory confirms Keynes's conclusion by predicting which decision you will make. First, the absolute performance of the stock you select is relatively unimportant. The start-up company's performance as compared with Johnson & Johnson's performance taken as a reference point is what matters. Second, loss aversion and anxiety will make the joy of winning on the start-up company less than the pain if you lose on it. Johnson & Johnson is an acceptable "long-term" holding even if it often underperforms. The stocks of good companies are not necessarily good stocks, but you can make life easier by agreeing with your clients that they are. So you advise your client to buy Johnson & Johnson. I am not making up a story out of whole cloth.


pages: 241 words: 75,516

The Paradox of Choice: Why More Is Less by Barry Schwartz

accounting loophole / creative accounting, attribution theory, Atul Gawande, availability heuristic, Cass Sunstein, Daniel Kahneman / Amos Tversky, endowment effect, framing effect, hedonic treadmill, income per capita, job satisfaction, loss aversion, medical residency, mental accounting, Own Your Own Home, Pareto efficiency, positional goods, price anchoring, psychological pricing, RAND corporation, Richard Thaler, science of happiness, The Wealth of Nations by Adam Smith

There is another feature of the graph worth noting: the loss portion of the graph is much steeper than the gain portion. Losing $100 produces a feeling of negativity that is more intense than the feelings of elation produced by a gain. Some studies have estimated that losses have more than twice the psychological impact as equivalent gains. The fact is, we all hate to lose, which Kahneman and Tversky refer to as loss aversion. The last and crucial element to the graph is the location of the neutral point. This is the dividing line between what counts as a gain and what counts as a loss, and here, too, subjectivity rules. When there is a difference in price between cash and credit at the gas station, is it a discount for cash or a surcharge for credit? If you think it’s a discount for cash, then you’re setting your neutral point at the credit-card price and paying cash is a gain.

You love to ride for exercise, especially in the hills outside the town in which you live. Is it worth the money? You think about it for a while and decide. Now imagine trying to decide whether to buy a mountain bike or a digital camera. Each option represents a gain (positive features it has that the other doesn’t) and a loss (positive features it doesn’t have that the other does). We saw in Chapter 3 that people tend to display loss aversion. The loss of $100 is more painful than the gain of $100 is pleasurable. What that means is that when the mountain bike and the digital camera are compared, each will suffer from the comparison. If you choose the camera, you’ll gain the quality and convenience of digital photography but lose the exercise in lovely surroundings. Because losses have a greater impact than gains, the net result will be that the camera fairs less well when compared with the mountain bike than it would have if you were evaluating it on its own.

Moxey, “Perspective in Statements of Quantity, with Implications for Consumer Psychology,” Psychological Science, 2002, 13, 130–134. Or suppose you are Many examples of phenomena discussed in this section can be found in articles collected in D. Kahneman and A. Tversky (eds.), Choices, Values, and Frames (New York: Cambridge University Press, 2000). On the endowment effect, see D. Kahneman, J. Knetsch, and R. Thaler, “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias.” On decisions to sell stock, see T. Odean, “Are Investors Reluctant to Realize Their Losses?” On sunk costs, see R. Thaler, “Mental Accounting Matters,” and R. Thaler, “Toward a Positive Theory of Consumer Choice.” On health insurance decisions, see E. Johnson, J. Hershey, J. Mezaros, and H. Kunreuther, “Framing, Probability Distortions, and Insurance Decisions.” On health plans and pension plans, see C.


pages: 288 words: 81,253

Thinking in Bets by Annie Duke

banking crisis, Bernie Madoff, Cass Sunstein, cognitive bias, cognitive dissonance, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, en.wikipedia.org, endowment effect, Estimating the Reproducibility of Psychological Science, Filter Bubble, hindsight bias, Jean Tirole, John Nash: game theory, John von Neumann, loss aversion, market design, mutually assured destruction, Nate Silver, p-value, phenotype, prediction markets, Richard Feynman, ride hailing / ride sharing, Stanford marshmallow experiment, Stephen Hawking, Steven Pinker, the scientific method, The Signal and the Noise by Nate Silver, urban planning, Walter Mischel, Yogi Berra, zero-sum game

If you applied to NASA’s astronaut program or the NBC page program, both of which have drawn thousands of applicants for a handful of positions, things will go your way a minority of the time, but you didn’t necessarily do anything wrong. Don’t fall in love or even date anybody if you want only positive results. The world is structured to give us lots of opportunities to feel bad about being wrong if we want to measure ourselves by outcomes. Don’t fall for it! Second, being wrong hurts us more than being right feels good. We know from Daniel Kahneman and Amos Tversky’s work on loss aversion, part of prospect theory (which won Kahneman the Nobel Prize in Economics in 2002), that losses in general feel about two times as bad as wins feel good. So winning $100 at blackjack feels as good to us as losing $50 feels bad to us. Because being right feels like winning and being wrong feels like losing, that means we need two favorable results for every one unfavorable result just to break even emotionally.

The Marshmallow Test: Why Self Control Is the Engine of Success. New York: Little, Brown, 2014. Mitchell, Deborah, J. Edward Russo, and Nancy Pennington. “Back to the Future: Temporal Perspective in the Explanation of Events.” Journal of Behavioral Decision Making 2, no. 1 (January 1989): 25–38. Morewedge, Carey, Lisa Shu, Daniel Gilbert, and Timothy Wilson. “Bad Riddance or Good Rubbish? Ownership and Not Loss Aversion Causes the Endowment Effect.” Journal of Experimental Social Psychology 45, no. 4 (July 2009): 947–51. Mullally, Sinead, and Eleanor Maguire. “Memory, Imagination, and Predicting the Future: A Common Brain Mechanism?” The Neuroscientist 20, no. 3 (June 2014): 220–34. Munnell, Alice, Wenliang Hou, and Anthony Webb. “NRRI Update Shows Half Still Falling Short.” Center for Retirement Research at Boston College, no. 14–20, December 2014. http://crr.bc.edu/briefs/nrri-update-shows-half-still-falling-short.

New York: Penguin, 2009. Todes, Daniel. Pavlov’s Physiology Factory: Experiment, Interpretation, Laboratory Enterprise. Baltimore: Johns Hopkins University Press, 2002. Tomlin, Damon, David Rand, Elliot Ludvig, and Jonathan Cohen. “The Evolution and Devolution of Cognitive Control: The Costs of Deliberation in a Competitive World.” Scientific Reports 5 (June 16, 2015). Tversky, Amos, and Daniel Kahneman. “Loss Aversion in Riskless Choice: A Reference-Dependent Model.” Quarterly Journal of Economics 106, no. 4 (November 1991): 1039–61. Von Neumann, John, and Oskar Morgenstern. Theory of Games and Economic Behavior. 60th anniv. ed. Princeton, NJ: Princeton University Press, 1944, 2004. Wachowski, Lana, and Wachowski, Lilly, dirs. The Matrix. Written by Lana Wachowski and Lilly Wachowski, produced by Joel Silver. 1999.


Super Thinking: The Big Book of Mental Models by Gabriel Weinberg, Lauren McCann

affirmative action, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, anti-pattern, Anton Chekhov, autonomous vehicles, bank run, barriers to entry, Bayesian statistics, Bernie Madoff, Bernie Sanders, Black Swan, Broken windows theory, business process, butterfly effect, Cal Newport, Clayton Christensen, cognitive dissonance, commoditize, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Attenborough, delayed gratification, deliberate practice, discounted cash flows, disruptive innovation, Donald Trump, Douglas Hofstadter, Edward Lorenz: Chaos theory, Edward Snowden, effective altruism, Elon Musk, en.wikipedia.org, experimental subject, fear of failure, feminist movement, Filter Bubble, framing effect, friendly fire, fundamental attribution error, Gödel, Escher, Bach, hindsight bias, housing crisis, Ignaz Semmelweis: hand washing, illegal immigration, income inequality, information asymmetry, Isaac Newton, Jeff Bezos, John Nash: game theory, lateral thinking, loss aversion, Louis Pasteur, Lyft, mail merge, Mark Zuckerberg, meta analysis, meta-analysis, Metcalfe’s law, Milgram experiment, minimum viable product, moral hazard, mutually assured destruction, Nash equilibrium, Network effects, nuclear winter, offshore financial centre, p-value, Parkinson's law, Paul Graham, peak oil, Peter Thiel, phenotype, Pierre-Simon Laplace, placebo effect, Potemkin village, prediction markets, premature optimization, price anchoring, principal–agent problem, publication bias, recommendation engine, remote working, replication crisis, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Ronald Reagan, school choice, Schrödinger's Cat, selection bias, Shai Danziger, side project, Silicon Valley, Silicon Valley startup, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, survivorship bias, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, transaction costs, uber lyft, ultimatum game, uranium enrichment, urban planning, Vilfredo Pareto, wikimedia commons

Sometimes you need to acknowledge that you are just not on the path to success. Other times you may find that what it would take to get where you originally wanted to go is just not worth the effort anymore. Unfortunately, psychologically, your mind is working hard against you here, and loss aversion is the model that explains why. You are more inclined to avoid losses, to be averse to them, than you are to want to make similar gains. Quite simply, you get more displeasure from losing fifty dollars than pleasure from gaining fifty dollars. Since you hate losing, loss aversion can cause you harm under many circumstances. You may hold losing stocks way too long, hoping they will recover back to the value they had when you bought them. You may stay in a house despite wanting to move, because you are waiting until its selling price exceeds your purchase price.

Daniel Kahneman and Amos Tversky’s work on this topic, detailed in the October 1992 issue of the Journal of Risk and Uncertainty, demonstrated that across many risky situations, such as winning or losing money based on a coin toss, people tend to want the potential payoff to be around double the potential loss before they are willing to take the gamble. That is, people want to have a fifty-fifty chance of winning one hundred dollars if they have to put fifty dollars on the line. Loss aversion can be better understood using the frame of reference model (see Chapter 1). When you already have a win on your hands, you tend to want to lock in your gains. From this frame of reference, you tend to act more conservatively and are more likely to pass up a chance at a bigger gain if it means risking your current winnings. Conversely, when you have a loss on your hands, you’d rather take a chance at breaking even than accept the sure loss.

, making it the top idea on your mind. Select between options based on opportunity cost models. Use the Pareto principle to find the 80/20 in any activity and increase your leverage at every turn. Recognize when you’ve hit diminishing returns and avoid negative returns. Use commitment and the default effect to avoid present bias, and periodic evaluations to avoid loss aversion and the sunk-cost fallacy. Look for shortcuts via existing design patterns, tools, or clever algorithms. Consider whether you can reframe the problem. 4 Becoming One with Nature BEFORE THE INDUSTRIAL REVOLUTION, most peppered moths in Manchester, England, were light-colored, using trees covered with pale bark and lichens as camouflage to avoid becoming prey for birds.


pages: 198 words: 53,264

Big Mistakes: The Best Investors and Their Worst Investments by Michael Batnick

activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, asset allocation, bitcoin, Bretton Woods, buy and hold, buy low sell high, cognitive bias, cognitive dissonance, Credit Default Swap, cryptocurrency, Daniel Kahneman / Amos Tversky, endowment effect, financial innovation, fixed income, hindsight bias, index fund, invention of the wheel, Isaac Newton, John Meriwether, Kickstarter, Long Term Capital Management, loss aversion, mega-rich, merger arbitrage, Myron Scholes, Paul Samuelson, quantitative easing, Renaissance Technologies, Richard Thaler, Robert Shiller, Robert Shiller, Snapchat, Stephen Hawking, Steve Jobs, Steve Wozniak, stocks for the long run, transcontinental railway, value at risk, Vanguard fund, Y Combinator

You go back and forth several times, but finally decide to pull the trigger on the team with the less talented quarterback but a stronger defense. After you've walked to the counter and placed your bet, you'll immediately feel much better about your decision than before you parted with your dollars. Kahneman, Knetsch, and Thaler documented this in an experiment in their 1991 paper, “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias.”1 In an advanced undergraduate economics class at Cornell, 22 students in alternating seats were given coffee mugs that sell for $6 at the bookstore. When sellers were given the option to sell, and buyers given the option to buy, the study found that the median owner was unwilling to sell for less than $5.25, while the median buyer was unwilling to pay more than $2.25.

Know when you're wrong; use price levels, dollar loss levels, or percentage loss levels. Making decisions ahead of time, especially decisions that involve admitting defeat, can help conquer one of the biggest hurdles investors face; looking in the mirror and seeing an ability that we just do not possess. Notes 1. Daniel Kahneman, Jack L. Knetsch, and Richard H. Thaler, “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias,” Journal of Economic Perspectives 5, no. 1 (Winter 1991): 193–206. 2. Robert Shiller, Irrational Exuberance (Princeton, NJ: Princeton University Press, 2000), 60. 3. David Dreman, Contrarian Investment Strategies: The Psychological Edge (New York: Free Press, 2012), 176. 4. Roger Lowenstein, Buffett (New York: Random House, 2008), 62. 5. Ibid., 93. 6. Warren Buffett, Partnership Letter, October 9, 1967. 7.

In his spare time he enjoys reading and spending time with his wife Robyn, son Koby, and dog Bianca. Index 13D registration, 90 101 Years on Wall Street (Brown), 50 Abbot Labs, 91 ABX Index, 134 Ackman, Bill, 3, 85, 88 CNN interview, 92 confidence, 88–89 persistence, 89 Adams, Evelyn, 131 Airbnb, 151 Alcoa, trading, 157 Alfond, Harold, 81 Amazon, 139–140 earnings, 7 Animal spirits, 126 “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias” (Kahneman/Knetsch/Thaler), 75 AOL/Time Warner, merger, 49 Apple earnings, certainty (example), 120 shareholder wealth, 109 Arthur Lipper, tracking, 70 Art of Contrary Thinking, The, (Neill), 67 Assets under management (AUM), reduction, 61 Automatic, Sacca investment, 149 Bacon, Louis, 103 Balanced fund, transformation, 50 Bank of England, currency defense, 103 Bank of Taiwan, investments, 40 Baruch, Bernard, 7 Batnick, Michael, 155 Behavior gap, 99 Bell, Alexander Graham, 29 Benchmarks, 77 Benjamin Graham Joint Account, 7 Berkowitz, David, 88 Berkshire Hathaway Buffett control, 76 drawdowns, 143 market cap, 79 recovery, 114 shares, decline, 142 stock, Buffett purchase, 76 value loss, 57 Bernstein, Peter, 121, 164 Bernstein, William, 37 Betting on Zero (Silvan), 94 Betty Crocker, comparison, 91 Black Monday, 102 Black‐Scholes option pricing model, 39–40 Blood money, 91 Blue Chip Stamps, 141–142 Bogle, Jack, 45, 159 firing (Wellington Management), 51 impact, 47 performance, problems, 51 Boston Security Analysis Society, Samuelson remarks, 51 Brokerage house, offer, 20 Brokers, long‐term relationship, 61 Brooks, John, 68 Brown, John Dennis, 50 Brown, Josh, 162–163 Bucket shops closure, 18 usage, 16 Buffalo Evening News (purchase), 142 Buffett, Warren, 4, 10, 73, 140 annual forecasts, 77 circle of competence, 80 comparison, 100 gross returns, 76 investment philosophy, 76–77 limited partnership, closure, 111 Oracle of Omaha, 76, 78 Pearson, contrast, 114 Bull market, margin for error, 67 Cabot, Walter, 50 Capital, usage, 17 Carr, Fred, 69 Cayne, James, 40 Charlie Munger: The Complete Investor (Griffin), 81 Charmin, comparison, 91 Chartered Financial Analyst (CFA) exam, 158–159 Chasing the Last Laugh (Zacks), 27 Chesapeake & Atlantic, 20–21 Chicago, Burlington and Quincy Railroad, 16 Chicago Herald (problems), 30 Church and Dwight, value, 91 Churchill, Winston, 91 Circle of competence (Buffett), 80 Cisco, gains, 57 Citron Research, 113–114 Clemens, Samuel.


pages: 190 words: 53,409

Success and Luck: Good Fortune and the Myth of Meritocracy by Robert H. Frank

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Amazon Mechanical Turk, American Society of Civil Engineers: Report Card, attribution theory, availability heuristic, Branko Milanovic, Capital in the Twenty-First Century by Thomas Piketty, carried interest, Daniel Kahneman / Amos Tversky, David Brooks, deliberate practice, en.wikipedia.org, endowment effect, experimental subject, framing effect, full employment, hindsight bias, If something cannot go on forever, it will stop - Herbert Stein's Law, income inequality, invisible hand, labor-force participation, lake wobegon effect, loss aversion, minimum wage unemployment, Network effects, Paul Samuelson, Report Card for America’s Infrastructure, Richard Thaler, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Rory Sutherland, selection bias, side project, sovereign wealth fund, Steve Jobs, The Wealth of Nations by Adam Smith, Tim Cook: Apple, ultimatum game, Vincenzo Peruggia: Mona Lisa, winner-take-all economy

As the seventeenth-century British philosopher John Locke wrote, “every man has a property in his own person. This nobody has any right to but himself. The labour of his body, and the work of his hands, we may say, are properly his.”8 With these words, Locke became the patron saint of tax resisters around the world. This sense of entitlement to the fruits of one’s labors may owe much to the phenomenon known as loss aversion. One of the most reliable findings in behavioral economics, loss aversion refers to the fact that people will fight much harder to avoid a loss than they would to achieve a gain of the same amount.9 Since most successful people work extremely hard for the money they earn, it feels like they own it, and that makes taxation feel like theft. But equating taxation and theft is difficult to defend. A country without taxes couldn’t field an army, after all, and would soon be overrun by a country that had one.

Chunliang Feng, Yi Luo, Ruolei Gu, Lucas S Broster, Xueyi Shen, Tengxiang Tian, Yue-Jia Luo, Frank Krueger, “The Flexible Fairness: Equality, Earned Entitlement, and Self-Interest,” PLOS ONE 8.9 (September 2013), http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0073106. 7. Mechanical Turk, https://www.mturk.com/mturk/welcome. 8. John Locke, Second Treatise on Civil Government, 1689, chap. 5, section 27, http://www.constitution.org/jl/2ndtr05.htm. 9. Daniel Kahneman, Jack L. Knetsch, and Richard H. Thaler, “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias,” Journal of Economic Perspectives 5.1 (1991): 193–206. 10. Liam Murphy and Thomas Nagel, The Myth of Ownership, New York: Oxford University Press, 2001. 11. David DeSteno, Monica Y. Bartlett, Jolie Baumann, Lisa A. Williams, and Leah Dickens, “Gratitude as Moral Sentiment: Emotion-Guided Cooperation in Economic Exchange,” Emotion 10.2 (2010): 289–93. 12. Monica Bartlett and David DeSteno, “Gratitude and Prosocial Behavior: Helping When It Costs You,” Psychological Science 17.4 (April 2006): 319–25. 13.


pages: 202 words: 58,823

Willful: How We Choose What We Do by Richard Robb

activist fund / activist shareholder / activist investor, Alvin Roth, Asian financial crisis, asset-backed security, Bernie Madoff, capital asset pricing model, cognitive bias, collapse of Lehman Brothers, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, delayed gratification, diversification, diversified portfolio, effective altruism, endowment effect, Eratosthenes, experimental subject, family office, George Akerlof, index fund, information asymmetry, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, lake wobegon effect, loss aversion, market bubble, market clearing, money market fund, Pareto efficiency, Paul Samuelson, Peter Singer: altruism, principal–agent problem, profit maximization, profit motive, Richard Thaler, Silicon Valley, sovereign wealth fund, survivorship bias, the scientific method, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, transaction costs, ultimatum game

Since the 1960s, detractors of the efficient market hypothesis have identified potential anomalies in the data that a savvy trader could exploit, and defenders have counterattacked with one of three claims: (1) The detractors looked at hundreds of possible anomalies and only published one—even if markets are perfectly unpredictable, some patterns will appear by chance, (2) There’s a flaw in the detractors’ analysis (for instance, transaction costs would chew up apparent profit or the securities were not really available at the published price), or (3) Any above-market returns can be attributed to risk, since the payoff is positively correlated with other financial assets or human capital. In return, detractors point to alleged cognitive biases, such as loss aversion, as the reason that money-making opportunities persist. Defenders then respond that some people may be biased some of the time, but even a small number of arbitrageurs can force the market to its proper level.1 I am neither in favor of the efficient market hypothesis, nor against it. I am against the way it frames the debate: it mischaracterizes markets by ignoring different ways of possessing information.

Behavioral Bias Purposeful choice’s explanation for non-maximizing action is behavioral economics. This field investigates the systematic mistakes that we could correct by recognizing our biases and mental shortcuts. It shouldn’t be hard to persuade anyone who falls for the gambler’s fallacy that the ball is no more likely to land on red in the next spin of the roulette wheel because it was red the last five times or the opposite, that black is not due to catch up. A person exhibiting loss aversion might reject a bet with a 50 percent chance of winning two dollars and a 50 percent chance of losing one dollar. She pays over the odds to avoid small losses because losing is accompanied by psychological discomfort. (This is different from risk aversion, which deals with losses on a large scale.) This bias had better be contained if you’re in the business of taking financial risks. After an event transpires, you may feel that you saw it coming, that you knew it all along, even though you didn’t.

See also mercy ambiguity effect, 24 American Work-Sports (Zarnowski), 191 Anaximander, 190 anchoring, 168 angel investors, 212–213n1 “animal spirits,” 169 Antipater of Tarsus, 134–135, 137 “anxious vigilance,” 73, 82 arbitrage, 70, 78 Aristotle, 200, 220n24 Asian financial crisis (1997–1998), 13 asset-backed securities, 93–95 asset classes, 75 astrology, 67 asymmetric information, 96, 210n2 authenticity, 32–37, 114 of challenges, 176–179 autism, 58, 59 auto safety, 139 Bank of New York Mellon, 61 Battle of Waterloo, 71, 205 Bear Stearns, 85 Becker, Gary, 33, 108–109 behavioral economics, 4, 10, 198–199 assumptions underlying, 24 insights of, 24–25 rational choice complemented by, 6 Belgium, 191 beliefs: attachment to, 51 defined, 50 evidence inconsistent with, 54, 57–58 formation of, 53, 92 persistence of, 26–28, 54 transmissibility of, 92–93, 95–96 Bentham, Jeremy, 127, 197–198 “black swans,” 62–64 blame aversion, 57, 72 brain hemispheres, 161 Brexit, 181–185 “bull markets,” 78 capital asset pricing model, 64 care altruism, 38, 104, 108–114, 115, 120, 135, 201 Casablanca (film), 120, 125 The Cask of Amontillado (Poe), 126–127 challenges, 202–203 authenticity of, 176–179 staying in the game linked to, 179–181 changes of mind, 147–164 charity, 40, 45–46, 119, 128 choice: abundance of, 172–174 intertemporal, 149–158, 166 purposeful vs. rational, 22–23 Christofferson, Johan, 83, 86, 87, 88 Cicero, 133–134 Clark, John Bates, 167 cognitive bias, 6, 23, 51, 147–148, 167, 198–199 confirmation bias, 200 experimental evidence of, 10–11, 24 for-itself behavior disguised as, 200–201 gain-loss asymmetry, 10–11 hostile attribution bias, 59 hyperbolic discounting as, 158 lawn-mowing paradox and, 33–34 obstinacy linked to, 57 omission bias, 200 rational choice disguised as, 10–11, 33–34, 199–200 salience and, 29, 147 survivor bias, 180 zero risk bias, 24 Colbert, Claudette, 7 Columbia University, 17 commitment devices, 149–151 commodities, 80, 86, 89 commuting, 26, 38–39 competitiveness, 11, 31, 41, 149, 189 complementary skills, 71–72 compound interest, 79 confirmation bias, 57, 200 conspicuous consumption, 31 consumption planning, 151–159 contrarian strategy, 78 cooperation, 104, 105 coordination, 216n15 corner solutions, 214n8 cost-benefit analysis: disregard of, in military campaigns, 117 of human life, 138–143 credit risk, 11 crime, 208 Dai-Ichi Kangyo Bank (DKB), 12–14, 15, 17, 87, 192–193 Darwin, Charles, 62–63 depression, psychological, 62 de Waal, Frans, 118 Diogenes of Seleucia, 134–135, 137 discounting of the future, 10, 162–164 hyperbolic, 158, 201 disjunction effect, 174–176 diversification, 64–65 divestment, 65–66 Dostoevsky, Fyodor, 18 drowning husband problem, 6–7, 110, 116, 123–125 effective altruism, 110–112, 126, 130, 135–136 efficient market hypothesis, 69–74, 81–82, 96 Empire State Building, 211–212n12 endowment effect, 4 endowments, of universities, 74 entrepreneurism, 27, 90, 91–92 Eratosthenes, 190 ethics, 6, 104, 106–108, 116, 125 European Union, 181–182 experiential knowledge, 59–61 expert opinion, 27–28, 53, 54, 56–57 extreme unexpected events, 61–64 fairness, 108, 179 family offices, 94 Fear and Trembling (Kierkegaard), 53–54 “felicific calculus,” 197–198 financial crisis of 2007–2009, 61, 76, 85, 93–94, 95 firemen’s muster, 191 flow, and well-being, 201–202 Foot, Philippa, 133–134, 135 for-itself behavior, 6–7, 19, 21, 27, 36, 116, 133–134, 204–205, 207–208 acting in character as, 51–53, 55–56, 94–95, 203 acting out of character as, 69, 72 analyzing, 20 authenticity and, 33–35 charity as, 39–40, 45–46 comparison and ranking lacking from, 19, 24, 181 consequences of, 55–64 constituents of, 26–31 defined, 23–24 difficulty of modeling, 204 expert opinion and, 57 extreme unexpected events and, 63–64 flow of time and, 30 free choice linked to, 169–172 in groups, 91–100 incommensurability of, 140–143 in individual investing, 77–78 in institutional investing, 76 intertemporal choice and, 168, 175, 176 job satisfaction as, 189 mercy as, 114 misclassification of, 42, 44, 200–201 out-of-character trading as, 68–69 purposeful choice commingled with, 40–43, 129, 171 rationalizations for, 194–195 in trolley problem, 137 unemployment and, 186 France, 191 Fuji Bank, 14 futures, 80–81 gain-loss asymmetry, 10–11 Galperti, Simone, 217n1 gambler’s fallacy, 199 gamifying, 177 Garber, Peter, 212n1 Germany, 191 global equity, 75 Good Samaritan (biblical figure), 103, 129–130, 206 governance, of institutional investors, 74 Great Britain, 191 Great Depression, 94 Greek antiquity, 190 guilt, 127 habituation, 201 happiness research (positive psychology), 25–26, 201–202 Hayek, Friedrich, 61, 70 hedge funds, 15–17, 65, 75, 78–79, 93, 95 herd mentality, 96 heroism, 6–7, 19–20 hindsight effect, 199 holding, of investments, 79–80 home country bias, 64–65 Homer, 149 Homo ludens, 167–168 hostile attribution bias, 59 housing market, 94 Huizinga, Johan, 167–168 human life, valuation of, 138–143 Hume, David, 62, 209n5 hyperbolic discounting, 158, 201 illiquid markets, 74, 94 index funds, 75 individual investing, 76–82 Industrial Bank of Japan, 14 information asymmetry, 96, 210n2 innovation, 190 institutional investing, 74–76, 82, 93–95, 205 intergenerational transfers, 217n1, 218n4 interlocking utility, 108 intertemporal choice, 149–159, 166 investing: personal beliefs and, 52–53 in start-ups, 27 Joseph (biblical figure), 97–99 Kahneman, Daniel, 168 Kantianism, 135–136 Keynes, John Maynard, 12, 58, 167, 169, 188–189 Kierkegaard, Søren, 30, 53, 65, 88 Knight, Frank, 145, 187 Kranton, Rachel E., 210–211n2 labor supply, 185–189 Lake Wobegon effect, 4 lawn-mowing paradox, 33–34, 206 Lehman Brothers, 61, 86, 89, 184 leisure, 14, 17, 41, 154, 187 Libet, Benjamin, 161 life, valuation of, 138–143 Life of Alexander (Plutarch), 180–181 Locher, Roger, 117, 124 long-term vs. short-term planning, 148–149 loss aversion, 70, 199 lottery: as rational choice, 199–200 Winner’s Curse, 34–36 love altruism, 104, 116, 123–125, 126, 203 lying, vs. omitting, 134 Macbeth (Shakespeare), 63 MacFarquhar, Larissa, 214n6 Madoff, Bernard, 170 malevolence, 125–127 Malthus, Thomas, 212n2 manners, in social interactions, 104, 106, 107, 116, 125 market equilibrium, 33 Markowitz, Harry, 65 Marshall, Alfred, 41, 167 Mass Flourishing (Phelps), 189–191 materialism, 5 merchant’s choice, 133–134, 137–138 mercy, 104, 114–116, 203 examples of, 116–120 inexplicable, 45–46, 120–122 uniqueness of, 119, 129 mergers and acquisitions, 192 “money pump,” 159 monks’ parable, 114, 124 Montaigne, Michel de, 114, 118 mortgage-backed securities, 93 Nagel, Thomas, 161 Napoleon I, emperor of the French, 71 neoclassical economics, 8, 10, 11, 22, 33 Nietzsche, Friedrich, 21, 43, 209n5 norms, 104, 106–108, 123 Norway, 66 Nozick, Robert, 162 observed care altruism, 108–112 Odyssey (Homer), 149–150 omission bias, 200 On the Fourfold Root of the Principle of Sufficient Reason (Schopenhauer), 209n5 “on the spot” knowledge, 61, 70, 80, 94, 205 Orico, 13 overconfidence, 57, 200 “overearning,” 44–45 The Palm Beach Story (film), 7 The Paradox of Choice (Schwartz), 172 parenting, 108, 141, 170–171 Pareto efficiency, 132–133, 136, 139–140 Peirce, Charles Sanders, 53–54, 67, 94 pension funds, 66, 74–75, 93, 95 permanent income hypothesis, 179 Pharaoh (biblical figure), 97–99 Phelps, Edmund, 17, 189–191 Philip II, king of Macedonia, 181 planning, 149–151 for consumption, 154–157 long-term vs. short-term, 148–149 rational choice applied to, 152–158, 162 play, 44–45, 167, 202 pleasure-pain principle, 18 Plutarch, 180–181 Poe, Edgar Allan, 126 pollution, 132–133 Popeye the Sailor Man, 19 portfolio theory, 64–65 positive psychology (happiness research), 25–26, 201–202 preferences, 18–19, 198 aggregating, 38–39, 132, 164 altruism and, 28, 38, 45, 104, 110, 111, 116 in behavioral economics, 24, 168 beliefs’ feedback into, 51, 55 defined, 23 intransitive, 158–159 in purposeful behavior, 25, 36 risk aversion and, 51 stability of, 33, 115, 147, 207, 208 “time-inconsistent,” 158, 159, 166, 203 present value, 7, 139 principal-agent problem, 72 Principles of Economics (Marshall), 41 prisoner’s dilemma, 105 private equity, 75 procrastination, 3, 4, 19, 177–178 prospect theory, 168 protectionism, 185–187 Prussia, 191 public equities, 75 punishment, 109 purposeful choice, 22–26, 27, 34, 36, 56, 133–134, 204–205 altruism compatible with, 104, 113–114, 115–116 commensurability and, 153–154 as default rule, 43–46 expert opinion and, 57 extreme unexpected events and, 62–63 flow of time and, 30 for-itself behavior commingled with, 40–43, 129, 171 mechanistic quality of, 68 in merchant’s choice, 135, 137–138 Pareto efficiency linked to, 132 rational choice distinguished from, 22–23 regret linked to, 128 social relations linked to, 28 stable preferences linked to, 33 in trolley problem, 135–136 vaccination and, 58–59 wage increases and, 187.


pages: 324 words: 92,805

The Impulse Society: America in the Age of Instant Gratification by Paul Roberts

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, asset allocation, business cycle, business process, Cass Sunstein, centre right, choice architecture, collateralized debt obligation, collective bargaining, computerized trading, corporate governance, corporate raider, corporate social responsibility, creative destruction, crony capitalism, David Brooks, delayed gratification, disruptive innovation, double helix, factory automation, financial deregulation, financial innovation, fixed income, full employment, game design, greed is good, If something cannot go on forever, it will stop - Herbert Stein's Law, impulse control, income inequality, inflation targeting, invisible hand, job automation, John Markoff, Joseph Schumpeter, knowledge worker, late fees, Long Term Capital Management, loss aversion, low skilled workers, mass immigration, new economy, Nicholas Carr, obamacare, Occupy movement, oil shale / tar sands, performance metric, postindustrial economy, profit maximization, Report Card for America’s Infrastructure, reshoring, Richard Thaler, rising living standards, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, shareholder value, Silicon Valley, speech recognition, Steve Jobs, technoutopianism, the built environment, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, total factor productivity, Tyler Cowen: Great Stagnation, Walter Mischel, winner-take-all economy

The very nature of the new financial tools meant any failure or breakdown would happen somewhere else, in time or space, and well outside Wall Street’s increasingly myopic field of vision. Or, to quote the acronym that traders and executives repeated whenever anyone raised concerns about the deals being done, “IBG YBG”—as in “I’ll Be Gone, You’ll Be Gone.”42 Gamblers, when their luck turns sour, often exhibit a behavioral tic known as loss aversion. It’s a survival thing—because we were adapted for scarcity, we’re predisposed to hate losing any sort of asset. In studies involving gambling, subjects perceive losses to be twice as large as wins even though the losses and wins involve the same amount of money.43 Loss aversion is why blackjack players will double-down repeatedly after a bad hand, and why stock traders will ride a losing stock into the ground. It’s also why homeowners often refuse to lower their selling price even when the market is collapsing, which is what began to happen in 2006.

“One day, it was just over. We couldn’t sell the houses.”44 Adding to the misery, however, realtors now had to get clients to understand that the massive wealth they’d possessed only months before was now gone. “You had to counsel people. I had one client come to me. He had twelve houses. He had been buying them and flipping them, and he got stuck with twelve houses. I said to him, ‘The market has stopped.’ ” Loss aversion is also an apt description of how the entire market, and especially the financial market, reacted to the collapse—with increasingly desperate moves that made the final damage so much worse. As the economy stalled and corporate earnings flattened, panicked CEOs initiated massive share buybacks. In 2007, companies on the Standard & Poor’s 500 spent 62 percent of their net profits on buybacks. The following year, they spent 89 percent.45 The buybacks helped preserve share prices and executive compensation, but they also left the companies less able to weather the downturn.

Wray, The Rise and Fall of Money Manager Capitalism (Oxford: Routledge, 2013). 42. “IBG YBG,” review of Jonathan Knee, The Accidental Investment Banker (Oxford University Press, 2006), in Words, Words, Words, http://wordsthrice.blogspot.com/2006/12/ibg-ybg.html. 43. Yexin Jessica Li, Douglas Kenrick, Vladas Griskevicius, and Stephen L. Neuberg, “Economic Decision Biases in Evolutionary Perspectives: How Mating and Self-Protection Motives Alter Loss Aversion,” Journal of Personality and Social Psychology 102, no. 3 (2012), http://www.csom.umn.edu/marketinginstitute/research/documents/HowMatingandSelf-ProtectionMotivesAlterLossAversion.pdf. 44. Interview with author. 45. William Lazonick, “The Innovative Enterprise and the Developmental State: Toward an Economics of ‘Organizational Success.’” Discussion paper presented at Finance, Innovation & Growth 2011. 46.


When the Money Runs Out: The End of Western Affluence by Stephen D. King

Albert Einstein, Asian financial crisis, asset-backed security, banking crisis, Basel III, Berlin Wall, Bernie Madoff, British Empire, business cycle, capital controls, central bank independence, collapse of Lehman Brothers, collateralized debt obligation, congestion charging, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, cross-subsidies, debt deflation, Deng Xiaoping, Diane Coyle, endowment effect, eurozone crisis, Fall of the Berlin Wall, financial innovation, financial repression, fixed income, floating exchange rates, full employment, George Akerlof, German hyperinflation, Hyman Minsky, income inequality, income per capita, inflation targeting, invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, joint-stock company, Kickstarter, liquidationism / Banker’s doctrine / the Treasury view, liquidity trap, London Interbank Offered Rate, loss aversion, market clearing, mass immigration, moral hazard, mortgage debt, new economy, New Urbanism, Nick Leeson, Northern Rock, Occupy movement, oil shale / tar sands, oil shock, old age dependency ratio, price mechanism, price stability, quantitative easing, railway mania, rent-seeking, reserve currency, rising living standards, South Sea Bubble, sovereign wealth fund, technology bubble, The Market for Lemons, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, Tobin tax, too big to fail, trade route, trickle-down economics, Washington Consensus, women in the workforce, working-age population

Entrepreneurial spirit vanishes, replaced by a desire only to protect existing income and wealth. This feature is not uniquely Argentine or Japanese. It is a deeply embedded psychological characteristic. It’s called loss aversion. Standard economic theory suggests that individuals treat gains and losses in similar fashion. In reality, however, people dislike losses far more than they enjoy gains. An economic system that seems to offer individuals the equal possibility of gains and losses – a world of stagnation rather than growth – is one that’s likely to be dominated by loss aversion. Entrepreneurial activity falls by the wayside. What we already think we have – or we are entitled to – we’ll not give up easily, even if we are much better off than previous generations. We are hard-­wired from birth to think in this way and 40 4099.indd 40 29/03/13 2:23 PM The Pain of Stagnation no amount of rational discussion makes ‘letting go’ any easier.

The Buyers had to spend their own money to purchase a mug, while the Choosers were offered the choice of either a mug or a sum of money. The Sellers started off with mugs but no money. In their experiments, the authors found that Sellers valued their mugs far 41 4099.indd 41 29/03/13 2:23 PM When the Money Runs Out more highly than the Choosers even though both groups were, in effect, faced with the same choice: both would go home either with a mug or some cash. The difference relates to loss aversion. We don’t like to lose things we already own. The Sellers had an ‘emotional’ attachment to their coffee mugs. This psychological insight is incredibly important in a world of economic stagnation or contraction, Smith’s dull and melancholy states. Melancholia sets in not just because there is an absence of economic progress but, worse, because there is a fight over the spoils of economic endeavour.

L. 41 Knickerbocker Trust Company 131 Korea 14, 193, 195, 202–4, 205 Krugman, Paul 112–15, 117, 118–19 labour market 115–16, 252 productivity 53 Landes, David 26 Latin American debt crisis 216 Layard, Richard 114, 117 Lehman Brothers 30, 255 Leveson inquiry 148 Libor 126 life expectancy 47 liquidity 84, 90 liquidity trap 72 Liquidity Coverage Ratio (LCR) 83 Little Dorrit (Dickens) 138–9 living standards 11, 27, 158, 169, 180–1 belief in ever rising 13, 34 China 27 Indonesia 197 Japan 23 Korea 195 late 19th century 185, 186 Malaysia 198 post-Second World War 139 US 11, 163 loan-to-value ratios, mortgage 51–2 Long Depression 189–90 loss aversion 40–1 lotteries 164–5 Macroeconomic Imbalance Procedure (MIP) 233 macroeconomic policies 32, 60, 121, 181, 253 Japan 21 macroprudential rules 256 Madoff, Bernie 35 Mahathir Mohamad 198–201, 205 Malaysia 193, 198–201, 205 Malthus, Thomas 37–9 Manchester United 165–6 Marr, Wilhelm 189 Marx, Karl 57, 179–80 Mary Poppins 131–2 May Report 98 Megawati Sukarnoputri 197 Mellon, Andrew 106, 108 Mexico 158 Mieno, Yasushi 21 miners 103–4 Mississippi 163 mistrust creditors and debtors 141 cross-border 176 endemic 147–9 governments 140, 217–18 of money 219–21 and political extremism 227 monetarism 59 monetary policy 58, 68–74, 77–9, 87–9, 97, 111–12 a new monetary framework 245–50 see also Gold Standard; interest rates; quantitative easing (QE) Monetary Policy Committee 90–1 monetary unions 236–7 see also eurozone moral hazard 62 mortgage-backed securities 30, 65, 136–7 mortgages 51–2, 63–5 Napoleon Bonaparte 156 Napoleon III 182 National Bank of North America 131 national incomes 32, 49–50, 141–2, 247 Germany 33 Japan 32 UK 33, 110–11, 112 US 33, 70, 109, 115, 117–18 284 4099.indd 284 29/03/13 2:23 PM Index National Lottery 164–5 nationalism 228 the Netherlands 48 New Deal 108–9 ‘new economy’ of the 1990s 29–30 New Order (Indonesia) 197 New Zealand 187 Nicholson, Viv 50 Nigeria 19 Northern Rock 30, 51–2, 129, 255 Norway 158 Occupy movement 162, 170–1 Office for Budget Responsibility 33 Oliver Twist (Dickens) 43 Osborne, George 231 Overend, Gurney and Co. 131 painkillers 70–1, 89 ‘The Panic of 1873’ 186 Paul, Ron 93 Peasants’ Revolt 213 Pension Protection Fund (PPF) 172 pensioners’ voting patterns 88 pensions 47, 51, 75, 171–3, 174 per capita incomes 27, 49, 159–60, 163 Argentina and Germany 14 China 251 France 101, 105 Germany 101, 105 India 27, 251 Indonesia 197 Japan 21 Korea 202 Malaysia 198 UK 1, 44, 101, 105 US 14, 101, 105 Perón, Eva 16 Perón, Juan 16–17 Pew Center report 173 Pickett, Kate 159 Pigou, Arthur 59 policies and central bankers 65 fiscal 58, 66–7, 69–70, 77–8, 246–7 macroeconomic 21, 32, 60, 121, 181, 253 monetary 58, 68–74, 77–9, 87–9, 97, 111–12 new monetary framework 245–50 political extremism 226–9 politics and central bankers 78, 89–90, 91–5 and economics 24–6, 34, 102, 191–2, 217 and the eurozone 224–5, 237 and expectations 152–3 and income inequality 160–1 and lack of trust 147–8, 149 and monetary regimes 119–20 voters 50, 78, 88, 222, 242–4 poll tax 211 populations, ageing 78, 88, 250 age-related expenditure 48 generational divide 171–4, 241, 243–5 Germany 136 Japan 23, 25 Portugal 50, 146, 158, 191 precious metal standards 183–4 see also Gold Standard prices asset 73 commodity 77, 109, 116–17 rising 157 see also deflation; inflation property sector see housing markets protectionism 214–15 capital controls 16, 199–200, 201, 234 tariffs 16 Protestant work ethic 26, 28 public sector see governments public spending 49–50, 66, 142, 147–8, 203 government spending 58, 109, 119 social spending 45–7 quantitative easing (QE) 72–82, 84–6, 91, 97, 176–7 ratings agencies 234–5 rationing 114–15, 142–3 recessions 2 recovery from the Asian crisis 195–6, 204–5, 206, 208–9 UK in the 1930s 101–2 redistribution by stealth 90 Reform Acts 222, 242–3 regulation 125, 256 dangers of further 214, 251 dollar transactions 177 reduction 168 the regulatory trap 83–4 Statute of Labourers 213 renminbi (currency) 177 Réveillon, Jean-Baptiste 155–6 Ricardo, David 183–4 Richard II 211–12 ringgit (currency) 198 285 4099.indd 285 29/03/13 2:23 PM When the Money Runs Out risk and banks 255–6 creditors and debtors imbalance 234 and financial services 168 and rapid economic change 170 risk aversion 216 Roosevelt, Franklin Delano 107–9, 117–18, 119, 219 Royal Bank of Scotland 30 Royal Navy 99 Russia 117, 135 Rwanda 19 Samuel, Herbert 104 Saudi Arabia 117, 135 savers and banks 136 confidence 65 and illusions 137 and income inequality 162–3 and interest rates 90, 91, 97 and the subprime boom 133–4 schisms between debtors and creditors 174–7, 191 generational 170–4 income inequality 158–70 Schwartz, Anna 59, 106, 188 second-hand car market 123–4 Sierra Leone 163 silver standard 183 SIVs (structured investment vehicles) 129–30 Skidelsky, R. and E. 37 Smith, Adam 39–40, 207 melancholy state 42, 124–5, 159–60 Snowden’s budget 99–102, 105 soccer 165 social contract, between generations 244–5 social insurance 44–8 social security systems 12 social spending 45–7 Soros, George 200 South Korea 14, 193, 195, 202–4, 205 South Sea Bubble 29 space exploration 9–10, 35 Spain deficit 54, 134 and the eurozone 191, 235–6 exports 82 fiscal position 85 government borrowing 144 interest rates 146 political disenfranchisement 95 property bubble 140 suicide of Amaia Egana 153 spending government 58, 109, 119 public sector 49–50, 66, 142, 147–8, 203 social 45–7 stagnation 37–43, 50, 52–3, 158, 219 and political extremism 227–8 Standard & Poor’s 80 ‘stately home’ effect 221–3 Statute of Labourers 211, 213 sterling 98–106, 110 Stern Review 38–9 stimulus 3–4 and jobs 116 monetary and fiscal 30, 57–8, 181 Paul Krugman 112–15, 118–19 policy 32, 69–70, 82 political debate 205 prior to the financial crisis 67 stock markets 20–1, 30, 193 stock-market crashes 18, 61–2, 66, 99, 186 Straw, Jack 212 structured investment vehicles (SIVs) 129–30 subprime boom 130, 133–4 crisis 190 Suharto 196–7, 205 surpluses 66, 135–7, 204, 232–4 Sweden 158, 204 Switzerland 158, 184 Taiwan 14 Takeshita, Noburo 24 Tanzania 19 tariffs 16 tax avoidance 49, 211, 214 taxation ancien régime and the French Revolution 154–5 death duties 139 medieval poll tax 211 taxpayers 145, 170, 174, 215, 254 technological progress 2–3, 10–11 dotcom bubble 169 and financial industry wages 167 Industrial Revolution 38 Thailand 193, 195 Thaler, R.


pages: 317 words: 89,825

No Rules Rules: Netflix and the Culture of Reinvention by Reed Hastings, Erin Meyer

Airbnb, Downton Abbey, Elon Musk, en.wikipedia.org, global village, hiring and firing, job-hopping, late fees, loose coupling, loss aversion, out of africa, performance metric, Saturday Night Live, Silicon Valley, Skype, Stephen Hawking, Steve Ballmer, Steve Jobs, subscription business

Employees who take holidays are happier, enjoy their jobs more, and are more productive. Yet many workers are hesitant to take the vacation allotted them. According to a survey conducted by Glassdoor in 2017, American workers took only about 54 percent of their entitled vacation days. Employees are likely to take even less time off if you remove the vacation allotment altogether because of a well-documented human behavior, which psychologists refer to as “loss aversion.” We humans hate to lose what we already have, even more than we like getting something new. Faced with losing something, we will do everything we can to avoid losing it. We take that vacation. If you’re not allotted vacation, you don’t fear losing it, and are less likely to take any at all. The “use it or lose it” rule built into many traditional policies sounds like a limitation, but it actually encourages people to take a break.

A Academy Awards, xvii, 165, 233 “accept or discard” feedback guideline, 31, 33 accidents and safety issues, management style and, 213–14, 269–71 “actionable” feedback guideline, 30, 31, 33, 36, 193, 257 “adapt” feedback guideline, 264 “aim to assist” feedback guideline, 30, 31, 33, 36 Airbnb, 136 Alexa and Katie, 145 alignment, 217–18, 231 on a North Star, 218–21 as tree, 221–31 Allmovie.com, 87 Amazon, 3, 81, 97, 136, 208, 232 Prime, 146, 148 amygdala, 21 Anitta, 97 annual performance reviews, 191 Antioco, John, xi–xii AOL, xviii, 236 Apple, xvii, 77, 97 “appreciate” feedback guideline, 31, 33 Arc de Triomphe, 268–69 Ariely, Dan, 83 Armstrong, Lance, 207, 232–33 Aronson, Elliot, 124 Aspen Institute, 107–8 autonomy, 133 see also decision-making; decision-making approvals, eliminating Avalos, Diego, 151 B Ballad of Buster Scruggs, The, xviii Ballmer, Steve, 122–23 Baptiste, Nigel, 64–66, 68 Bazay, Dominique, 223, 224, 227–31 Bde Maka Ska, 267, 268 Becker, Justin, 35–36 belonging cues, 24–25 bet-taking analogy, 138–40, 153–57, 225–27 Bird Box, 165 Blacklist, The, 26 Black Mirror, 157–59 Blitstein, Ryan, 52 Blockbuster, 3, 171, 236 bankruptcy of, xii, xviii late fees of, 3 Netflix’s offer to, xi–xii size of, xi, xii bonuses, 80–84 Booz Allen Hamilton, 81 brain: feedback and, 20, 21 secrets and, 103 Branson, Richard, xxiv, 50 Brazil, 137, 150, 224–26, 243, 247, 249–51, 257, 264 Brier, David, xxiv brilliant jerks, 34–36, 200 Brown, Brené, 123 Bruk, Anna, 123–24 Bull Durham, 169 Bullock, Sandra, 165 bungee jumping, 194–95 C Canada, 241 candor, 18–21, 141, 175 cultural differences around the world, 250-55, 260, 263–64 culture of, 22–23 dentist visits compared to, 190–91 as disliked but needed, 20–22 failure to speak up, 18, 27, 141 increasing, xx, xxi, 1, 12–37, 72, 100–127, 188–205 jerks and, 34–36 misuse of, 29, 30, 36 “only say about someone what you will say to their face,” 15, 189–90 performance and, 17–20 and readiness to release decision-making controls, 133–35 saying what you really think with positive intent, 13–37 see also feedback; transparency Carey, Chris, 181 Caro, Manolo, 137 Caruso, Rob, 113–14 Casa De Papel, La, xviii celebrating wins, 140, 152 Chapman, Jack, 86 Chase, Chevy, 222 cheating, 62–64 Chelsea, 115–16 children’s programming, 144–45, 226–31 Choy, Josephine, 252–54, 257 Christensen, Nathan, 51 circle of feedback (360-degree assessments), 26–27, 189–205 benefits of, 202–3 discussion facilitated by, 194 in Japan, 256 live, 197–203 stepping out of line during, 200–201 tips for, 199–200 written, names used in, 191–97 Cobb, Melissa, 221–27, 231 Coen, Joel and Ethan, xii Coherent Software, 101, 104 collaboration, 170, 178 Colombia, 251 Comparably, xvii competitiveness, internal, 177–78 compliments and praise, 21, 23 computer software, 77–78, 216 conformity, 141–42 connecting the dots, xxiv first dot, 10–11 second dot, 36 third dot, 69 fourth dot, 98 fifth dot, 125 sixth dot, 160 seventh dot, 185 eighth dot, 203–4 ninth dot, 233 last dot, 264–65 consensus building, 149 contagious behavior, 8–10 context, see leading with context, not control contract signing, 149–51 control, leadership by, 209 ExxonMobil example of, 213–14 leading with context versus, 209–12 see also leading with context, not control controls, removing, xx, xxi, 1, 38–72, 128–61, 206–36 decision-making approvals, 129–61 bet-taking analogy in, 138–40, 153–57, 225–27 Informed Captain model in, 140, 149–52, 216, 223, 224, 231, 248 and picking the best people, 165–66 readiness for, 133–35 signing contracts, 149–51 travel and expense approvals, 55–72 cheating and, 62–64 company’s best interest and, 58, 59, 61, 66, 68–69 context and, 59–62 Freedom and Responsibility ethos and, 60–62 frugality and, 64–69 vacation policy, xv, 39–53, 56, 69–70 freedom and responsibility and, 52–53 Hastings’ nightmares about, 40–41, 42, 44 Hastings’ vacations, 44, 45, 47 Japanese workers and, 46–47 leaders’ modeling and, 42–47 loss aversion and, xv–xvi and setting and reinforcing context to guide employee behavior, 48–49 value added by, 50–52 see also leading with context, not control corporate culture, xiii of Netflix, xiii, xxii, xxiii, 45 Netflix Culture Deck, xiii–xvi, 172–73 Costa, Omarson, 150–51 coupling: alignment and, 218 loose versus tight, 215–17 Coyle, Daniel, 24 creative positions, 78–79, 83–84 criticism (negative feedback), 19–21, 23 belonging cues and, 24 brain and, 20, 21 cultural differences around the world, 251, 261 as disliked but needed, 20–22 language used in, 251–52 responding to, 24, 31 upgraders and downgraders in, 251–52 see also feedback Crook-Davies, Danielle, 19–20 Crown, The, xvii Cryan, John, 82–83 Cuarón, Alfonso, xii, 165 cultural differences around the world, see global expansion and cultural differences Culture Code, The (Coyle), 24 culture map, 242–50 Culture Map, The (Meyer), xxii, 19, 242–50 culture of freedom and responsibility, see Freedom and Responsibility D Daring Greatly: How the Courage to Be Vulnerable Transforms the Way We Live, Love, Parent, and Lead (Brown), 123 Dark, xvii days off, 39–40 see also vacation policy, removing decision-making: dispersed, 216–17 innovation and, 130, 131, 135, 136 and leading with context, 210, 216, 217 to please the boss, 129–30, 133, 152–53 pyramid structure for, 129, 221–23 spreadsheet system and, 143–44 talent density and, 131 transparency and, 131 decision-making approvals, eliminating, 129–61 bet-taking analogy in, 138–40, 153–57, 225–27 Informed Captain model in, 140, 149–52, 216, 223, 224, 231, 248 and picking the best people, 165–66 readiness for, 133–35 signing contracts, 149–51 Del Castillo, Kate, 138 Del Deo, Adam, 207–9, 232–33 Disney, 144, 221, 222, 226, 227 dissent, farming for, 140–44, 158 diversity, 241 Dora the Explorer, 145 Dormen, Yasemin, 157–59 dot-com bubble, 4 dots, see connecting the dots downloading, 146–48 dream teams, 76 DreamWorks, 145, 221, 226 driver feedback, 22 Dutch, Netherlands, 242, 243, 246, 248, 251, 261–63 DVDs, 3–4, 5, 129 Qwikster and, 140–42 shift to streaming from, xii, xvii, 140–41, 236 E Edmondson, Amy, xv Eichenwald, Kurt, 176 Eisner, Michael, 195 elephants, penguins versus, 174 Elite, xvii Emmy Awards, xvii, 145 “Emperor’s New Clothes” syndrome, 23–29 empowerment, 109, 133, 134 see also decision-making; decision-making approvals, eliminating; Freedom and Responsibility Engadget, 158 Enron, xiii entrepreneurship, 138 error prevention, and management style, 213–14, 220, 269–71 Escobar, Pablo, 132 Estaff meetings, 218–19, 243 Evening Standard, 25 Eventbrite, 50 expenses, see travel and expenses; travel and expense approvals, removing experimentation, 138 Explorer project, 154–55, 157 Express, 158 ExxonMobil, 213–14 F Facebook, xiii, 77, 97, 130, 137, 195 failures, 140, 152–59 asking what learning came from the project, 153, 155 not making a big deal about, 153–55 sunshining of, 153, 155–59 family business metaphor, 166–68 moving to sports team metaphor from, 168–70, 173–74 farming for dissent, 140–44, 158 Fast Company, xxiv, 213 fear of losing one’s job, xv, 178–80, 183–84 Fearless Organization, The (Edmondson), xv FedEx, 139 feedback, 14–17, 139, 175, 190, 240 annual performance reviews and, 191 belonging cues and, 24 brain’s response to, 20, 21 circle of (360-degree assessments), 26–27, 189–205 benefits of, 202–3 discussion facilitated by, 194 in Japan, 256 live, 197–203 stepping out of line during, 200–201 tips for, 199–200 written, names used in, 191–97 cultural differences and, 250-57, 260, 261–64 for drivers, 22 “Emperor’s New Clothes” syndrome and, 23–29 failure to speak up with, 18, 27, 141 4A guidelines for, 29–36, 255, 264 accept or discard, 31, 33 actionable, 30, 31, 33, 36, 193, 257 adding 5th A to (adapt), 264 aim to assist, 30, 31, 33, 36 appreciate, 31, 33 cultural differences and, 260 for giving feedback, 30 for receiving feedback, 31 frequency of, 18 Hastings and, 26–29 honesty in, 18; see also candor Japanese culture and, 251–57 loop of, 22–23 Meyer and, 19, 32 negative (criticism), 19–21, 23 belonging cues and, 24 brain and, 20, 21 cultural differences around the world, 251, 261 as disliked but needed, 20–22 language used in, 251–52 responding to, 24, 31 upgraders and downgraders in, 251–52 positive, brain and, 21 responding to, 24, 31 and speaking and reading between the lines, 253 spreadsheet system for gathering, 143–44 survey on, 21–22 teaching employees how to give and receive, 29–32 from teammates, 199 when and where to give, 31–34 see also candor Felps, Will, 8–9 firing, see letting people go Fisher Phillips, 50 five-year plans, 219–20 Flint, Joe, 178 flexibility, and leading with context or control, 220, 221 Fogel, Bryan, 207–8, 233 4K ultra high definition televisions, 65–66 Fowler, Geoffrey, 65–66 Fox, 221 France, 240, 251 Paris, 268–69 Freedom and Responsibility (F&R), xx–xxi, 191, 236, 267, 268 expenses and, 60–62 first steps to, 1–72 Informed Captain model in, 140, 149–52, 216, 223, 224, 231, 248 next steps to, 73–161 techniques to reinforce, 163–236 vacations and, 52–53 weight of responsibility in, 150–52 Friedland, Jonathan, 196 Fuller House, 145 G Game of Thrones, 131–32 Garden Grove, Calif., 22 Gates, Bill, 78 General Electric (GE), 177–78 Germany, 147–48, 250–51 Gizmodo, 178 Gladwell, Malcolm, 142 Glassdoor, xv, 50 global expansion and cultural differences, 237–65, 239–65 adjusting your style for, 257–61 Brazil, 137, 150, 224–26, 243, 247, 249–51, 257, 264 candor and, 250–55, 260, 263–64 culture map, 242–50 feedback and, 250–57, 260, 261–64 Google and, 240–41 Japan, 46–47, 183, 224, 225, 257, 261 in culture map, 243, 247, 248 feedback and criticism in, 251–57 Japanese language, 252–53 360 process and, 256 Netherlands, 242, 243, 246, 248, 251, 261–63 Schlumberger and, 240–41 Singapore, 243, 246, 248, 251, 257–59, 261, 264 trust and, 248, 249 Golden Globe Awards, xvii, 76 Goldman Sachs, 177 Golin, 50 Google, xvii, 77, 94–96, 98, 136 global expansion of, 240–41 gossip, 189 Guillermo, Rob, 207 H Handler, Chelsea, 115–16 happiness, xvii Harvard Business Review, xxii Hastings, Mike, 87 Hastings, Reed: childhood of, 10, 13 at Coherent Software, 101, 104 downloading issue and, 146–48 feedback and, 26–27 interview with, 173–80 in leadership tree, 224–25 marriage of, 13–15 Meyer contacted by, xxii–xxiii Netflix cofounded by, xi, 3–4 in Netflix’s offer to Blockbuster, xi–xii in Peace Corps, xxii, xxiii, 14, 101, 239–40 Pure Software company of, xviii–xix, xxiv, 3, 4, 6, 7, 13–14, 55, 64, 71, 101, 122, 123, 236 Qwikster and, 140–42 HBO, 113–14, 208 Hewlett-Packard (HP), 66–67 hierarchy of picking, 165–66 Hired, xvii hiring: hierarchy of picking and, 165–66 talent density and, see talent density honesty, xvi, xxiii, 178 and spending company money, 58–59 see also candor; transparency hours worked, 39 House of Cards, xvii, 65, 75, 171, 236 HubSpot, xvii, 50 Huffington Post, xxii Hulu, 208, 232 humility, 123 Hunger Games, The, 176 Hunt, Neil, 41, 45, 94, 98, 154, 196 downloads and, 146, 148 and Netflix as team, not family, 173–74 360s and, 197, 198 vacations of, 41 I Icarus, 207–8, 232–33 India, 83, 84, 147–48, 224–26 Mighty Little Bheem in, 228–31 industrial era, 269, 271 industry shifts, xvii–xviii, xix Informed Captain model, 140, 149–52, 216, 223, 224, 231, 248 innovation, xv, xix, xxi, 84, 135–36, 155, 271–72 decision-making and, 130, 131, 135, 136 and leading with context or control, 214–15, 217 Innovation Cycle, 139–40 asking what learning came from the project, 153, 155 celebrating wins, 140, 152 failures and, 140, 152–59 farming for dissent, 140–44, 158 not making a big deal about failures, 153–55 placing your bet as an informed captain, 140, 149–52 socializing the idea, 140, 144–45, 158, 159 spreadsheet system and, 143–44 sunshining failures, 153, 155–59 testing out big ideas, 140, 146–48 International Olympic Committee, 232 internet, 146–48, 154 internet bubble, 4 iPhone, 130 Italy, 131–32 J Jacobson, Daniel, 166–68 Jaffe, Chris, 153–57 Japan, 46–47, 183, 224, 225, 257, 261 in culture map, 243, 247, 248 feedback and criticism in, 251–57 Japanese language, 252–53 360 process and, 256 jerks, 34–36, 200 Jobs, Steve, xxiv, 130 Jones, Rhett, 178 K karoshi, 46 kayaking, 180 Keeper Test, xiv, 165–87, 240, 242 Keeper Test Prompt, 180–83 Key Performance Indicators (KPIs), 81, 191, 209 Kilgore, Leslie, 14–15, 81, 94, 171 expense reports and, 61–62 on hiring and recruiters, 95–96 “lead with context, not control” coined by, 48, 208–9 new customers and, 81–82 signing contracts and, 149–50 360s and, 192, 193, 197, 198 King, Rochelle, 27–29 Kodak, xviii, 236 Korea, 224, 225 Kung Fu Panda, 221 L Lanusse, Adrien, 148 Latin America, 136, 241, 249 Brazil, 137, 150, 224–26, 243, 247, 249–51, 257, 264 Lawrence, Jennifer, 176 lawsuits, 175 layoffs at Netflix, 4–7, 10, 77, 168 leading with context, not control, 48, 207–36 alignment in, 217–18, 231 on a North Star, 218–21 as tree, 221–31 control versus context, 209–12 decision-making in, 210, 216, 217 Downton Abbey-type cook example, 211–12, 218 error prevention and, 213–14, 220, 269–71 ExxonMobil example, 213–14 Icarus example, 207–8, 232–33 innovation and, 214–15, 217 Kilgore’s coining of phrase, 48, 208–9 and loose versus tight coupling, 215–17 Mighty Little Bheem example, 228–31 parenting example, 210–11 spending and, 59–62 talent density and, 212, 213 Target example, 213–15 lean workforce, 79 letting people go, 173–76 “adequate performance gets a generous severance,” xv, xxii, 171, 175–76, 242 employee fears about, xv, 178–80, 183–84 employee turnover, 184–85 in Japan, 183 Keeper Test, xiv, 165–87, 240, 242 Keeper Test Prompt, 180–83 lawsuits and, 175 at Netflix, 185 Netflix layoffs in 2001, 4–7, 10, 77, 168 post-exit communications, 117–20, 183–84 quotas for, 178 LinkedIn, 50, 51, 137 Little Prince, The (Saint-Exupéry), 215 loose versus tight coupling, 215–17 Lorenzoni, Paolo, 131–33, 135, 138 loss aversion, xv–xvi Low, Christopher, 258–60 M Mammoth, 51 Management by Objectives, 209 Man of the House, 222 Massachusetts Institute of Technology, 83 McCarthy, Barry, 14–15, 56 McCord, Patty, 4–7, 9, 10, 15, 27–28, 41, 53, 71, 173 all-hands meetings and, 108 departure from Netflix, 171 expense policy and, 55, 60–61 financial data and, 110 salary policy and, 78, 81, 94, 96 team metaphor and, 169 360s and, 197–99 vacation policy and, 40, 43, 45, 52–53 Memento project, 156, 157 Mexico, 136–38 Meyer, Erin, xxii The Culture Map, xxii, 19, 242–50 Hastings’ message to, xxii–xxiii keynote address of, 19, 32 Netflix employees interviewed by, xxiii, 19–20 in Peace Corps, xxii micromanaging, 130, 133, 134 Microsoft, 78, 122, 176–78 Mighty Little Bheem, 228–31 Mirer, Scott, 200–201 mistakes, 121–25, 271–72 distancing yourself from, 157 management style and, 213–14, 220, 270 sunshining of, 157 see also failures Morgan Stanley, 123 Moss, Trenton, 50–51 Mr.

., 22 Gates, Bill, 78 General Electric (GE), 177–78 Germany, 147–48, 250–51 Gizmodo, 178 Gladwell, Malcolm, 142 Glassdoor, xv, 50 global expansion and cultural differences, 237–65, 239–65 adjusting your style for, 257–61 Brazil, 137, 150, 224–26, 243, 247, 249–51, 257, 264 candor and, 250–55, 260, 263–64 culture map, 242–50 feedback and, 250–57, 260, 261–64 Google and, 240–41 Japan, 46–47, 183, 224, 225, 257, 261 in culture map, 243, 247, 248 feedback and criticism in, 251–57 Japanese language, 252–53 360 process and, 256 Netherlands, 242, 243, 246, 248, 251, 261–63 Schlumberger and, 240–41 Singapore, 243, 246, 248, 251, 257–59, 261, 264 trust and, 248, 249 Golden Globe Awards, xvii, 76 Goldman Sachs, 177 Golin, 50 Google, xvii, 77, 94–96, 98, 136 global expansion of, 240–41 gossip, 189 Guillermo, Rob, 207 H Handler, Chelsea, 115–16 happiness, xvii Harvard Business Review, xxii Hastings, Mike, 87 Hastings, Reed: childhood of, 10, 13 at Coherent Software, 101, 104 downloading issue and, 146–48 feedback and, 26–27 interview with, 173–80 in leadership tree, 224–25 marriage of, 13–15 Meyer contacted by, xxii–xxiii Netflix cofounded by, xi, 3–4 in Netflix’s offer to Blockbuster, xi–xii in Peace Corps, xxii, xxiii, 14, 101, 239–40 Pure Software company of, xviii–xix, xxiv, 3, 4, 6, 7, 13–14, 55, 64, 71, 101, 122, 123, 236 Qwikster and, 140–42 HBO, 113–14, 208 Hewlett-Packard (HP), 66–67 hierarchy of picking, 165–66 Hired, xvii hiring: hierarchy of picking and, 165–66 talent density and, see talent density honesty, xvi, xxiii, 178 and spending company money, 58–59 see also candor; transparency hours worked, 39 House of Cards, xvii, 65, 75, 171, 236 HubSpot, xvii, 50 Huffington Post, xxii Hulu, 208, 232 humility, 123 Hunger Games, The, 176 Hunt, Neil, 41, 45, 94, 98, 154, 196 downloads and, 146, 148 and Netflix as team, not family, 173–74 360s and, 197, 198 vacations of, 41 I Icarus, 207–8, 232–33 India, 83, 84, 147–48, 224–26 Mighty Little Bheem in, 228–31 industrial era, 269, 271 industry shifts, xvii–xviii, xix Informed Captain model, 140, 149–52, 216, 223, 224, 231, 248 innovation, xv, xix, xxi, 84, 135–36, 155, 271–72 decision-making and, 130, 131, 135, 136 and leading with context or control, 214–15, 217 Innovation Cycle, 139–40 asking what learning came from the project, 153, 155 celebrating wins, 140, 152 failures and, 140, 152–59 farming for dissent, 140–44, 158 not making a big deal about failures, 153–55 placing your bet as an informed captain, 140, 149–52 socializing the idea, 140, 144–45, 158, 159 spreadsheet system and, 143–44 sunshining failures, 153, 155–59 testing out big ideas, 140, 146–48 International Olympic Committee, 232 internet, 146–48, 154 internet bubble, 4 iPhone, 130 Italy, 131–32 J Jacobson, Daniel, 166–68 Jaffe, Chris, 153–57 Japan, 46–47, 183, 224, 225, 257, 261 in culture map, 243, 247, 248 feedback and criticism in, 251–57 Japanese language, 252–53 360 process and, 256 jerks, 34–36, 200 Jobs, Steve, xxiv, 130 Jones, Rhett, 178 K karoshi, 46 kayaking, 180 Keeper Test, xiv, 165–87, 240, 242 Keeper Test Prompt, 180–83 Key Performance Indicators (KPIs), 81, 191, 209 Kilgore, Leslie, 14–15, 81, 94, 171 expense reports and, 61–62 on hiring and recruiters, 95–96 “lead with context, not control” coined by, 48, 208–9 new customers and, 81–82 signing contracts and, 149–50 360s and, 192, 193, 197, 198 King, Rochelle, 27–29 Kodak, xviii, 236 Korea, 224, 225 Kung Fu Panda, 221 L Lanusse, Adrien, 148 Latin America, 136, 241, 249 Brazil, 137, 150, 224–26, 243, 247, 249–51, 257, 264 Lawrence, Jennifer, 176 lawsuits, 175 layoffs at Netflix, 4–7, 10, 77, 168 leading with context, not control, 48, 207–36 alignment in, 217–18, 231 on a North Star, 218–21 as tree, 221–31 control versus context, 209–12 decision-making in, 210, 216, 217 Downton Abbey-type cook example, 211–12, 218 error prevention and, 213–14, 220, 269–71 ExxonMobil example, 213–14 Icarus example, 207–8, 232–33 innovation and, 214–15, 217 Kilgore’s coining of phrase, 48, 208–9 and loose versus tight coupling, 215–17 Mighty Little Bheem example, 228–31 parenting example, 210–11 spending and, 59–62 talent density and, 212, 213 Target example, 213–15 lean workforce, 79 letting people go, 173–76 “adequate performance gets a generous severance,” xv, xxii, 171, 175–76, 242 employee fears about, xv, 178–80, 183–84 employee turnover, 184–85 in Japan, 183 Keeper Test, xiv, 165–87, 240, 242 Keeper Test Prompt, 180–83 lawsuits and, 175 at Netflix, 185 Netflix layoffs in 2001, 4–7, 10, 77, 168 post-exit communications, 117–20, 183–84 quotas for, 178 LinkedIn, 50, 51, 137 Little Prince, The (Saint-Exupéry), 215 loose versus tight coupling, 215–17 Lorenzoni, Paolo, 131–33, 135, 138 loss aversion, xv–xvi Low, Christopher, 258–60 M Mammoth, 51 Management by Objectives, 209 Man of the House, 222 Massachusetts Institute of Technology, 83 McCarthy, Barry, 14–15, 56 McCord, Patty, 4–7, 9, 10, 15, 27–28, 41, 53, 71, 173 all-hands meetings and, 108 departure from Netflix, 171 expense policy and, 55, 60–61 financial data and, 110 salary policy and, 78, 81, 94, 96 team metaphor and, 169 360s and, 197–99 vacation policy and, 40, 43, 45, 52–53 Memento project, 156, 157 Mexico, 136–38 Meyer, Erin, xxii The Culture Map, xxii, 19, 242–50 Hastings’ message to, xxii–xxiii keynote address of, 19, 32 Netflix employees interviewed by, xxiii, 19–20 in Peace Corps, xxii micromanaging, 130, 133, 134 Microsoft, 78, 122, 176–78 Mighty Little Bheem, 228–31 Mirer, Scott, 200–201 mistakes, 121–25, 271–72 distancing yourself from, 157 management style and, 213–14, 220, 270 sunshining of, 157 see also failures Morgan Stanley, 123 Moss, Trenton, 50–51 Mr.


Quantitative Trading: How to Build Your Own Algorithmic Trading Business by Ernie Chan

algorithmic trading, asset allocation, automated trading system, backtesting, Black Swan, Brownian motion, business continuity plan, buy and hold, compound rate of return, Edward Thorp, Elliott wave, endowment effect, fixed income, general-purpose programming language, index fund, John Markoff, Long Term Capital Management, loss aversion, p-value, paper trading, price discovery process, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Ray Kurzweil, Renaissance Technologies, risk-adjusted returns, Sharpe ratio, short selling, statistical arbitrage, statistical model, survivorship bias, systematic trading, transaction costs

Hence, it is critical even if we trade using quantitative strategies to understand some of our own psychological weaknesses. Fortunately, there is a field of financial research called “behavioral finance” (Thaler, 1994) that studies irrational financial decision making. I will try to highlight a few of the common irrational behaviors that affect trading. The first behavioral bias is known variously as the endowment effect, status quo bias, or loss aversion. The first two effects cause some traders to hold on to a losing position for too long, because traders (and people in general) give too much preference to the status quo (the status quo bias), or because they demand much more P1: JYS c06 JWBK321-Chan September 24, 2008 Money and Risk Management 13:57 Printer: Yet to come 109 to give up the stock than what they would pay to acquire it (the endowment effect).

As I argued in the risk management section, there are rational reasons to hold on to a losing position (e.g., when you expect mean-reverting behavior); however, these behavioral biases cause traders to hold on to losing positions even when there is no rational reason (e.g., when you expect trending behavior, and the trend is such that your positions will lose even more). At the same time, the loss aversion bias causes some traders to exit their profitable positions too soon, even if holding longer will lead to a larger profit on average. Why do they exit the profitable positions so soon? Because the pain from possibly losing some of the current profits outweighs the pleasure from gaining higher profits. This behavioral bias manifests itself most clearly and most disastrously when one has entered a position by mistake (because of either a software bug, an operational error, or a data problem) and has incurred a big loss.

See Sharpe ratio Information, slow diffusion of, 117–118 Interactive Brokers, 15, 73, 82, 83 Investors, herdlike behavior of, 118–119 J January effect, 143–146 backtesting, 144–146 Java, 80, 85 P1: JYS ind JWBK321-Chan October 2, 2008 14:7 178 K Kalman filter, 116 Kavanaugh, Paul, 149 Kelly formula, 95, 97, 100–103, 105, 107, 153, 161 calculating the optimal allocation based on, 100–102 calculating the optimal leverage based on, 99 simple derivation of, when return distribution is Gaussian, 112–113 Kerviel, Jérôme, 160 Khandani, Amir, 104 Kirk Report, 10 L LeSage, James, 168 Leverage, 5, 95–103 Liquidnet, 73 Lo, Andrew, 104 Logical Information Machines, 35, 36 Long-only versus market-neutral strategies, calculating Sharpe ratio for, 45–47 Long-Term Capital Management, 110, 157 Long-term wealth, maximizing, 96 Look-ahead bias, 51–52 Loss aversion, 108–109 M Market impact, 22 MarketQA (Quantitative Analytics), 35 Markov models, hidden, 116, 121 Printer: Yet to come INDEX R , 21, 32–34, MATLAB 137–139 calculating optimal allocation using Kelly formula, 100–102 a quick survey of, 163–168 using in automated trading systems, 80, 81, 83, 85 using to avoid look-ahead bias, 51–52 using to backtest January effect, 144–146 mean-reverting strategy with and without transaction costs, 61–65 year-on-year seasonal trending strategy, 146–148 using to calculate maximum drawdown and its duration, 48–50 using to calculate Sharpe ratio for long-only strategies, 46–47 using for pair trading, 56–58, 59–60 using to scrape web pages for financial data, 34 MCSI Barra, 35, 136 Mean-reverting versus momentum strategies, 116–119 Mean-reverting time series, calculation of the half-life of, 141–142 Millennium Partners, 12 Model risk, 107 ModelStation (Clarifi), 35 Momentum strategies, mean-reverting versus, 116–119 P1: JYS ind JWBK321-Chan October 2, 2008 14:7 Index Money and risk management, 95–113 optimal capital allocation and leverage, 95–103 psychological preparedness, 108–111 risk management, 103–108 Murphy, Kevin, 168 N National Association of Securities Dealers (NASD) Series 7 examination, 70 National Bureau of Economic Research, 10 Neural networks, 116 New York Mercantile Exchange (NYMEX), 16, 149 Northfield Information Services, 136 O Oanda, 37, 73 Octave, 33 O-Matrix, 33 Ornstein-Uhlenbeck formula, 140–141, 142 Out-of-sample testing, 53–55 P Pair trading of GLD and GDX, 55 Paper trading, 55 testing your system by, 89–90 Parameterless trading models, 54–55 PFG Futures, 73 Plus-tick rule, elimination of, 92, 120 Posit (ITG), 73 Position risk, 107 Printer: Yet to come 179 Post earnings announcement drift (PEAD), 118 Principal component analysis (PCA), 136–139 Profit and loss (P&L), 6, 89 curve, 20 Programming consultant, hiring a, 86–87 Psychological preparedness, 108–111 Q Qian, Edward, 154 Quantitative Analytics, 35 Quantitative Services Group, 136 Quantitative trading, 1–8 business case for, 4–8 demand on time, 5–7 marketing, nonnecessity of, 7–8 scalability, 5 the way forward, 8 special topics in, 115–156 exit strategy, 140–143 factor models, 133–139 high-frequency trading strategies, 151–153 high-leverage versus high-beta portfolio, 153–154 mean-reverting versus momentum strategies, 116–119 regime switching, 119–126 seasonal trading strategies, 143–151 stationarity and cointegration, 126–133 who can become a quantitative trader, 2–4 Quotes-plus.com, 37 P1: JYS ind JWBK321-Chan October 2, 2008 14:7 180 R Random walking, 116 REDIPlus trading platform (Goldman Sachs), 73, 82, 83, 84 Regime shifts, 25, 91–92 Regime switching, 119–126 academic attempts to model, 120–121 Markov, 121 using a machine learning tool to profit from, 122–126 Regulation T (SEC), 5, 14, 69–70 Renaissance Technologies Corporation, 104 Representativeness bias, 109 Reverse split, 38 Risk management, 103–108.


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Beyond the Random Walk: A Guide to Stock Market Anomalies and Low Risk Investing by Vijay Singal

3Com Palm IPO, Andrei Shleifer, asset allocation, buy and hold, capital asset pricing model, correlation coefficient, cross-subsidies, Daniel Kahneman / Amos Tversky, diversified portfolio, endowment effect, fixed income, index arbitrage, index fund, information asymmetry, liberal capitalism, locking in a profit, Long Term Capital Management, loss aversion, margin call, market friction, market microstructure, mental accounting, merger arbitrage, Myron Scholes, new economy, prediction markets, price stability, profit motive, random walk, Richard Thaler, risk-adjusted returns, risk/return, selection bias, Sharpe ratio, short selling, survivorship bias, transaction costs, Vanguard fund

Understanding and Learning from Behavioral Finance Investors hold losers for too long and sell winners too quickly. Most investors suffer from the tendency to hold on to losers for too long because they are loss-averse and do not wish to realize a loss. Investors are also overconfident and do not believe that they made a bad decision. They hope that the stock will turn around. By the time they accept an error in judgment, it is too late. Investors also make a sharp distinction between paper losses or gains and realized losses or gains, fooling themselves into believing that a paper loss/gain is not a real loss/gain. Similarly and based on loss aversion, there is a tendency to realize profits quickly before the investment becomes a loss. Investors trade too much. Chasing winners and the ease of Internet trading causes excessive trading.

Even though the real change in salary is –6 percent for the first worker and 2 percent for the second worker, the pay raises are framed and compared separately from inflation rates. Consequently, the first worker is likely to be happier than the second. In the same vein, investors look at each stock individually, not as part of a portfolio as traditional economists assume. As a result, investors engage in mental accounting. They tend to value stocks that pay dividends more than stocks that pay capital gains. They tend to be loss-averse rather than risk averse. Some experiments find that investor behavior is consistent with frame dependence. For example, investors are known to hold losers for too long because they are averse to realizing a loss. On the other hand, investors sell winners too quickly because they don’t want to see the winner become a loser. Explaining Anomalous Price Patterns with Behavioral Finance Since the behavior outlined with frame dependence and heuristics is not economically rational, what does it mean?

A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets. Journal of Finance 54(6), 2143–84. Kadlec, Gregory B., and John J. McConnell. 1994. The Effect of Market Segmentation and Illiquidity on Asset Prices: Evidence from Exchange Listings. Journal of Finance 49(2), 611–36. Kahneman, Daniel, Jack L. Knetsch, and Richard H. Thaler. 1991. Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias. Journal of Economic Perspectives 5(1), 193–206. Kahneman, Daniel, and Amos Tversky. 1979. Prospect Theory: An Analysis of Decision Under Risk. Econometrica 47(2), 263–92. Mackenzie, Craig. 1997. Where Are the Motives? A Problem with Evidence in the Work of Richard Thaler. Journal of Economic Psychology 18(1), 123–35. Merton, Robert C. 1987. Presidential Address: A Simple Model of Capital Market Equilibrium with Incomplete Information.


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Irresistible: The Rise of Addictive Technology and the Business of Keeping Us Hooked by Adam L. Alter

Alexey Pajitnov wrote Tetris, augmented reality, barriers to entry, call centre, Cass Sunstein, cognitive dissonance, Daniel Kahneman / Amos Tversky, easy for humans, difficult for computers, en.wikipedia.org, experimental subject, game design, Google Glasses, IKEA effect, Inbox Zero, Kickstarter, loss aversion, Mark Zuckerberg, Menlo Park, mental accounting, meta analysis, meta-analysis, Oculus Rift, Richard Thaler, side project, Skype, Snapchat, Steve Jobs, telemarketer

Back, and Stanley Schacter, Social Pressures in Informal Groups: A Study of Human Factors in Housing (Stanford, CA: Stanford University Press, 1950). Rewards are a: On the power of loss aversion and motivation: Thomas C. Schelling, “Self-Command in Practice, in Policy, and in a Theory of Rational Choice, American Economic Review 74, no. 2 (1984): 1–11; Jan Kubanek, Lawrence H. Snyder, and Richard A. Abrams, “Reward and Punishment Act as Distinct Factors in Guiding Behavior,” Cognition 139 (June 2015): 154–67; Ronald G. Fryer, Steven D. Levitt, John List, and Sally Sadoff, “Enhancing the Efficacy of Teacher Incentives Through Loss Aversion: A Field Experiment,” Working Paper 18237, National Bureau of Economic Research, Cambridge, MA, 2012; Daniel Kahneman and Amos Tversky, “Prospect Theory: An Analysis of Decision under Risk,” Econometrica 47, no. 2 (March 1979): 263–92.

Bidders form an emotional attachment to winning the auction. For the two students bidding up to $60 in my classroom, the motivation isn’t the thrill of winning $20—it’s the threat of losing to the other bidder. As neuroscientist Kent Berridge suggested, their facial expressions show that they want to keep bidding, but they’re certainly not liking the experience at all. You can see the same loss aversion even more clearly in so-called penny auction websites like Quibids.com, HappyBidDay.com, and Beezid.com. To begin using Beezid, for example, you buy a pack of bids. Packs range in size from forty bids (for $36, or 90 cents per bid) to one thousand bids (for $550, or 55 cents per bid). The Beezid site features hundreds of ongoing auctions for products like laptops, TVs, and headphones. This is how an auction for a new TV looks after the first bid: The first bid was for one cent—a single cent!

(IGN column), 178 Italian Job, The (movie), 191–92, 204 Jarecki, Andrew, 199 Jeong, Ken, 279–80 Jinx, The (real-life crime documentary), 199–200 Jobs, Steve, 1, 2, 4 John, Daymond, 279–80 Johnson, Eric, 209 Journey, 202 juice, 137–39 Just Press Play program, 304–5 Kagan, Jerome, 19–20 Kahneman, Daniel, 282 Kaiser Foundation, 245–46 Kappes, Heather, 161 Kardashian, Kim, 158 “Karma Police” (Radiohead), 195 karoshi (death from overworking), 186–87 Keas, 300–302 Kennedy, Joe, 279–80 khat leaf, 31 King, 137 Klosterman, Chuck, 109–10 Koenig, Sarah, 196, 197, 203 Kondo, Marie, 207–8 KonMari, 207–8 Kotler, Steven, 142 Kraft, Robert, 116 Krieger, Mike, 216–17 Kulagin, Mikhail, 172–73 Lancet, 296 Lantz, Frank, 164–65, 188–89, 300 Larson, Michael, 100–106 Larson, Teresa, 106 Lawrence, Andrew, 82–85 laziness, 305–6 leaderboards, 298 League of Legends (game), 228 learning, gamification of, 302–5 Lee, Hae Min, 196, 198, 200, 203 Lego, 174 Lewis, Michael, 119 Liar’s Poker (Lewis), 119 Life-Changing Magic of Tidying Up, The (Kondo), 207–8 likes/like button, 127–29, 217 Lindner, Emilee, 159 LinkedIn, 128 Litras, Janie, 103 Little Mister Cricket (game), 138–39 LiveOps, 306–7 Long, Ed, 103 Lord of the Rings (Tolkien), 305 loss aversion, 152–54 losses disguised as wins, 133–34 love, 75–78 Love and Addiction (Peele), 76 “Love Is Like Cocaine” (Fisher), 75–76 Lovematically, 128–29 Love (TV show), 212 Luckey, Palmer, 141–42 Lucky Larry’s Lobstermania (slot machine), 133–34 ludic loops, 177–79 Lumos Labs, 313 MacInnis, Cara, 265 Mad Men (TV show), 290 Making a Murderer (real-life crime documentary), 199–200 mapping, 139 marathon runners, and goal-setting, 95–97 Marks, Isaac, 76–77 Massachusetts Institute of Technology, 275 Matheus, Kayla, 282–83 Medalia, Hilla, 252 medical benefits, of gamification, 309–12 Meier, Darleen, 206–7 melatonin, 69–70 memory, and addiction, 57–60 micro-cliffhangers, 205–8 microfeedback, 136–37 Microsoft, 28–29 Milner, Peter, 52–57, 67 Miyamoto, Shigeru, 147–49, 155, 166 Mochon, Daniel, 173 Moment (app), 13–15 Morrissey, Tracie, 159 Moti, 282–83 motivated perception, 144–45 motivational interviewing, 258–62 MUDs (multiuser dungeons), 227–28 Murphy, Morgan, 48 Muscat, Luke, 164 Myst, 3 Myst (game), 178 nail-biting, 267–69 Nanya, 186 National Public Radio, 196 Nature, 312 NBC News Online, 197 Neanderthals, 30 near wins, 145–46, 181–83 negative reinforcement, 21 Netflix, 3, 199, 208, 210–12, 287–89, 291 NeuroRacer, 312 New York Times, 48, 141, 215–16 Nguyen, Dong, 42–43 nicotine, 31 nicotine gum, 267 Nintendo, 148, 171 Nixon, Richard, 47–48 no. 3 heroin, 46 no. 4 heroin, 47 nomophobia, 15 Norton, Michael, 173 O’Brien, Conan, 84, 243 obsession, 20–21 obsessive passion, 21–22 Oculus VR, 140–42 Olds, James, 52–57, 58, 67 O’Neill, Essena, 220–21 online shopping, 4 on-the-job training, gamification of, 308–9 opium, 31 optimal distinctiveness, 226 origami, 173–74 overcoming addictive behaviors, 263–92 behavioral architecture and, 273–92 distraction and, 267–73 habits and, 268–73 replacing bad routines with good, 268–71 subconscious attraction to ideas railed against and, 264–65 willpower, role of, 265–66 overworking, 186–88 pain, and gamification, 309–10 Pajitnov, Alexey, 170, 171, 172, 173 Parkinson’s disease patients behavioral addictions as side effect of drug treatments for, 82–85 overcoming small hurdles and, 93–95 Paskin, Willa, 212 passion, 21 Patrick, Vanessa, 272 Pavlok, 279–81 Peele, Stanton, 76, 77–79, 88 Pelling, Nick, 298, 306 Pemberton, John, 36–38, 273 Penfield, Wilder, 19 Penn, Hugh, 46 penny auction websites, 152–55 Peretz, Jeff, 194–94 perfectionism, 107–9 Perry, Steve, 202, 203 Petrie, Ryan, 226–27 Pettijohn, Adrienne, 103 Pfizer, 301–2 Phelps, Andy, 305 Philips Sonicare, 300 pineal gland, 69–70 Pinterest, 122 pituri plant, 31 planning fallacy, 289–90 “pleasure center” of brain, 55 points, 298, 299 Pokémon (game), 155 Pokhilko, Vladimir, 170 Polk, Sam, 118–19 Polkus, Laura, 216 Pommerening, Katherine, 41–42 Popular Science, 17 pornography, 4, 265–66 post-play, 208, 210–12 post traumatic stress disorder (PTSD), gamification as intervention for, 311–12 Powell, Mike, 100 Power of Habit, The (Duhigg), 268 Prelec, Dražen, 188 predatory video games, 155–59 Press Your Luck (TV show), 101–5 progress, 147–66 barriers to entry, lack of, 161–64 beginner’s luck and, 159–62 Dollar Auction Game, trap in, 149–52 energy systems, use of, 155–57 hooks in games and, 149–55 penny auction websites and, 152–55 positive feedback and, 158–59 smartphone delivery of games and, 164–66 proximity of temptation, 273–77 psychological response to experience of addiction, 73–75, 77–79 Pullen, John Patrick, 8 punding behaviors, 81–82 punishment, in breaking habits, 278–81 PurseForum, 207 Quest to Learn (Q2L), 302–4 Quibids.com, 152 Radiohead, 195 Rae, Cosette, 178–79, 249, 274 Raising Men Lawn Care, 307–8 rat experiments, of Olds and Milner, 52–57 readiness ruler, 259 Realism, 269–70 real-life crime documentaries, 196–201 Reddit, 122–25 red light, 69 regrams, 217 reinforcing good behaviors, 282–84 relational spending, 284 repression, 264 reSTART, 17–18, 62–63, 178, 228, 248–50, 255 reward, of habits, 268–69 Ricciardi, Laura, 199 Rift (game), 140–42 Robins, Lee, 50–52, 60, 67 Rochester School of Technology Just Press Play program, 304–5 Rolling Stone, 196 routine, of habits, 268–69 Routtenberg, Aryeh, 56–59 Rustichini, Aldo, 315 Ryan, Maureen, 203 Rylander, Gösta, 81, 84 Sacca, Chris, 140 Sales, Nancy Jo, 41–42 Saltsman, Adam, 155–56, 163–64 SAT vocabulary learning, gamification of, 296–97 Schachter, Stanley, 275–76 Schreiber, Katherine, 112–13, 115, 185 Schüll, Natasha Dow, 130, 134–35, 155, 183 Science, 168 Sedaris, David, 113–14 Self-Determination Theory (SDT), 260–62 “September” (Earth, Wind & Fire), 194–95, 196 Serial (podcast), 196–99, 200, 203, 204 Sesame Street (TV show), 247 Sethi, Maneesh, 279, 280–81 sexuality, 264–65 Shlam, Shosh, 252 shopping, compulsive, 205–8 Shubik, Martin, 149–51 Sign of the Zodiac (game), 130, 131 Sim, Leslie, 112–13, 114–15, 185–86 Simester, Duncan, 188 Simmons, Bill, 140 Simpsons, The (TV show), 145–46 Singer, Robert, 264 SiteJabber.com, 154 Sitzmann, Traci, 308–9 sleep deprivation, 68–70 Sleep Revolution, The (Huffington), 68–69 slot machines, 130–36, 183 smartphone addiction, 22 disruptive nature of, 15–16 overuse of, 13–15 Realism as treatment for, 269–70 scope of, 27–28 video games and, 164–66 smart watches, 113 Smith, Rodney, Jr., 307 Smith, Sandra, 112 SnowWorld, 309–10 SnŪzNLŪz, 278 social comparison, 118–19 social confirmation, 224–25 social interaction, 214–33 extensive online interactions at young ages, long-term effect of, 228–33 Hot or Not website and, 221–26 Instagram and, 216–17, 218 in multiuser games, 227–28 negative feedback in, 219–21 optimal distinctiveness and, 226 positive feedback in, 218–19 social confirmation and, 224–25 Sopranos, The (TV show), 201–3, 204 Space Invaders (game), 148 Spark Joy (Kondo), 208 Sperry, Roger, 19 SpongeBob SquarePants (TV show), 247 Steele, Robert, 48 Steiner-Adair, Catherine, 39, 41, 250–51 Stephen, Christian, 141 stereotypies, 84 Stern, Rick, 103 stopping rules, disruption of, 184–90 butt-brush effect and, 184 credit cards and, 188 exercise and, 185–86 overworking and, 186–88 video games and, 188–89 streaks, 115–16, 117 Strumsky, Dawn, 115 Strumsky, John, 115, 116 substance addiction, 8–9, 29–39 blurring of line behavioral addiction and, 81, 82–85 brain patterns and, 70–71 in early civilizations, 30–31 Freud’s research and experiments with cocaine and, 33–36 manufacturing process and, 31–32 Pemberton’s French Wine Coca (Coca-Cola) and, 37–38 punding behaviors and, 81–82 trial and error, discovery of drug effects by, 32 of Vietnam War veterans, 46–52 Sullivan, Roy, 111 Super Hexagon (game), 179–81 Super Mario Bros.


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Effective Programming: More Than Writing Code by Jeff Atwood

AltaVista, Amazon Web Services, barriers to entry, cloud computing, endowment effect, Firefox, future of work, game design, Google Chrome, gravity well, job satisfaction, Khan Academy, Kickstarter, loss aversion, Marc Andreessen, Mark Zuckerberg, Merlin Mann, Minecraft, Paul Buchheit, Paul Graham, price anchoring, race to the bottom, recommendation engine, science of happiness, Skype, social software, Steve Jobs, web application, Y Combinator, zero-sum game

But when a truffle was $0.14 and a kiss was free, 69 percent chose the kiss and 31 percent the truffle. According to standard economic theory, the price reduction shouldn’t have led to any behavior change, but it did. Ariely’s theory is that for normal transactions, we consider both upside and downside. But when something is free, we forget about the downside. “Free” makes us perceive what is being offered as immensely more valuable than it really is. Humans are loss-averse; when considering a normal purchase, loss-aversion comes into play. But when an item is free, there is no visible possibility of loss. You will tend to overestimate the value of items you get for free. Resist this by viewing free stuff skeptically rather than welcoming it with open arms. If it was really that great, why would it be free? Free stuff often comes with well hidden and subtle strings attached. How will using a free service or obtaining a free item influence your future choices?

Break up large purchases, when possible, into smaller ones over time so that you can savor the entire experience. When it comes to happiness, frequency is more important than intensity. Embrace the idea that lots of small, pleasurable purchases are actually more effective than a single giant one. 4. Buy less insurance Humans adapt readily to both positive and negative change. Extended warranties and insurance prey on your impulse for loss aversion, but because we are so adaptable, people experience far less regret than they anticipate when their purchases don’t work out. Furthermore, having the easy “out” of insurance or a generous return policy can paradoxically lead to even more angst and unhappiness because people deprived themselves of the emotional benefit of full commitment. Thus, avoid buying insurance, and don’t seek out generous return policies. 5.


pages: 121 words: 31,813

The Art of Execution: How the World's Best Investors Get It Wrong and Still Make Millions by Lee Freeman-Shor

Black Swan, buy and hold, cognitive bias, collapse of Lehman Brothers, credit crunch, Daniel Kahneman / Amos Tversky, diversified portfolio, family office, I think there is a world market for maybe five computers, index fund, Isaac Newton, Jeff Bezos, Long Term Capital Management, loss aversion, Richard Thaler, Robert Shiller, Robert Shiller, rolodex, Skype, South Sea Bubble, Stanford marshmallow experiment, Steve Jobs, technology bubble, The Wisdom of Crowds, too big to fail, tulip mania, zero-sum game

“In the morning, when temptation is remote, we vow to go to bed early, stick to our diet, and not to have too much to drink. That night we stay out until 3:00am, have two helpings of chocolate decadence, and a variety of Aquavit at a Norwegian restaurant.”37 4. Fear The research of Shlomo Benartzi and Richard Thaler also showed that the pain of a short-term loss overpowers the pleasure of a long-term gain. This myopic (short-term) focus and a hatred of losing they called myopic loss aversion.38 This produces a fear which turns many investors into Raiders when a share starts doing well. The findings of Terrance Odean suggest that this problem has grown thanks to the unprecedented immediacy of the internet. He discovered that people who traded via telephone from 1991 to 1996 outperformed the market by 2.4% per year on average. However, when they changed to trading online they underperformed the market by 3.5% per year.39 Incidentally, Odean also found that stocks investors switch into after selling winners tend to underperform the old ones by 2.3%.40 Investors think they are getting rid of weak winners and replacing them with stronger ones, but in fact they are usually doing the opposite. 5.

Many managers, once they’re up 30 or 40 percent, will book their year … The way to attain truly superior long-term returns is to grind it out until you’re up 30 or 40 percent, and then if you have the convictions, go for a 100 percent year.”60 * * * 34 Lynch (2000). 35 Ibid. 36 ‘Some Empirical Evidence on Dynamic Inconsistency’, Economic Letters, by Richard Thaler (1981). 37 ‘Anomalies: Intertemporal Choice’, Journal of Economic Perspectives, George Loewenstein and Richard H. Thaler (1989). 38 ‘Risk Aversion or Myopia? Choices in Repeated Gambles and Retirement Investments’, Management Science, by Shlomo Benartzi and Richard Thaler (1999). They showed that the pain of a short-term loss overpowers the pleasure of a long-term gain. This myopic (short-term) focus and a hatred of losing is what Thaler and Benartzi called myopic loss aversion. 39 ‘Online Investors: Do the Slow Die First?, EFA, by Brad Barber and Terrance Odean (1999). 40 ‘Trading is hazardous to your wealth: the common stock investment performance of individual investors’, The Journal of Finance, by Brad Barber and Terrance Odean (2000). 41 Kahneman and Tversky (1979). 42 ‘Focusing on the Forgone: How Value Can Appear So Different to Buyers and Sellers’, Journal of Consumer Research, by Ziv Carmon and Dan Ariely (2000). 43 The Psychology of Finance, by Lars Tvede (1999). 44 More Than You Know, by Michael Mauboussin (2006). 45 Mauboussin (2006). 46 Mean Genes, by Terry Burnham and Jay Phelan (2001). 47 Lynch (2000). 48 Thaler and Johnson (1990). 49 ‘Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency’, Journal of Finance, by Narasimhan Jegadeesh and Sheridan Titman (1993). 50 ‘Do Stock Prices Move Too Much to Be Justified by Subsequent Changes in Dividends?’


pages: 387 words: 110,820

Cheap: The High Cost of Discount Culture by Ellen Ruppel Shell

barriers to entry, Berlin Wall, big-box store, business cycle, cognitive dissonance, computer age, creative destruction, Daniel Kahneman / Amos Tversky, delayed gratification, deskilling, Donald Trump, Edward Glaeser, fear of failure, Ford paid five dollars a day, Frederick Winslow Taylor, George Akerlof, global supply chain, global village, Howard Zinn, income inequality, interchangeable parts, inventory management, invisible hand, James Watt: steam engine, Joseph Schumpeter, Just-in-time delivery, knowledge economy, loss aversion, market design, means of production, mental accounting, Monkeys Reject Unequal Pay, Pearl River Delta, Ponzi scheme, price anchoring, price discrimination, race to the bottom, Richard Thaler, Ronald Reagan, side project, Steve Jobs, The Market for Lemons, The Wealth of Nations by Adam Smith, Thomas L Friedman, trade liberalization, traveling salesman, ultimatum game, Victor Gruen, washing machines reduced drudgery, working poor, yield management, zero-sum game

Confronted with a scowling enemy or a growling beast, those who hesitated were almost certainly lost. But in the modern world these cognitive shortcuts sometimes lead us astray. When it comes to money, focusing too hard on scowls and growls can cause us to act in a way that seems irrational and can ultimately harm rather than help us. As illustration of this, Kahneman and Tversky evoked the universal phenomenon of loss aversion, the tendency of most people to strongly prefer avoiding losses rather than acquiring gains. At first blush this sounds counterintuitive. Doesn’t everyone want to win? The answer, of course, is yes, but not as much as we don’t want to lose. If you don’t play, you can’t win, but you also can’t lose. And that’s the reason so many of us decline to play when we should. Not playing results in lost opportunities, but scientists have shown that humans are not wired to spontaneously factor in missed opportunities, particularly when those opportunities are projected far into the future.

Not playing results in lost opportunities, but scientists have shown that humans are not wired to spontaneously factor in missed opportunities, particularly when those opportunities are projected far into the future. We are wired, however, to worry a good deal about losing. And when it comes to feelings of loss, it is not necessarily the actual loss but the perception of loss that keeps us from acting in what would seem to be a rational manner. Loss aversion is what spurs a scorned lover to cling to a bad relationship, an unhappy worker to cling to a bad job, and unhappy stockholders to cling to a plummeting stock rather than sell the loser and invest the proceeds in something more promising. In the latter case, the only logical reason to hold a stock is that you believe it is likely to grow in value. But because of our reluctance to admit mistakes and to cleave to what we already own, many of us prefer to avoid facing that central issue.

Kresge Company Kristof, Nicholas Kroger Supermarkets Krummeck, Elsie labor arbitrage labor exploitation in China, worldwide effects of labor movement labor unions Landsman, Janet Lasch, Christopher Lawrence, Robert Lawrie, George lean-retailing techniques Leonhardt, David Les Halles Levi Strauss Levitt, Alfred Levitt, William Levitt and Sons Levy, Leon Lichtenstein, Donald Lichtenstein, Nelson The Limited Lindell, Jens Lindgren, Charlotte Linnaeus, Carl livestock industry Locke, Richard Long, Huey P. Lord & Taylor Los Angeles Times loss aversion loss leaders Lowenstein, George Lowe’s Lundgren, Gillis luxury goods LVMH Macy’s Madoff, Michael mail-in rebates mail-order business mainstream retailers discount sections in markdowns by, growth of malls Gruen’s architectural designs improving patron satisfaction with mall attributes outlet (See outlet malls) Malmendier, Ulrike Mammoth Mart mangrove forest, shrimp farming’s impact on Mankiw, Gregory Mansfield, Jayne manual labor manufacturer’s suggested price (MSP) markdown money markdowns free of imported goods by mainstream retailers optimization of seasonal variations setting amount of types of market value Marshall Field’s mass production adoption of European-style techniques and clothing market cotton gin Ford’s assembly line gun manufacture home construction Matlock, Larry Mattel mattress industry maximum price regulations, during World War II, Maxwell, Sarah May Department Stores McDonald, David McDonald’s McGovern, Charles McKinley, William McNair, Malcolm P.


pages: 254 words: 72,929

The Age of the Infovore: Succeeding in the Information Economy by Tyler Cowen

Albert Einstein, Asperger Syndrome, business cycle, Cass Sunstein, cognitive bias, David Brooks, en.wikipedia.org, endowment effect, Flynn Effect, framing effect, Google Earth, impulse control, informal economy, Isaac Newton, loss aversion, Marshall McLuhan, Naomi Klein, neurotypical, new economy, Nicholas Carr, pattern recognition, phenotype, placebo effect, Richard Thaler, selection bias, Silicon Valley, social intelligence, the medium is the message, The Wealth of Nations by Adam Smith, theory of mind

The economically correct answer is to view the two sure outcomes as equal in comparing them to the series of risks. But in the laboratory subjects typically are more averse to the prospect framed in terms of a loss (“loss aversion”). More specifically, once the outcome is framed in terms of a loss, people will accept greater gambles to try to avoid any loss at all, compared to the risks they will take when the position is framed in terms of gains. In the study, the autistic subjects did significantly better at seeing that the talk of “loss” and “gain” was mere framing and that the two options should be treated the same, although they too showed some degree of loss aversion. Skin conductance tests run during the experiment indicated that the autistics reacted less emotionally to framing the one option in terms of loss rather than gain. In other words, the mere fact that a material resource is viewed as “theirs” seems to bias autistics less than it does non-autistics.

., 195 Joyce, James, 166 Kant, Immanuel, 203–4 Keillor, Frank, 103 Kendall, Joshua, 29 Kidmondo, 9 Kindle, 43, 62 Klein, Naomi, 198 Knecht, Joseph (fictional character), 160–66 Krugman, Paul, 111–12 Lamoureux, Hugo, 190 late-talking children, 26 Laurie, Hugh, 154 least-common-denominator effect, 134 libraries, 43 Lil’Grams, 9 LinkedIn, 83 literature, 139, 146, 147–48, 170–71. See also Holmes, Sherlock LiveJournal discussion group, 35 Living to Tell the Tale (Márquez), 120 local processing or perception, 18, 19, 36 Locke, John, 177, 204 The Lord of the Rings (Tolkien), 127 loss aversion, 196 lunch, duration of, 43 Mackenzie, Henry, 168 macroeconomics, 138 magazines, 44 manipulation, 139–41 Mankiw, Greg, 111–12, 114 mantras, 95 The Man Who Made Lists (Kendall), 29 Marginal Revolution blog, 1 market economy, 201 Márquez, Gabriel García, 120 marriage, 217–18 Marx, Karl, 216 mathematics, 19, 24, 153 Maxim, 44 McLuhan, Marshall, 65–66 media coverage, 34, 135–36 meditation, 94–95, 96 meetways.com, 131 Mehrling, Perry, 96–97 Melville, Herman, 166 memory, 18, 130, 195 Mendel, Gregor, 25, 166 mental ordering.


pages: 245 words: 72,893

How Democracy Ends by David Runciman

barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, Capital in the Twenty-First Century by Thomas Piketty, centre right, crowdsourcing, cuban missile crisis, Dominic Cummings, Donald Trump, Edward Snowden, first-past-the-post, Francis Fukuyama: the end of history, full employment, Internet of things, Joseph Schumpeter, Kickstarter, loss aversion, Mahatma Gandhi, Mark Zuckerberg, money: store of value / unit of account / medium of exchange, mutually assured destruction, Network effects, Norman Mailer, Panopticon Jeremy Bentham, Peter Thiel, quantitative easing, self-driving car, Silicon Valley, Steven Pinker, The Wisdom of Crowds, Travis Kalanick, universal basic income, Yogi Berra

When flooding or air pollution or water scarcity have become an acute threat, pragmatic authoritarianism has delivered on its promise to prioritise immediate results over long-term gains. It has much less to worry about when it comes to respecting the views of dissenters. But that is not enough to tip the balance in mature democracies. There the trade-off works the other way. Human beings tend to suffer from loss aversion: we don’t like to give up what we think is ours by right, regardless of the compensations on offer. It is very hard to imagine the citizens of Western democracies acquiescing in the loss of the personal dignity that comes with being able to kick the bastards out, even if it means bearing a collective material cost. We see plenty of evidence for this, too. Economic growth has been stagnant in much of western Europe for more than a decade.

But he argued that once it had been granted, no sane politician should ever think about taking it away: the backlash would be too terrible. The only thing worse than letting everyone vote is telling some people that they no longer qualify. Never mind who sets the exam, who is going to tell us that we’ve failed? Mill was right: democracy comes after epistocracy, not before. You can’t run the experiment in reverse. The cognitive biases that epistocracy is meant to rescue us from are what will ultimately scupper it. Loss aversion makes it more painful to be deprived of something we have that doesn’t always work than something we don’t have that might. It’s like the old joke. Q: ‘Do you know the way to Dublin?’ A: ‘Well, I wouldn’t start from here.’ How do we get to a better politics? Well, maybe we shouldn’t start from here. But here is where we are. That said, there must be other ways of trying to inject more wisdom into democratic politics than an exam.

., 87–8, 108 Khrushchev, President Nikita, 108 Kimera Systems (digital technology company), 189 Kissinger, Henry, 56, 95, 96 knowledge acquisition of, 153 and discrimination, 180 internet and, 153 political, 188–9 and power, 186–7, 204 social, 196 social scientific, 183 Krugman, Paul, 90 Kubrick, Stanley: Dr Strangelove or: How I Learned to Stop Worrying and Love the Bomb (film), 95–6, 109 L Land, Nick, 165–7 Le Pen, marine, 149 Lenin, Vladimir Ilych: The State and Revolution, 171 libertarianism, 194 Lilla, mark, 150 Limbaugh, Rush, 20 Lincoln, President Abraham, 14 Lloyd George, David, 71 Long, Huey, 49 loss aversion, 175, 188 Luttwak, Edward: Coup D’État: A Practical Handbook, 41, 44 M McCarthy, Cormac: The Road, 113, 118–19 McGinnis, Joe: The Selling of the President, 158 machines, 121–2, 125–6, 127, 196, 197, 199, 200–201, 202, 205, 219; see also artificial intelligence; computers; robots; technocracy; technology McKinley, President William, 74 Macron, President Emanuel, 148, 149–50 Man on Wire (film), 117–18 Marx, Karl: ‘The Fragment on machines’, 196–7 Marxism-Leninism, 171 Mason, Paul: Postcapitalism, 196, 197, 199, 205 Mélenchon, Jean-Luc, 58 Mencius Moldbug see Yarvin, Curtis metadata, 154 Mill, John Stuart, 182–3, 185 Miller, Stephen, 13 mindlessness, 84, 86–8 Mitchell, David: The Bone Clocks, 113 Modi, Narendra, 65–6, 149 monarchs, 167 Monsanto (company): ‘The Desolate Year’, 88 Mugabe, President Robert, 48 Mullin, Chris: A Very British Coup, 58 N NATO, 59 Nazis, 85, 97, 99 Netherlands, 148 networks and anarchism, 193 and change, 196 interconnectedness, 112–15 political movements, 149 social 136, 151, 160, 177; see also Facebook; social media; Twitter utopian, 200 see also internet New York crime, 211 World Trade Center, 117–18 New York Times, 159–60 New Yorker (magazine), 82–3, 84, 106 news, fake, 64, 75, 98, 156, 157 Nixon, President Richard, 56, 90, 158 North Korea, 213 Nozick, Robert: Anarchy, State, and Utopia, 193–4, 195 nuclear disarmament, 107 Campaign for Nuclear Disarmament (CND), 94–5 nuclear weapons, 56, 83–4, 86, 94, 95, 96–7, 102, 103–104, 106, 107 Nunn, Sam, 95 O Obama, President Barack and climate change, 92 and conspiracy theory, 64 executive initiatives, 55 and inequality, 79 and Trump’s election, 13, 14, 15, 16, 18 oil companies, 131 Orban, Viktor, 175 Osborne, George, 208 Oxford and Cambridge Review, 120 P Papademos, Lucas, 39 Papandreou, Andreas, 27 Papandreou, George, 39 paranoia, 67, 74 Parent, Joe, 62 Parfit, Derek, 100, 202–3 Paul, Rand, 154 Perry, William, 95 pesticides, 87–9 Petit, Philippe, 117–18 Piergiacomi, Alessio, 167–8 Piketty, Thomas: Capital in the Twenty-First Century, 78 Pinker, Steven: The Better Angels of our Nature, 211 Plato, 179 Poland, 65, 66 police, 171 political parties, 214 artificiality, 145–6 charisma, 147 and identity politics, 150 as machines, 127 membership, 146, 147–8 ‘Net’, 162 partisan nature, 146 ‘Pirate’, 162 United States, 146–7, 221 politicians: and trust, 144–5, 164, 214 pollution, 89, 90 populism, 13, 175 and banality, 98–9 causes of, 67 and conspiracy theory, 65–7, 72, 168 and disconnect, 141 and economic growth, 192 and inequality, 77–8 and movement politics, 148–9 United States, 67–70, 73 and war, 75 precautionary principle, 100–101 pressure groups, 89 prisons, 151, 152, 212 Putin, President Vladimir, 157 R racism, 143 Rand, Ayn, 194 rational choice theory, 108–9 referendums, 47–8, 179, 183 France, 70 Turkey, 52 United Kingdom, 48 reform, 70, 71, 78, 79, 185; see also social change revolutions, 41, 78, 196; see also digital revolution risk, 101–5, 110–12, 116 robots, 7, 103, 111, 128–9, 130, 168, 210 Rockefeller, John D., 131–2 Roosevelt, President Theodore, 70, 71, 131 Russia ‘competitive authoritarianism’, 175 Cuban missile Crisis (1962), 107–8 data harvesting, 156 foreign policy, 30 S Sacco, Justine, 143 San Francisco, 162, 163 Sandberg, Cheryl, 137 Sanders, Bernie, 58, 149 Sarandon, Susan, 198 Scarry, Elaine: Thermonuclear Monarchy: Choosing between Democracy and Doom, 104 Scheidel, Walter: The Great Leveler, 78 Schlesinger, James, 56 Schultz, George, 95 Shita, Mouna, 189–90 Simon, Herbert, 153 el-Sisi, General Abdul Fatah, 48–9 slavery, 23, 35, 73, 123–4 sleepwalking, 115, 116, 117 Snowden, Edward, 151–2 Snyder, Timothy: On Tyranny: Twenty Lessons from the Twentieth Century, 97–8, 99 social change, 192, 219; see also reform social media, 149; see also Facebook; networks: social; Twitter socialism 171 Socrates, 38 Spain, 162 Stalinism, 99, 169, 171 suffrage, universal, 187–8 Sulzberger, Cyrus, 27, 28 surveillance, 152–5 Sweden, 162, 163 T taxation, 70, 72, 193 technocracy, 180–81, 191–2, 198, 205, 214 technology, 125, 126 corporations, 131 digital, 144, 151, 154, 161, 162–3; see also internet and dignity, 203 information, 7–8 and mortality, 24–5 and risk management, 105 and ‘the shock of the old’, 122 threat of, 103, 120–21 see also machines terrorism, 74 terrorists, 97, 212 Texas, 163 Thiel, Peter, 198 tightrope-walking, 117–18 totalitarianism, 98; see also tyrannies tribalism, 163–4 Truman, President Harry S., 84–5 Trump, Melania, 13 Trump, President Donald, 49 behaviour, 20–21, 22–3, 159, 173 and change, 198 and Charlottesville demonstrations, 4 and climate change, 93 and conspiracy theory, 64–5 and dignity, 173 election of, 1–2, 5, 13, 16–18, 19, 20, 25, 118, 149, 156 and executive aggrandisement, 92 and fake news, 157 inaugural speech, 11–14, 74 military’s influence on, 59 novels inspired by, 57 and nuclear war, 86 and political violence, 212 presidency, 213 and Silicon Valley firms, 137 supporters of, 98 on surveillance, 154 use of Twitter, 143 Tsipras, Alexis, 33–4, 209 Turkey, 50–3 conspiracy theories, 65, 66 coups, 50–2, 53, 66 and Cyprus, 38 elections, 51 Justice and Development Party (AKP), 51 movement politics, 149 referendum (2017), 52 Twitter, 65, 137, 142, 143, 156 tyrannies 61; see also totalitarianism U United Kingdom austerity, 208 Boer War, 75 Brexit, 48, 156, 179 Campaign for Nuclear Disarmament (CND), 94–5 Conservative Party, 146, 209 general election (2017), 95 Labour Party, 58, 70, 94–5, 148–9, 150 metadata, 154 political enfranchisement, 76 reform, 185 welfare state, 76 United States, 23–4, 25, 49–50 CIA, 28, 30 climate change, 92 Congress, 19 conspiracy theories, 62, 67 corporations, 132 Cuban missile Crisis (1962), 107–8 democratic failure, 2, 14 demonstrations, 4 direct democracy, 163 economic growth, 175 and Egypt compared, 49–50 environment, 87–90 and Greece, 30 immigration, 183 inequality, 79 judiciary, 19 McCarthyism, 67 metadata, 154 military, 17, 18 National Security Agency (NSA), 152 New Deal, 76, 78 and nuclear war, 86, 95 ‘pax Americana’, 198 pesticides, 87–9 political enfranchisement, 76 political parties Democrats, 15, 62, 64, 108, 146–7, 221 Republicans, 62, 146–7, 221 politicians, 164 populism, 67–70, 73 presidential elections, 14, 16, 54–5, 58, 68, 220–24 Kennedy, John F., 108 Trump, Donald, 1–2, 5, 13, 19, 20, 25, 118, 149 prisons, 212 reform, 70 rights, 72 road accidents, 211–12 Silicon Valley, 137, 204 ‘tyranny of the majority’, 142 violence, 73–4, 211–12 war with Spain (1890s), 75 see also Chicago; New York; San Francisco; Texas Uscinski, Joe, 62 utopias, 126, 194, 195, 201 V Varoufakis, Yanis, 32–4, 116–17, 209 Venezuela, 154–5, 208 violence, 6, 73–5 ancient Athens, 38 decline of, 13 and environmental disaster, 93 Greece, 31, 210 and inequality, 78–80 Japan, 210 online, 142–4 political, 16–17, 18 United States, 73–4, 211–12 voting AI and, 189–90 right to, 76, 183–4 systems, 182–3 see also elections W wars, 74–7 citizens’ experience of, 77 and conspiracy theory, 77 First World War, 76, 115 of national survival, 75 nuclear, 83–4, 84–5, 87, 93–7, 109, 213 and populism, 75 total, 76–7 United States and North Korea, 115 see also Cold War wealth: and death, 204; see also elites Weber, Max, 127, 131, 147, 164, 187–8 welfare states, 70, 76, 109–10 whistleblowers see Snowden, Edward Wilson, President Woodrow, 69, 71, 75–6 Y Yarvin, Curtis, 167 Z Zimbabwe, 48 Zuckerberg, Mark, 131, 133, 135, 137, 138, 140, 157–8, 215; see also Facebook ALSO FROM PROFILE BOOKS Political Order and Political Decay: From the Industrial Revolution to the Globalisation of Democracy Francis Fukuyama The most important book about the history and future of politics since The End of History.


pages: 336 words: 113,519

The Undoing Project: A Friendship That Changed Our Minds by Michael Lewis

Albert Einstein, availability heuristic, Cass Sunstein, choice architecture, complexity theory, Daniel Kahneman / Amos Tversky, Donald Trump, Douglas Hofstadter, endowment effect, feminist movement, framing effect, hindsight bias, John von Neumann, Kenneth Arrow, loss aversion, medical residency, Menlo Park, Murray Gell-Mann, Nate Silver, New Journalism, Paul Samuelson, Richard Thaler, Saturday Night Live, Stanford marshmallow experiment, statistical model, the new new thing, Thomas Bayes, Walter Mischel, Yom Kippur War

The two problems were identical, but, in the first case, when the choice was framed as a gain, the subjects elected to save 200 people for sure (which meant that 400 people would die for sure, though the subjects weren’t thinking of it that way). In the second case, with the choice framed as a loss, they did the reverse, and ran the risk that they’d kill everyone. People did not choose between things. They chose between descriptions of things. Economists, and anyone else who wanted to believe that human beings were rational, could rationalize, or try to rationalize, loss aversion. But how did you rationalize this? Economists assumed that you could simply measure what people wanted from what they chose. But what if what you want changes with the context in which the options are offered to you? “It was a funny point to make because the point within psychology would have been banal,” the psychologist Richard Nisbett later said. “Of course we are affected by how the decision is presented!”

“What made the theory important and what made it viable were completely different,” said Danny, years later. “Science is a conversation and you have to compete for the right to be heard. And the competition has its rules. And the rules, oddly enough, are that you are tested on formal theory.” After they finally sent a draft of their paper to the economics journal Econometrica, Danny was perplexed by the editor’s response. “I was kind of hoping he’d say, ‘Loss aversion is a really cool idea.’ He said, ‘No, I like the math.’ I was sort of shattered.” By 1976, purely for marketing purposes, they changed their title to “Prospect Theory.” “The idea was to give the theory a completely distinct name that would have no associations whatsoever,” said Danny. “When you say ‘prospect theory,’ no one knows what you’re talking about. We thought: Who knows? It may turn out to be influential.

But by then it was clear that no matter how often people trained in statistics affirmed the truth of Danny and Amos’s work, people who weren’t would insist that they knew better. * * * Upon their arrival in North America, Amos and Danny had published a flurry of papers together. Mostly it was stuff they’d had in the works when they’d left Israel. But in the early 1980s what they wrote together was not done in the same way as before. Amos wrote a piece on loss aversion under both their names, to which Danny added a few stray paragraphs. Danny wrote up on his own what Amos had called “The Undoing Project,” titled it “The Simulation Heuristic,” and published it with both their names on top, in a book that collected their articles, along with others by students and colleagues. (And then set out to explore the rules of the imagination not with Amos but with his younger colleague at the University of British Columbia, Dale Miller.)


pages: 302 words: 83,116

SuperFreakonomics by Steven D. Levitt, Stephen J. Dubner

agricultural Revolution, airport security, Andrei Shleifer, Atul Gawande, barriers to entry, Bernie Madoff, Boris Johnson, call centre, clean water, cognitive bias, collateralized debt obligation, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, deliberate practice, Did the Death of Australian Inheritance Taxes Affect Deaths, disintermediation, endowment effect, experimental economics, food miles, indoor plumbing, Intergovernmental Panel on Climate Change (IPCC), John Nash: game theory, Joseph Schumpeter, Joshua Gans and Andrew Leigh, longitudinal study, loss aversion, Louis Pasteur, market design, microcredit, Milgram experiment, oil shale / tar sands, patent troll, presumed consent, price discrimination, principal–agent problem, profit motive, randomized controlled trial, Richard Feynman, Richard Thaler, selection bias, South China Sea, Stanford prison experiment, Stephen Hawking, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, ultimatum game, urban planning, William Langewiesche, women in the workforce, young professional

In that case, you’d expect them to prefer it when a researcher initially offered them two grapes instead of one. But precisely the opposite happened! Once the monkeys figured out that the two-grape researcher sometimes withheld the second grape and that the one-grape researcher sometimes added a bonus grape, the monkeys strongly preferred the one-grape researcher. A rational monkey wouldn’t have cared, but these irrational monkeys suffered from what psychologists call “loss aversion.” They behaved as if the pain from losing a grape was greater than the pleasure from gaining one. Up to now, the monkeys appeared to be as rational as humans in their use of money. But surely this last experiment showed the vast gulf that lay between monkey and man. Or did it? The fact is that similar experiments with human beings—day traders, for instance—had found that people make the same kind of irrational decisions at a nearly identical rate.

Keith Chen and Laurie Santos, “The Evolution of Rational and Irrational Economic Behavior: Evidence and Insight from a Non-Human Primate Species,” chapter from Neuroeconomics: Decision Making and the Brain, ed. Paul Glimcher, Colin Camerer, Ernst Fehr, and Russell Poldrack (Academic Press, Elsevier, 2009). / 212 “Nobody ever saw a dog”: see Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations, ed. Edwin Cannon (University of Chicago Press, 1976; originally published in 1776). / 214 Day traders are also loss-averse: see Terrance Odean, “Are Investors Reluctant to Realize Their Losses?” Journal of Finance 53, no. 5 (October 1998). SEARCHABLE TERMS Note: Entries in this index, carried over verbatim from the print edition of this title, are unlikely to correspond to the pagination of any given e-book reader. However, entries in this index, and other terms, may be easily located by using the search feature of your e-book reader.

See Genovese, Kitty, murder of Krueger, Alan, 62, 63–64 Kyoto Protocol, 115 laboratory experiments artificiality of, 123 and crash-test data, 153–55 games as, 108–11 See also specific researcher or experiment Lake Toba (Sumatra), volcanic eruption at, 189 Lakshminarayanan, Venkat, 212 LaSheena (prostitute), 19–20, 26, 27, 30, 54 Latham, John, 201, 202 Latham, Mike, 201 law of unintended consequences, 138–41 Leave It to Beaver (TV program), 102 LeMay, Curtis, 147 Lenin, Vladimir, 63 leverage, 193 Levitt, Steven D., 17 life expectancy, 20 life insurance, 94, 200 life span, extending the, 82–87 List, John, 113–20, 121, 123, 125 locavore movement, 166 LoJack (anti-theft device), 173–75 London, England, terrorism in, 92 loss aversion, 214 Lovelock, James, 166, 170, 177 Lowell, Mike, 92 macroeconomics, 16–17, 211 Madison, Wisconsin, home-sales data in, 39 Maintenance of Parents Act, Singapore, 106 Major League Baseball, birthdays among players of, 61, 62 malaria, experiment about, 177, 180, 181 manipulation, and altruism, 125 March of Dimes, 145 marijuana, 66 Martinelli, César, 27–28 Masters, Will, 142 Matthews, H.


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Finance and the Good Society by Robert J. Shiller

Alvin Roth, bank run, banking crisis, barriers to entry, Bernie Madoff, buy and hold, capital asset pricing model, capital controls, Carmen Reinhart, Cass Sunstein, cognitive dissonance, collateralized debt obligation, collective bargaining, computer age, corporate governance, Daniel Kahneman / Amos Tversky, Deng Xiaoping, diversification, diversified portfolio, Donald Trump, Edward Glaeser, eurozone crisis, experimental economics, financial innovation, financial thriller, fixed income, full employment, fundamental attribution error, George Akerlof, income inequality, information asymmetry, invisible hand, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, land reform, loss aversion, Louis Bachelier, Mahatma Gandhi, Mark Zuckerberg, market bubble, market design, means of production, microcredit, moral hazard, mortgage debt, Myron Scholes, Nelson Mandela, Occupy movement, passive investing, Ponzi scheme, prediction markets, profit maximization, quantitative easing, random walk, regulatory arbitrage, Richard Thaler, Right to Buy, road to serfdom, Robert Shiller, Robert Shiller, Ronald Reagan, selection bias, self-driving car, shareholder value, Sharpe ratio, short selling, Simon Kuznets, Skype, Steven Pinker, telemarketer, Thales and the olive presses, Thales of Miletus, The Market for Lemons, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, Vanguard fund, young professional, zero-sum game, Zipcar

New Haven, CT: Cowles Foundation for Research in Economics, Yale University. Shleifer, Andrei. 2000. Ine cient Markets: An Introduction to Behavioral Finance. Oxford: Oxford University Press. Shubik, Martin. 2009. A Proposal for a Federal Employment Reserve Authority. Economics Policy Note 09-5. New York: Levy Economics Institute. Simmons, Joseph P., and Nathan Novemsky. 2009. “From Loss Aversion to Loss Acceptance: Context E ects on Loss Aversion in Risky Choice.” Working Paper. New Haven, CT: Yale School of Management. Small, Deborah A., George Loewenstein, and Paul Slovic. 2007. “Sympathy and Callousness: The Impact of Deliberative Thought on Donations to Identi able and Statistical Victims.” Organizational Behavior and Human Decision Processes 102(2):143– 53. Smith, Adam. 1761. The Theory of Moral Sentiments, Second Edition.

The “gaming industry,” as it styles itself, defends its activities as a form of entertainment. Certainly it is that, but it is unique among entertainment forms in that it cultivates and ampli es to a considerable extent human risk-taking impulses, sometimes with disastrous consequences. The puzzle comes down to why one would be willing to place even one single bet at a casino. Research by psychologists Daniel Kahneman and Amos Tversky has shown that people exhibit a tendency toward loss aversion.1 They are pathologically avoidant of even small losses. If o ered an asymmetrical bet on a coin toss—to win $20 if it comes up heads, to lose $10 if it comes up tails—most people will turn down the bet, even though it has a positive expected return of $5. How then are gambling casinos able to induce people to place bets with a negative expected return, and to do so again and again despite having experienced repeated losses?

See language Linnainmaa, Juhani, 31 liquidity, 40, 62, 144 livelihood insurance, 67 Liverpool School of Tropical Medicine, 126 living wages, 150 Li Zhisui, 182 loans, 38, 42, 43, 44. See also debt; mortgages Lobbying Disclosure Act of 1995, 90 lobbyists: for accountants’ groups, 102; for financial industry, 87, 88–89, 90, 92; former members of Congress, 88; gifts, 90; motives, 91; power, 87–88, 89–90, 92; public perceptions, 91; reforms, 92–93; regulation of, 88, 89–90, 92–93; roles, 87–89, 90–91 Locke, John, 145 Lorenz, Konrad, 226, 229 loss aversion, 160 lotteries, 140. See also gambling lottery-linked savings, 177 loyalty, 215 Lummis, Cynthia, 193 Luther, Martin, 141 Macmillan, Harold, 212 MacroMarkets LLC, 98 MacroShares, 98 Madoff, Bernard, 17, 95–96, 98 manics, 173 Mao Zedong, 174, 182, 233 market designers, 69–71, 73–74. See also financial engineers; financial innovations market makers, 57, 61–62. See also traders markets: efficiency, 169–70; liquidity, 62; for marriage partners, 71–74; new, 62–63, 69–71, 73–74; price discovery, 8, 132, 185; trading in, 29–30, 46; trust in, 36; valuations made by, 58–60, 63.


Innovation and Its Enemies by Calestous Juma

3D printing, additive manufacturing, agricultural Revolution, Asilomar, Asilomar Conference on Recombinant DNA, autonomous vehicles, big-box store, business cycle, Cass Sunstein, clean water, collective bargaining, colonial rule, computer age, creative destruction, Daniel Kahneman / Amos Tversky, deskilling, disruptive innovation, energy transition, Erik Brynjolfsson, financial innovation, global value chain, Honoré de Balzac, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of movable type, invention of the printing press, Joseph Schumpeter, knowledge economy, loss aversion, Marc Andreessen, means of production, Menlo Park, mobile money, New Urbanism, Nicholas Carr, pensions crisis, phenotype, Ray Kurzweil, refrigerator car, Second Machine Age, self-driving car, smart grid, smart meter, stem cell, Steve Jobs, technological singularity, The Future of Employment, Thomas Kuhn: the structure of scientific revolutions, Travis Kalanick

The first is “status quo bias” and the second is “omission bias.”93 The former describes the disproportionate tendency to stick with the status quo when choosing between alternatives.94 For example, when asked to decide whether or not to participate in an organ donation program, offering the default option “yes” on the relevant insurance forms produces much higher participation rates than offering “no” as the default option and asking people to take action through opting into the program.95 New technologies that alter not only social habits but also what is perceived to be the status quo lead to negative responses because they threaten the customs that people have grown comfortable with. Loss aversion also causes people to underestimate the risks of doing nothing and sticking with the status quo. The tendency to favor inaction over action is called omission bias. This bias prevails even when people know the outcomes of omission and commission. For example, people tend to think that it is worse to vaccinate a child when the vaccination could cause harm than not to vaccinate, even though delivering the vaccination could significantly reduce the risk of harm through disease to the overall population and probably to the individual child as well.

Thus, communication that encourages a positive cognitive approach to new technologies—for example, through emphasizing benefits of specific aspects of the technology—can increase the likelihood that people will accept the technology.100 It follows that challenges to innovation can be reduced by three psychological factors. First, new ideas are more easily adopted if they work through existing or entirely new habits rather than attempt to break existing ones. Second, framing the potential outcomes of new technologies in terms of gains or losses has a significant impact on whether loss aversion will produce risk-seeking or risk-avoiding behavior.101 Third, people are more likely to adopt a new technology when communication encourages positive attitudes toward it—for example, by emphasizing the concrete benefits of specific aspects of the technology. An equally important psychological factor in defining the challenge to new technologies is political empathy. Social movements use framing as “strategic versions of reality for mobilizing audiences, conferring meanings that include causes and solutions.”102 Political empathy not only helps social movements to focus attention on victimization but also creates a basis to mobilize support from other fields that share common concerns.

For a related study on the harassment and defamation of scientists seeking to bring research to bear on justice, see Alice Dreger, Galileo’s Middle Finger: Heretics, Activists, and the Search for Justice in Science (New York: Penguin, 2015). 17. See, for example, Michael W. Bauer, Andrew Jordan, Christoffer Green-Pedersen, and Adrienne Héritier, Dismantling Public Policy: Preferences, Strategies, and Effects (Oxford: Oxford University Press, 2012); Stegmaier, Kuhlmann, and Visser, “Discontinuation.” Chapter 1 1. Eyal Ert and Ido Erev, “On the Descriptive Value of Loss Aversion in Decisions under Risk: Six Clarifications,” Judgment and Decision Making 8, no. 3 (2013): 214–235. 2. National Academy of Engineering, Grand Challenges for Engineering (Washington, DC: NAE, 2008). 3. Graeme Laurie, Shawn Harmon, and Fabiana Arzuaga, “Foresighting Futures: Law, New Technologies, and the Challenges of Regulating for Uncertainty,” Law, Innovation and Technology 4, no. 1 (2012): 1–33. 4.


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Actionable Gamification: Beyond Points, Badges and Leaderboards by Yu-Kai Chou

Apple's 1984 Super Bowl advert, barriers to entry, bitcoin, Burning Man, Cass Sunstein, crowdsourcing, Daniel Kahneman / Amos Tversky, delayed gratification, don't be evil, en.wikipedia.org, endowment effect, Firefox, functional fixedness, game design, IKEA effect, Internet of things, Kickstarter, late fees, lifelogging, loss aversion, Maui Hawaii, Minecraft, pattern recognition, peer-to-peer, performance metric, QR code, recommendation engine, Richard Thaler, Silicon Valley, Skype, software as a service, Stanford prison experiment, Steve Jobs, The Wealth of Nations by Adam Smith, transaction costs

When the game announced that it was shutting down, players (mostly consisting of students) banded together and raised $700,000 to see if they could keep the game going. That was quite an impressive figure, mainly motivated by Core Drive 4: Ownership & Possession as well as Core Drive 8: Loss & Avoidance. In fact, in higher-level Octalysis studies, you will see that building Core Drive 4 often reinforces the power of Core Drive 8, and that the Endowment Effect connects directly to our irrational sense of Loss Aversion). Monopolizing Billions Another great example of Collection Sets is seen in McDonald’s Monopoly Game28. McDonald’s wants people to buy more fast food from them - the Desired Action, so it created the McDonald’s Monopoly game where every time you hit the Win-State of “buying more burgers and fries” you will get a piece of property on the Monopoly Board. Once you accumulate all the properties, McDonald’s will give you great cash prizes and rewards.

This is because gaining something and preventing a loss is incredibly different from the standpoint of motivation. Studies234 have shown over and over that we are much more likely to change our behavior to avoid a loss than to make a gain. It forces us to act differently and plays by different mental rules. In fact, Nobel Prize winner Daniel Kahneman indicates that on average, we are twice as loss-averse compared to seeking a gain5. This means that we have a tendency to only take on a risk if we believed the potential gain would be double the potential loss if the risk were realized. Through using the Octalysis Framework, this differentiation improves behavioral design by specifically identifying opportunities to integrate proactive loss-avoidance mechanics that generate a more suble set of motivational dynamics.

Have you ever been on a website, where you click around before you stumble upon the conversion page (“sign-up” or “purchase”), and then see some offer that reads, “Purchase now and instantly get a 20% discount!” or “Sign-up now to receive 3000 free credits”? Often, we dismiss these offers as gimmicky, and a poor appeal to Core Drive 4: Ownership & Possession, so we ignore them. However, some sites integrate game techniques into the experience by harnessing our loss aversion tendencies. Imagine as you click around a website, there is a little popup widget that says, “Great! Your actions have earned you 500 credits!” As you click on more places, it will continue to say, “Great! Your actions have earned you 1500 credits!” Finally, when you get onto the landing page, the text reads, “You now have 3000 credits. Sign-up to save your credits for later!” Even though this is the exact same result as “Sign-up now to receive 3000 free credits,” the experience design makes signing up feel more compelling.


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The End of Jobs: Money, Meaning and Freedom Without the 9-To-5 by Taylor Pearson

"side hustle", Airbnb, barriers to entry, Ben Horowitz, Black Swan, call centre, cloud computing, commoditize, creative destruction, David Heinemeier Hansson, Elon Musk, en.wikipedia.org, Frederick Winslow Taylor, future of work, Google Hangouts, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, loss aversion, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, market fragmentation, means of production, Oculus Rift, passive income, passive investing, Peter Thiel, remote working, Ronald Reagan: Tear down this wall, sharing economy, side project, Silicon Valley, Skype, software as a service, software is eating the world, Startup school, Steve Jobs, Steve Wozniak, Stewart Brand, telemarketer, Thomas Malthus, Uber and Lyft, uber lyft, unpaid internship, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog

Your status was lowered in the tribe for the rest of your life; you might never find a mate, reproduce, and pass on your genes. This principle is called loss aversion: when directly compared to each other, losses loom larger than gains. Consider: You are offered a gamble on the toss of a coin. Heads, you win $150. Tails, you lose $100. How do you feel about it? Although the expected value is obviously positive (if you repeated the bet 100 times, you’d almost certainly come out on top), most people decline the bet. When asked: “What is the smallest gain that you need to balance an equal chance to lose $100?” most people answer $200—twice as much as the loss.28 The ratio of loss aversion has been measured at between 1.5 and 2.5, meaning people typically want to see a 150–250% expected return to make the bet. This, again, is a mentality from our evolutionary past.


pages: 368 words: 96,825

Bold: How to Go Big, Create Wealth and Impact the World by Peter H. Diamandis, Steven Kotler

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Charles Lindbergh, cloud computing, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, dematerialisation, deskilling, disruptive innovation, Elon Musk, en.wikipedia.org, Exxon Valdez, fear of failure, Firefox, Galaxy Zoo, Google Glasses, Google Hangouts, gravity well, ImageNet competition, industrial robot, Internet of things, Jeff Bezos, John Harrison: Longitude, John Markoff, Jono Bacon, Just-in-time delivery, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loss aversion, Louis Pasteur, low earth orbit, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mars Rover, meta analysis, meta-analysis, microbiome, minimum viable product, move fast and break things, Narrative Science, Netflix Prize, Network effects, Oculus Rift, optical character recognition, packet switching, PageRank, pattern recognition, performance metric, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, Ray Kurzweil, recommendation engine, Richard Feynman, ride hailing / ride sharing, risk tolerance, rolodex, self-driving car, sentiment analysis, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart grid, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, superconnector, technoutopianism, telepresence, telepresence robot, Turing test, urban renewal, web application, X Prize, Y Combinator, zero-sum game

Sometimes this is correct, but sometimes this will take you right off a cliff. Thinking in first principles protects you from these errors.” When it comes to scale, these aren’t the only errors one must guard against. Daniel Kahneman and Amos Tversky won the Nobel Prize for their work on human irrationality. One great example of this is what happens when two of the most common cognitive biases—loss aversion and narrow framing—begin to overlap. Loss aversion is the idea that humans are more sensitive to losses—even small losses—than gains, while narrow framing is our tendency to treat every risk we encounter as an isolated incident. In combination, what this means is when we go to assess risk, we tend not to look at the entire picture. In an interview with Big Think, Kahneman explained it like this:12 People tend to frame things very narrowly.

., 27 LIDAR, 43–44, 44 life-extension projects, 66, 81 Li’l Abner (comic strip), 71 Lincoln, Abraham, 109, 194 Lindbergh, Charles, 112, 244, 245, 259–60 linear growth, 7, 9 linear industries, 38, 116 exponential technologies in disrupting of, 17, 18–22 linear organizations, 15, 17, 18, 19, 20, 21, 76, 85, 116 LinkedIn, 77, 213, 231 Lintott, Chris, 220 Linux, 11, 163 Littler Workplace Policy Institute, 60 live-streaming, in crowdsourcing campaigns, 207 Lloyd, Gareth, 4 Local Motors, 33, 217, 223–25, 231, 238, 240, 241 Locke, Edwin, 23, 74, 75, 103 Lockheed, 71–72, 75 Lockheed Martin, 249 Longitude Prize, 245, 247, 267 long-term thinking, 116, 128, 130–31, 132–33, 138 Los Angeles, Calif., 258 loss aversion, 121 Louis Pasteur Université, 104 Lovins, Amory, 222 MacCready, Paul, 263 McDowell, Mike, 291n machine learning, 54–55, 58, 66, 85, 137, 167, 216 see also artificial intelligence (AI) Macintosh computer, 72 McKinsey & Company, 245 McLucas, John, 102 Macondo Prospect, 250 macrotasks, crowdsourcing of, 156, 157–58 Made in Space, 36–37 Made to Stick: Why Some Ideas Survive and Others Die (Heath and Heath), 248 MakerBot printers, 39 Makers (Doctorow), 38 MakieLabs, 39 manufacturing, 33, 41 biological, 63–64 digital, 33 in DIY communities, 223–25 robotics in, 62 subtractive vs. additive, 29–30, 31 3–D printing’s impact on, 30, 31, 34–35 Marines, US, 222 Markoff, John, 56 Mars missions, 99, 118–19, 128 Mars Oasis project, 118 Maryland, University of, 74 Maryniak, Gregg, 244 Mashable, 238 massively transformative purpose (MTP), 215, 221, 230, 231, 233, 240, 242, 274 in incentive competitions, 249, 255, 263, 265, 270 mastery, 79, 80, 85, 87, 92 materials, in crowdfunding campaigns, 195 Maven Research, 145 Maxwell, John, 114n Mead, Margaret, 247 Mechanical Turk, 157 meet-ups, 237 Menlo Ventures, 174 message boards, 164 Mexican entrepreneurs, 257–58 Michigan, University of, 135, 136 microfactories, 224, 225 microlending, 172 microprocessors, 49, 49 Microsoft, 47, 50, 99 Microsoft Windows, 27 Microsoft Word, 11 microtasks, crowdsourcing of, 156–57, 166 Mightybell, 217, 233 Migicovsky, Eric, 175–78, 186, 191, 193, 198, 199, 200, 206, 209 Millington, Richard, 233 Mims, Christopher, 290n MIT, 27, 60, 100, 101, 103, 291n mobile devices, 14, 42, 42, 46, 46, 47, 49, 124, 125, 135, 146, 163, 176 see also smartphones Modernizing Medicine, 57 monetization: in incentive competitions, 263 of online communities, 241–42 Montessori education, 89 moonshot goals, 81–83, 93, 98, 103, 104, 110, 245, 248 Moore, Gordon, 7 Moore’s Law, 6–7, 9, 12, 31, 64 Mophie, 18 moral leadership, 274–76 Morgan Stanley, 122, 132 Mosaic, 27, 32, 33, 57 motivation, science of, 78–80, 85, 87, 92, 103 incentive competitions and, 148, 254, 255, 262–63 Murphy’s Law, 107–8 Museum of Flight (Seattle), 205 music industry, 11, 20, 124, 125, 127, 161 Musk, Elon, xiii, 73, 97, 111, 115, 117–23, 128, 134, 138, 139, 167, 223 thinking-at-scale strategies of, 119–23, 127 Mycoskie, Blake, 80 Mycroft, Frank, 180 MySQL, 163 Napoléon I, Emperor of France, 245 Napster, 11 Narrative Science, 56 narrow framing, 121 NASA, 96, 97, 100, 102, 110, 123, 221, 228, 244 Ames Research Center of, 58 Jet Propulsion Laboratory (JPL) of, 99 Mars missions of, 99, 118 National Collegiate Athletic Association (NCAA), 226 National Institutes of Health, 64, 227 National Press Club, 251 navigation, in online communities, 232 Navteq, 47 Navy Department, US, 72 NEAR Shoemaker mission, 97 Netflix, 254, 255 Netflix Prize, 254–56 Netscape, 117, 143 networks and sensors, x, 14, 21, 24, 41–48, 42, 45, 46, 66, 275 information garnered by, 42–43, 44, 47, 256 in robotics, 60, 61 newcomer rituals, 234 Newman, Tom, 268 New York Times, xii, 56, 108, 133, 145, 150, 155, 220 Nickell, Jake, 143, 144 99designs, 145, 158, 166, 195 Nivi, Babak, 174 Nokia, 47 Nordstrom, 72 Nye, Bill, 180, 200, 207 “Oatmeal, the” (web comic), 178, 179, 193, 196, 200 Oculus Rift, 182 O’Dell, Jolie, 238–39 oil-cleanup projects, 247, 250–53, 262, 263, 264 Olguin, Carlos, 65 1Qbit, 59 operational assets, crowdsourcing of, 158–60 Orteig Prize, 244, 245, 259, 260, 263 Oxford Martin School, 62 Page, Carl, 135 Page, Gloria, 135 Page, Larry, xiii, 53, 74, 81, 84, 99, 100, 115, 126, 128, 134–39, 146 thinking-at-scale strategies of, 136–38 PageRank algorithm, 135 parabolic flights, 110–12, 123 Paramount Pictures, 151 Parliament, British, 245 passion, importance of, 106–7, 113, 116, 119–20, 122, 125, 134, 174, 180, 183, 184, 248, 249 in online communities, 224, 225, 228, 231, 258 PayPal, 97, 117–18, 167, 201 PC Tools, 150 Pebble Watch campaign, 174, 175–78, 179, 182, 186, 187, 191, 200, 206, 208, 209, 210 pitch video in, 177, 198, 199 peer-to-peer (P2P) lending, 172 Pelton, Joseph, 102 personal computers (PCs), 26, 76 Peter’s Laws, 108–14 PHD Comics, 200 philanthropic prizes, 267 photography, 3–6, 10, 15 demonetization of, 12, 15 see also digital cameras; Kodak Corporation Pink, Daniel, 79 Pishevar, Shervin, 174 pitch videos, 177, 180, 192, 193, 195, 198–99, 203, 212 Pivot Power, 19 Pixar, 89, 111 Planetary Resources, Inc., 34, 95, 96, 99, 109, 172, 175, 179, 180, 186, 189–90, 193, 195, 201–3, 221, 228, 230 Planetary Society, 190, 200 Planetary Vanguards, 180, 201–3, 212, 230 PlanetLabs, 286n +Pool, 171 Polaroid, 5 Polymath Project, 145 Potter, Gavin, 255–56 premium memberships, 242 PricewaterhouseCoopers, 146 Prime Movers, The (Locke), 23 Princeton University, 128–29, 222 Prius, 221 probabilistic thinking, 116, 121–22, 129 process optimization, 48 Project Cyborg, 65 psychological tools, of entrepreneurs, 67, 115, 274 goal setting in, 74–75, 78, 79, 80, 82–83, 84, 85, 87, 89–90, 92, 93, 103–4, 112, 137, 185–87 importance of, 73 line of super-credibility and, 96, 98–99, 98, 100, 101–2, 107, 190, 203, 266, 272 passion as important in, 106–7, 113, 116, 119–20, 122, 125, 134, 174, 249, 258 Peter’s Laws in, 108–14 and power of constraints, 248–49 rapid iteration and, 76, 77, 78, 79–80, 83–84, 85, 86, 120, 126, 133–34, 236 risk management and, see risk management science of motivation and, 78–80, 85, 87, 92, 103, 254, 255 in skunk methodology, 71–87, 88; see also skunk methodology staging of bold ideas and, 103–4, 107 for thinking at scale, see scale, thinking at triggering flow and, 85–94, 109 public relations managers, in crowdfunding campaigns, 193–94 purpose, 79, 85, 87, 116, 119–20 in DIY communities, see massively transformative purpose (MTP) Qualcomm Tricorder XPRIZE, 253 Quirky, 18–20, 21, 66, 161 Rackspace, 50, 257 Rally Fighter, 224, 225 rapid iteration, 76, 77, 78, 79–80, 83–84, 85, 86, 236 feedback loops in, 77, 83, 84, 86, 87, 90–91, 92, 120 in thinking at scale, 116, 126, 133–34 rating systems, 226, 232, 236–37, 240 rationally optimistic thinking, 116, 136–37 Ravikant, Naval, 174 Raytheon, 72 re:Invent 2012, 76–77 reCAPTCHA, 154–55, 156, 157 registration, in online communities, 232 Reichental, Avi, 30–32, 35 Rensselaer Polytechnic Institute, 4 reputation economics, 217–19, 230, 232, 236–37 Ressi, Adeo, 118 ReverbNation, 161 reward-based crowdfunding, 173, 174–80, 183, 185, 186–87, 195, 205, 207 case studies in, 174–80 designing right incentives for affiliates in, 200 early donor engagement in, 203–5 fundraising targets in, 186–87, 191 setting of incentives in, 189–91, 189 telling meaningful story in, 196–98 trend surfing in, 208 upselling in, 207, 208–9 see also crowdfunding, crowdfunding campaigns rewards, extrinsic vs. intrinsic, 78–79 Rhodin, Michael, 56 Richards, Bob, 100, 101–2, 103, 104 Ridley, Matt, 137 risk management, 76–77, 82, 83, 84, 86, 103, 109, 116, 121 Branson’s strategies for, 126–27 flow and, 87, 88, 92, 93 incentive competitions and, 247, 248–49, 261, 270 in thinking at scale, 116, 121–22, 126–27, 137 Robinson, Mark, 144 Robot Garden, 62 robotics, x, 22, 24, 35, 41, 59–62, 63, 66, 81, 135, 139 entrepreneurial opportunities in, 60, 61, 62 user interfaces in, 60–61 Robot Launchpad, 62 RocketHub, 173, 175, 184 Rogers, John “Jay,” 33, 38, 222–25, 231, 238, 240 Roomba, 60, 66 Rose, Geordie, 58 Rose, Kevin, 120 Rosedale, Philip, 144 Russian Federal Space Agency, 102 Rutan, Burt, 76, 96, 112, 127, 269 San Antonio Mix Challenge, 257–58 Sandberg, Sheryl, 217, 237 Santo Domingo, Dominican Republic, 3 Sasson, Steven, 4–5, 5, 6, 9 satellite technology, 14, 36–37, 44, 100, 127, 275, 286n scale, thinking at, xiii, 20–21, 116, 119, 125–28, 148, 225, 228, 243, 257 Bezos’s strategies for, 128, 129, 130–33 Branson’s strategies for, 125–27 in building online communities, 232–33 customer-centric approach in, 116, 126, 128, 130, 131–32, 133 first principles in, 116, 120–21, 122, 126, 138 long-term thinking and, 116, 128, 130–31, 132–33, 138 Musk’s strategies for, 119–23, 127 Page’s strategies for, 136–38 passion and purpose in, 116, 119–20, 122, 125, 134 probabilistic thinking and, 116, 121–22, 129 rapid iteration in, 116, 126, 133–34 rationally optimistic thinking and, 116, 136–37 risk management in, 116, 121–22, 126–27, 137 Scaled Composites, 262 Schawinski, Kevin, 219–21 Schmidt, Eric, 99, 128, 251 Schmidt, Wendy, 251, 253 Schmidt Family Foundation, 251 science of motivation, 78–80, 85, 87, 92, 103 incentive competitions and, 148, 254, 255, 262–63 Screw It, Let’s Do It (Branson), 125 Scriptlance, 149 Sealed Air Corporation, 30–31 Second Life, 144 SecondMarket, 174 “secrets of skunk,” see skunk methodology Securities and Exchange Commission (SEC), US, 172 security-related sensors, 43 sensors, see networks and sensors Shapeways.com, 38 Shingles, Marcus, 159, 245, 274–75 Shirky, Clay, 215 ShotSpotter, 43 Simply Music, 258 Singh, Narinder, 228 Singularity University (SU), xi, xii, xiv, 15, 35, 37, 53, 61, 73, 81, 85, 136, 169, 278, 279 Six Ds of Exponentials, 7–15, 8, 17, 20, 25 deception phase in, 8, 9, 10, 24, 25–26, 29, 30, 31, 41, 59, 60 dematerialization in, 8, 10, 11–13, 14, 15, 20–21, 66 democratization in, 8, 10, 13–15, 21, 33, 51–52, 59, 64–65, 276 demonetization in, 8, 10–11, 14, 15, 52, 64–65, 138, 163, 167, 223 digitalization in, 8–9, 10 disruption phase in, 8, 9–10, 20, 24, 25, 29, 32, 33–35, 37, 38, 39, 256; see also disruption, exponential Skonk Works, 71, 72 skunk methodology, 71–87, 88 goal setting in, 74–75, 78, 79, 80, 82–83, 84, 85, 87, 103 Google’s use of, 81–84 isolation in, 72, 76, 78, 79, 81–82, 257 “Kelly’s rules” in, 74, 75–76, 77, 81, 84, 247 rapid iteration approach in, 76, 77, 78, 79–80, 83–84, 85, 86 risk management in, 76–77, 82, 83, 84, 86, 87, 88 science of motivation and, 78–80, 85, 87, 92 triggering flow with, 86, 87 Skunk Works, 72, 75 Skybox, 286n Skype, 11, 13, 167 Sloan Digital Sky Survey, 219–20 Small Business Association, US, 169 smartphones, x, 7, 12, 14, 15, 42, 135, 283n apps for, 13, 13, 15, 16, 28, 47, 176 information gathering with, 47 SmartThings, 48 smartwatches, 176–77, 178, 191, 208 software development, 77, 144, 158, 159, 161, 236 in exponential communities, 225–28 SolarCity, 111, 117, 119, 120, 122 Space Adventures Limited, 96, 291n space exploration, 81, 96, 97–100, 115, 118, 119, 122, 123, 134, 139, 230, 244 asteroid mining in, 95–96, 97–99, 107, 109, 179, 221, 276 classifying of galaxies and, 219–21, 228 commercial tourism projects in, 96–97, 109, 115, 119, 125, 127, 244, 246, 261, 268 crowdfunding campaigns for, see ARKYD Space Telescope campaign incentive competitions in, 76, 96, 109, 112, 115, 127, 134, 139, 246, 248–49, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269 International Space University and, 96, 100–104, 107–8 Mars missions in, 99, 118–19, 128 see also aerospace industry Space Fair, 291n “space selfie,” 180, 189–90, 196, 208 SpaceShipOne, 96, 97, 127, 269 SpaceShipTwo, 96–97 SpaceX, 34, 111, 117, 119, 122, 123 Speed Stick, 152, 154 Spiner, Brent, 180, 200, 207 Spirit of St.


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The Social Animal: The Hidden Sources of Love, Character, and Achievement by David Brooks

Albert Einstein, asset allocation, assortative mating, Atul Gawande, Bernie Madoff, business process, Cass Sunstein, choice architecture, clean water, creative destruction, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, deliberate practice, disintermediation, Donald Trump, Douglas Hofstadter, Emanuel Derman, en.wikipedia.org, fear of failure, financial deregulation, financial independence, Flynn Effect, George Akerlof, Henri Poincaré, hiring and firing, impulse control, invisible hand, Joseph Schumpeter, labor-force participation, longitudinal study, loss aversion, medical residency, meta analysis, meta-analysis, Monroe Doctrine, Paul Samuelson, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, school vouchers, six sigma, social intelligence, Stanford marshmallow experiment, Steve Jobs, Steven Pinker, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, Walter Mischel, young professional

In the nonaroused state, 23 percent said they could imagine having sex with a twelve-year-old girl. In the aroused state, 46 percent said they could imagine it. In the nonaroused state, 20 percent said they would try to have sex with their date after she said no. In the aroused state, 45 percent said they would keep trying. Finally, there is loss aversion. Losing money brings more pain than winning money brings pleasure. Daniel Kahneman and Amos Tversky asked people if they would accept certain bets. They found that people needed the chance of winning $40 if they were going to undergo a bet that might cost them $20. Because of loss aversion investors are quicker to sell stocks that have made them money than they are to sell stocks that have been declining. They’re making self-destructive decisions because they don’t want to admit their losses. Rebirth Gradually Erica acquired a new vocabulary to define unconscious biases.

Ornstein, Multimind: A New Way of Looking at Human Behavior (New York: Houghton Mifflin, 1996), 86. 21 high Social Security numbers Dan Ariely, “The Fallacy of Supply and Demand,” Huffington Post, March 20, 2008, http://www.huffingtonpost.com/dan-ariely/the-fallacy-of-supply-and_b_92590.html. 22 People who are given Hallinan, 50. 23 “Their predictions became” Jonah Lehrer, How We Decide (New York: Houghton Mifflin Co., 2009), 146. 24 They just stick with Thaler and Sunstein, 34. 25 The picture of the smiling Hallinan, 101. 26 In the aroused state Ariely, 96 and 106. 27 Daniel Kahneman and Amos Tversky Jonah Lehrer, “Loss Aversion,” The Frontal Cortex, February 10, 2010, http://scienceblogs.com/cortex/2010/02/loss_aversion.php. CHAPTER 12: FREEDOM AND COMMITMENT 1 In Guess culture Oliver Burkerman, “This Column Will Change Your Life,” The Guardian, May 8, 2010, http://www.guardian.co.uk/lifeandstyle/2010/may/08/change-life-asker-guesser. 2 Thirty-eight percent of young Americans “Pew Report on Community Satisfaction,” Pew Research Center (January 29, 2009): 10, http://pewsocialtrends.org/assets/pdf/Community-Satisfaction.pdf. 3 In Western Europe William A.


pages: 518 words: 147,036

The Fissured Workplace by David Weil

accounting loophole / creative accounting, affirmative action, Affordable Care Act / Obamacare, banking crisis, barriers to entry, business cycle, business process, buy and hold, call centre, Carmen Reinhart, Cass Sunstein, Clayton Christensen, clean water, collective bargaining, commoditize, corporate governance, corporate raider, Corrections Corporation of America, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, declining real wages, employer provided health coverage, Frank Levy and Richard Murnane: The New Division of Labor, George Akerlof, global supply chain, global value chain, hiring and firing, income inequality, information asymmetry, intermodal, inventory management, Jane Jacobs, Kenneth Rogoff, law of one price, loss aversion, low skilled workers, minimum wage unemployment, moral hazard, Network effects, new economy, occupational segregation, Paul Samuelson, performance metric, pre–internet, price discrimination, principal–agent problem, Rana Plaza, Richard Florida, Richard Thaler, Ronald Coase, shareholder value, Silicon Valley, statistical model, Steve Jobs, supply-chain management, The Death and Life of Great American Cities, The Nature of the Firm, transaction costs, ultimatum game, union organizing, women in the workforce, yield management

If the pay of the group just above me is too high—or if the gap widens over time—I may be less and less happy with the pay I receive, regardless of its absolute level. Psychologists have long known that people care more about a small loss in income than about an equal gain in income.25 This effect—called loss aversion—means that perceptions of being adversely affected by a change in a current situation will make people feel worse than a comparable improvement in position makes them feel better. In a workplace context, loss aversion means that if a worker’s pay situation changes in a way that is judged unfair, it will have larger effects than if the situation changes in a way that is judged as improving fairness. Wage comparisons across different occupations or jobs can have this effect. Imagine that I have a job I view as “better” (for example, requiring more skill or savvy) than another job at my workplace.

For example, Herbert Meyer, on the basis of his research on personnel policies, recommended that firms give “all employees judged to be performing at a satisfactory level the same percentage increase whenever salaries are adjusted upward.” In so doing, “a predictable salary progress schedule not only should help to reduce uncertainty about future pay but also should prevent the development of false expectations. In addition it should minimize dysfunctional competition between individuals for favored treatment.” Quoted in Foulkes (1980, 186). 25. Fehr, Goette, and Zehnder (2009, 378). The literature on loss aversion and “framing” in psychology is extensive. The seminal papers are Tversky and Kahneman (1974) and Kahneman and Tversky (1984). Kahneman (2011) provides an overview of the extensive research in the field in the decades following those landmark works. 26. Slichter, Healy, and Livernash (1960) explained the common practice of uniform pay increases with job grades with minimal performance evaluation in union and nonunion facilities as an outgrowth of union avoidance and the constant problems of defending merit-based evaluations in the minds of workers.

Yensavage, 347n50 Lenny, Richard, 115 Lettire Construction, 233–234 Liability: as issue in fissuring, 78; tests to assess, 186, 190; vicarious liability defined, 189; and subcontracting, 190–192; and multiemployer settings, 192–195, 233–234; and franchising, 195–201; and supply chain relationships, 201–203 Lilly Ledbetter Fair Pay Act, 209 Litton Industries, 36 Locke, Richard, 174, 264, 365n39, 366n41 Logistics industry: and outsourcing, 57–58, 63; and fissuring, 96, 117–118, 160–167 Loss aversion, 85–86 LRSolutions, 275–276 Lyons and Sons, 115–117, 321n55 Maintenance services, and outsourcing, 55–56 Markets. See Capital markets; Financial markets; Internal labor markets; Labor market; Stock market Marriott, 2–3, 146, 150; and branding, 331n54 Massachusetts: and franchising, 198–199; and presumption of employee status, 204–205 Massey Doctrine, 102–103, 107, 369n17 Massey Upper Big Branch (mine disaster), 238 McDonald’s, 127, 259, 261, 323n4, 325n14; Miller v.


pages: 274 words: 93,758

Phishing for Phools: The Economics of Manipulation and Deception by George A. Akerlof, Robert J. Shiller, Stanley B Resor Professor Of Economics Robert J Shiller

"Robert Solow", Andrei Shleifer, asset-backed security, Bernie Madoff, business cycle, Capital in the Twenty-First Century by Thomas Piketty, collapse of Lehman Brothers, corporate raider, Credit Default Swap, Daniel Kahneman / Amos Tversky, dark matter, David Brooks, desegregation, en.wikipedia.org, endowment effect, equity premium, financial intermediation, financial thriller, fixed income, full employment, George Akerlof, greed is good, income per capita, invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kenneth Arrow, Kenneth Rogoff, late fees, loss aversion, market bubble, Menlo Park, mental accounting, Milgram experiment, money market fund, moral hazard, new economy, Pareto efficiency, Paul Samuelson, payday loans, Ponzi scheme, profit motive, publication bias, Ralph Nader, randomized controlled trial, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, short selling, Silicon Valley, the new new thing, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, theory of mind, Thorstein Veblen, too big to fail, transaction costs, Unsafe at Any Speed, Upton Sinclair, Vanguard fund, Vilfredo Pareto, wage slave

Or, in another example, insurance companies played on desires for immortality through advertising that, curiously, portrayed the deceased father in after-death family pictures.21 Social psychologist/marketer Robert Cialdini has written a book full of impressive evidence of psychological biases.22 According to his “list,” we are phishable because we want to reciprocate gifts and favors; because we want to be nice to people we like; because we do not want to disobey authority; because we tend to follow others in deciding how to behave; because we want our decisions to be internally consistent; and because we are averse to taking losses.23 Following Cialdini, each of these respective biases is paired with common salesman’s tricks. One such example concerns how his brother, Richard, paid his way through college. Every week, Richard would purchase two or three cars from the advertisements in the local newspapers. He would clean them up and offer them for sale again. Here, Richard put “loss aversion” to work. Richard did not, as most of us would do, schedule his prospective buyers to come at different times. Instead, intentionally, he scheduled them with overlap. Each buyer, whatever the merits of the prospective car, was then apprehensive that he might lose out: that other guy might get his car.24 Information Phools A great deal of phishing comes from another source: from supplying us with misleading, or erroneous, information.

Vance Packard, The Hidden Persuaders: What Makes Us Buy, Believe—and Even Vote—the Way We Do (Brooklyn: Ig Publishing, 2007; original ed., New York: McKay, 1957), pp. 90–91 (cake mixes); p. 94 (insurance). 22. Robert B. Cialdini, Influence: The Psychology of Persuasion (New York: HarperCollins, 2007). 23. These correspond to Cialdini’s categories of “reciprocation,” “liking,” “authority: directed deference,” “social proof,” “commitment and consistency,” and “scarcity.” We have referred to “scarcity” as “loss aversion” since Cialdini emphasizes (ibid., p. 204) that “the way to love anything is to realize it might be lost [sic].” Behavioral economists would, we think, have a slightly different classification. 24. Ibid., pp. 229–30. 25. London School of Economics economist Eric Eyster told George that he witnessed this magic trick used in a con game on the Chicago subway. The tricksters boarded his subway car, set the cups up on the floor, and did their swirl, inviting passengers to guess where the coin would end up.

In the case of Vance Packard, the cake-baking housewives are embedding themselves in a story in which they are creative; the insurance-purchasing men are embedding themselves in a story in which they are literally “in the pic ture.” It is useful to look at Cialdini’s list of behaviors, since they encompass most of the psychological biases that have formed the basis for behavioral economics. According to Cialdini, the purchasers of his brother Richard’s cars are embedding themselves in a story in which they are thinking of the possibility that they will “lose” the car (they are what Kahneman has called loss averse); what we here call stories, he calls “mental frames.” For the other five items on Cialdini’s list we can again view people as making their decisions from the point of view of a “story.” People want to reciprocate gifts and favors: to do so they must be taking part in a story in which someone gives a gift, and it would be wrong not to reciprocate. People want to be liked: to do so they must be taking part in a story in which they are liked, or not liked, by someone else.


pages: 437 words: 105,934

#Republic: Divided Democracy in the Age of Social Media by Cass R. Sunstein

A Declaration of the Independence of Cyberspace, affirmative action, Affordable Care Act / Obamacare, Bernie Sanders, Cass Sunstein, choice architecture, Donald Trump, drone strike, Erik Brynjolfsson, Filter Bubble, friendly fire, global village, illegal immigration, immigration reform, income inequality, Jane Jacobs, loss aversion, Mark Zuckerberg, obamacare, prediction markets, road to serfdom, Ronald Reagan, Silicon Valley, Skype, Snapchat, stem cell, The Chicago School, The Death and Life of Great American Cities, The Wisdom of Crowds, WikiLeaks

Countless people are using social media to build larger and more diverse communities. But there is narrowing as well, in the form of communities of niches. One of my own fields is behavioral science, and with the help of Twitter, those of us who are interested in that field can easily find each other. If you want to learn about the latest developments, Twitter is a great help. For example, behavioral scientists are interested in “loss aversion,” which means that people dislike losses more than they like corresponding gains. If you’re interested in new examples, exceptions, or elaborations of the behavioral finding, Twitter is terrific. And yes, there is a #lossaversion. That’s great, but for academics in any particular field, there’s a risk that Twitter will contain echo chambers just for them. And of course people can find hashtags to signal topics or points of view of many different kinds.

Kelly, 114–15 Gates, Bill, 52–53, 134, 196 general-interest intermediaries: bias and, 148; citizens and, 166; Daily Me and, 20; as default, 25; improving, 230; judgment and, 43; mass media and, 18–19; newspapers and, 13 (see also newspapers); polarization and, 84; power of, 18; republicanism and, 253, 257, 260–61; self-insulation and, 13; shared experiences and, 152; social clarity and, 142–43; spreading information and, 140–43, 148, 151–52, 156; television and, 13 (see also television); as unacknowledged public forums, 41–44, 58 genetically modified organisms (GMOs), 59, 100, 130–32, 217 Gentzkow, Matthew, 115–16, 120–21 Gerken, Heather, 85 Germany, ix, 6, 17, 19, 25, 32, 34, 73, 203, 237 global warming, 68–69, 88, 217 Goodman, Jack, 197–98 Google, 3, 28, 37, 53, 118, 229, 265n2 greenhouse gases, 9, 127, 130–32, 218 group identity, 75–78, 81 Guess, Andrew, 116–17 Habermas, Jürgen, 46–47 Haberstam, Yosh, 120 hacking, 109, 178, 184, 186, 188, 201 Hale, Scott, 105–6, 108 Hamilton, Alexander, 49, 54 Hand, Learned, 249–50 Hardball (TV show), 120 Hardin, Russell, 240 Harvard University, 160 hashtags, 3, 43, 119, 245, 271n23; Congress and, 82; Democrats and, 80–81; entrepreneurs and, 4, 79–82; Internet Relay Chats and, 79; polarization and, 59, 79–82; Republicans and, 80–81; serendipity and, 79–81; Trump and, 83 hate groups, 67–68, 70, 87, 236 HBO, 179 health issues: Affordable Care Act (ACA) and, 81, 129; AIDS/HIV and, 110; bandwagon diseases and, 100; conspiracies and, 125–26; cybercascades and, 99–101; deliberative opinion polls on, 133; democracy and, 23, 29; false information and, 110; famine as metaphor and, 149; GMOs and, 59, 100, 130–32; insurance premiums and, 129; OSHA and, 218–19 Hebrew University, 112 Her (Jonze film), 20–22, 33 heterogeneous society: anti-federalists and, 48; fragmentation and, 51, 135; improving, 216; mass media and, 19; opinion polls and, 134; polarization and, 84, 86, 88–89; public forums and, 38–39, 41, 43; republicanism and, 257, 262; shared experiences and, 140; social problems and, 7; spreading information and, 140, 145, 155; US Constitution and, 48–51 Himelboim, Itai, 118–19 Hitler, Adolf, ix HIV, 110 holidays, 7, 141–42, 242 Holmes, Oliver Wendell, 52–57, 247–48, 250 homogeneous society: Facebook and, 125; polarization and, 69, 86, 92; social media bias and, 135; spreading information and, 151; Twitter and, 119; US Constitution and, 48–51; virtual world and, 13 homophily, 1–2, 5, 117–22 How to Win Friends and Influence People (Carnegie), 160 Huffington Post, 117, 123 Hughes, Chris, 82 human rights, 107 Hurricane Katrina, 19, 139 Hussein, Saddam, 94 Huxley, Aldous, x, 21 ideal speech situation, 47 identity: culture and, 129–35; group, 75–77, 81; judgment and, 129–35; shared, 239 ideologies: cultural cognition and, 129–30; cybercascades and, 115–23, 127, 131; polarization and, 61–62, 65, 81, 94–95; republicanism and, 260; spreading information and, 140; values and, 11, 14–15, 22, 30, 52, 75, 101, 113, 126–32, 142, 145, 163, 165, 169, 227, 232, 235, 253, 258; website choice and, 5, 25 ILOVEYOU virus, 176–78, 186, 191, 207 immigration, 1, 3–4, 11, 19, 39, 66, 129, 159, 235, 246 inert people, ix, 56, 145, 204, 261 information: advertising and, 146, 152–53; algorithms and, 3, 15, 21–22, 28–29, 32, 122–24, 257, 265n2; backfiring corrections and, 93–97, 111; bias and, 151–53 (see also bias); conspiracies and, 124–26; consumer sovereignty and, 52–53 (see also consumer sovereignty); copyright and, 29, 184–85, 195, 200–201, 219; cultural cognition and, 129–30; customized filtering and, 52–53 (see also filtering); cybercascades and, 98–136; Daily Me and, 1–4, 14–15, 19–21, 30–31, 52, 56, 58–59, 114, 153, 253, 255; disclosure policies and, 215, 218–23; easy creation of, 27–28; Emergency Planning and Community Right-to-Know Act and, 218; exposure and, 40–41; false, 11, 23, 109–10, 135, 155, 237, 250; fragmentation and, 140–41, 146, 149–55 (see also fragmentation); general-interest intermediaries and, 140–43, 148, 151–52, 156; hashtags and, 3–4, 43, 59, 79–83, 119, 245, 271n23; Internet and, 31, 138, 143–44, 148–54 (see also Internet); must-carry rules and, 215, 226–29; News Feed and, 2, 14–16, 41, 124, 232–33; preferences and, 58; producers and, 145–46; as product, 149; propaganda and, 109, 160, 236–37, 239, 245, 248–50; public forums and, 142, 156 (see also public forums); as public good, 45, 51, 57–58, 147–48, 260; reinforcement and, 63, 72, 78, 81, 114–15, 132, 148, 260–61; rumors and, 103, 108–11, 125, 236–37; self-imposed echo chambers and, 5–13, 17, 20, 50, 57, 59, 68, 71, 81, 90, 93, 114–18, 122–24, 131–32, 153, 163, 244, 262–64; social glue and, 7, 140, 143, 155, 260; social media and, 138–39, 148, 150, 152, 154–55; solidarity goods and, 58, 141–44; sound bites and, 43, 151, 224, 268n19; tipping points and, 102–4, 108–11; trending petitions and, 106; up/down votes and, 112–13; as wildfire, 102–4 innovation, 5, 133, 183, 243 “Inspire” (online terrorist journal), 236 Instagram, 22; cybercascades and, 114; polarization and, 79, 83, 89; public forums and, 36–37; regulation and, 179; spreading information and, 138, 149; terrorism and, 237–38 Internet: access to, 30; advertising and, 28; algorithms and, 3, 15, 21–22, 28–29, 32, 122–24, 257, 265n2; architecture of, 13; baselines and, 23; beginnings of, 181–86; Berners-Lee and, 183; bomb-making instructions and, 192, 235–37; browsing habits and, 5, 21–22, 116, 124; citizens and, 158, 160, 164, 169, 171–74; commercialization of, 183; consumer effect of, 171–74; conveniences of, 31–32; copyright and, 29; cybercascades and, 102, 108–11, 115–16, 123, 133–35; DARPA and, 182–83; death of mass media and, 19; deliberative domains and, 215–17; filtering and, 25–26 (see also filtering); forms of neutrality and, 207–10; free content and, 28; freedom of speech and, 192, 201–10; hashtags and, 3–4, 43, 59, 79–83, 119, 245, 271n23; ideologies and, 5, 25; ILOVEYOU virus and, 176–78, 186, 191, 207; improving, 215–16, 223, 226, 228–29; information available on, 31; isolation index and, 116, 120; legal issues and, 184–88; most popular sites on, 171–72; music and, 3, 21, 31–34, 64, 102, 104–8, 159, 192; online behavior and, 22–23, 65, 83, 98, 116–17, 130, 234–35; overload and, 63–68; Pariser and, 265n2; partyism and, 10; polarization and, 59–60, 64–68, 70, 72, 76–79, 86, 89; politics and, 116–17; potential of, 24; as public forum, 36; public sphere and, 153; regulation and, 178, 182–90; republicanism and, 253–61; self-insulation and, 13; shared experience and, 143; social media and, 22 (see also social media); sovereignty and, 52, 55; spreading information and, 138, 143–44, 148–54; tabloidization and, 223–24; terrorism and, 234–38, 240–43, 245–47; as threat, ix–x; websites and, 3, 6, 13, 22, 27–28, 32–33, 59–60, 62, 65, 67, 106–12, 146, 154, 166, 179, 185–94, 207–8, 212–17, 222–25, 229, 235, 242, 255, 268n18 Internet Relay Chats, 79 Iraq, 18, 42, 64, 93–94, 98, 242 ISIS, 238, 244 Islamic State of Iraq and Levant (ISIL), 98, 234, 236, 239, 241–48, 283n22 isolation: filtering and, 27, 38, 64, 98, 115–16, 120–22, 234, 242–43, 254, 265n2; index for, 115–16, 120–21; self-imposed echo chambers and, 5–13, 17, 20, 50, 57, 59, 68, 71, 81, 90, 93, 114–18, 122–24, 131–32, 153, 163, 244, 262–64 Israel, 6, 87, 91, 140–41, 245–46, 284n31 Italy, 6, 124, 203 Jacobs, Jane, 12–13, 260 jarring of parties, 49, 54 Jefferson, Thomas, 51–52 Jews, 96, 185 Jiabao, Wen, 139 jihad, 239, 241–42 John, Peter, 105–6, 108 Jonze, Spike, 20–22, 33 judgment: citizens and, 167, 169–70; cybercascades and, 99, 101–2, 127–35; freedom of speech and, 206; general-interest intermediaries and, 43; identity and, 129–35; insulation and, 51; prediction and, 28; republicanism and, 259, 261; sound bites and, 268n19; strengthening preexisting, 34; terrorism and, 235 Kahan, Dan, 129–31 Kahneman, Daniel, 17–18 Kennedy, Anthony, 36–37 King, Gary, 160–61 Knight, Brian, 120 Koran, 239 Kossinets, Gueorgi, 118 Ku Klux Klan, 109 Lazzaro, Stephanie, 127 legal issues: behavior and, 220–21; Brandeis and, 52–56, 145, 203, 220, 228, 247–48, 250–51; child-support and, 133; commercial speech and, 193, 205, 207; communications and, 220, 227; constitutional doctrine and, 192–201, 204 (see also constitutional doctrine); copyright and, 29, 184–85, 195, 200–201, 219; deliberative democracy and, 25, 34, 44, 48, 55–56, 86, 92, 133–35, 169, 195, 215–17, 220, 222, 228; Dewey and, 252; disclosure policies and, 215, 218–23; educational programming for children and, 170, 181, 197–99, 202, 204–5, 210–11, 221, 226; Facebook’s complicity in terrorism and, 246; First Amendment and, 36, 193, 195–207, 212, 227–28, 231; forms of neutrality and, 207–10; Fourteenth Amendment and, 199; fraud and, 2–6, 74, 109, 200–201, 258; freedom of speech and, 55–56, 191–212; Hand and, 249–50; Holmes and, 52–56, 247–48, 250; interference in communications market and, 177–79; Internet and, 184–88; must-carry rules and, 215, 226–29; national security and, 4, 42, 74, 178, 186, 216, 246; Nuremberg Files and, 191–92, 208; President’s Advisory Committee on the Public Interest Obligations of Digital Television Broadcasters and, 196–98; privacy and, 178, 225, 237, 243; property rights and, 179–90, 194, 258; Second Amendment and, 119, 198, 234; self-protection against illegal immigrants and, 235; sexual harassment and, 101; terrorism and, 246–47; unfreedom and, 163; US Constitution and, 247 (see also US Constitution) Lessig, Lawrence, 184 liberals: blogs and, 231; Colorado experiment and, 68–70, 77; confirmation bias and, 123; cybercascades and, 114–23; differing points of view and, 230; Facebook and, 3, 232; foxnews.com and, 228; fragmentation and, 10; polarization and, 61, 64, 68–70, 74, 84–85, 90, 94–95 liberty, 5, 11, 52, 138, 174, 204 limited argument pool, 72, 76 limited options, 164–67, 174 Littleton, Colorado attack, 236 lone-wolf attacks, 241, 244–45 long tails, 149–51, 171 Lorenz, Jan, 113–14 Los Angeles Times, 19, 152 loss aversion, 59 machine learning, 4–5 Madison, James, 45, 51–52, 203, 261 magazines: bias and, 152; choice of, 18; isolation and, 116; free content and, 229; general-interest intermediaries and, 41–42, 257; points of view and, 18, 66, 230; public forums and, 41–42; regulation and, 179, 181–82, 184, 187, 189; Twitter and, 118 majority rule, 53–54, 169–70 Malik, Tashfeen, 241 manipulation, 17, 28–29, 95, 164 Mao Tse-tung, ix Margetts, Helen, 105–6, 108 Marginal Revolution, 22 Martin, Gregory J., 61 martyrdom, 241 mass media: behavior and, 19; bias and, 151–52; death of, 19; echo chambers and, 116; freedom of speech and, 203; as general-interest intermediaries, 18–19; heterogeneous society and, 19; improving, 222; opposing viewpoints and, 71, 84, 207, 215, 231–33, 255; public forums and, 36–37; public sphere and, 153–54.

., 126–27 MSNBC, 61–62 Muchnik, Lev, 112 murder, 9, 109, 113–14, 192, 249 music, 21; artificial lab for, 102–4; consumption and, 3, 31–34, 64, 159, 192; cybercascades and, 102–8; preferences and, 3, 32–33; Rodriguez and, 103–5 Muslims, 79, 109, 235, 237, 239, 242, 248 must-carry rules, 215, 226–29 nanotechnology, 95–96, 129 National Association of Broadcasters, 197–98, 221 National Public Radio (NPR), 64–65 National Review magazine, 231 National Rifle Association, 198, 236 National Science Foundation, 183 national security, 4, 42, 74, 178, 186, 216, 246 Nation magazine, 230 Nazism, 87 NBC, 61–62, 152, 179–80, 198 Negroponte, Nicholas, 1–2 Netflix, 32–33, 150, 229 net neutrality, 29 Netscape, 171 New England Journal of Medicine, 100 newspapers: bias and, 151–52; curation and, 1; customized, 53; decline of, 20; education and, 20; freedom of speech and, 196; free society and, 18–19; ideological segregation and, 121; improving, 222–23, 227, 229, 233; isolation and, 116; particular histories of, 20; polarization and, 61, 66, 71, 84; public forums and, 13, 41–42; regulation and, 179, 181–82, 187, 189; republicanism and, 257; tabloidization and, 223–24; technology and, 152–53 Newsweek magazine, 18–19, 42 New York Review of Books, 19, 153 New York Times, 18, 22, 94–95, 120, 144, 152–53, 232 niches: cybercascades and, 115, 118; enclaves and, 85–89, 238, 253–56; fragmentation and, 23; markets and, 20, 27, 149–51, 253, 256; polarization and, 59–60; rise of, 8; spreading information and, 149–51 Nineteen Eighty-Four (Orwell), ix, 12, 21 Nobel Prize, 17, 187 Noell-Neumann, Elisabeth, 73 nostalgia, 8, 57–58, 259–61 Nuremberg Files, 191–92, 208 Obama, Barack, 2, 11, 79, 81–83, 87, 100, 104, 109, 113, 168, 246, 263 Occupational Safety and Health Administration (OSHA), 218–19 Oklahoma City bombing, 236 online behavior, 22–23, 65, 83, 98, 116–17, 130, 234–35 Open Government Partnership, 219 open-source software, 79, 184 opinion polls, 126, 133–35, 216, 268n19 opposing viewpoints, 71, 84, 207, 215, 231–33, 255 optimism, 8, 97 organic food, 131 Orkut, 22 Orlando nightclub shootings, 236 Orwell, George, ix, 12, 21 Ostrom, Elinor, 187–88 overload, 63–68 Palestine, 239, 245–46, 284n31 Pandora, 22, 32–33 Pariser, Eli, 265n2 partyism, 9–12, 25 paternalism, 167 PBS, 179, 225–26 penalties, 34–35, 92, 210–12, 246 Perez, Heather, 244 Periscope, 83 pessimism, 8, 16, 259–61 Pew Research Center, 126 Pokémon Go game, 22 polarization: abortion and, 66, 81, 90, 191–92, 208–9; advertising and, 63; appropriately slanted stories and, 62–63; backfiring corrections and, 93–97, 111; balkanization and, 66, 70, 73, 89, 111, 259; behavior and, 59, 61, 65–66, 83; bias and, 63, 92, 97; blogs and, 63, 79; Colorado experiment and, 68–70, 77; communications and, 25, 60, 63–64, 70, 75, 84–86, 89–92; confidence and, 74–75; conservatives and, 61, 64, 68–70, 72–75, 80, 84–85, 90, 94–95; conspiracies and, 124–26; consumer sovereignty and, 89; corroboration and, 74–75; crime and, 64, 92; cybercascades and, 82; cyberpolarization and, 68; Daily Me and, 59; deliberative democracy and, 86, 92; Democrats and, 61, 65, 70, 72, 76, 80–81, 90, 95; depolarization and, 89–92; diversity and, 69, 85–86; echo chambers and, 59, 68, 71, 81, 90, 93; emotion and, 82, 96–97; enclaves and, 85–89; entreprenuers of, 238; extremism and, 7, 67, 69, 72, 74, 76, 78, 86, 88; Facebook and, 64, 71–72, 82–83, 86, 89; fairness doctrine and, 84–85, 207, 221, 227; filtering and, 60–62, 64, 66, 71, 79, 82; fragmentation and, 5, 7, 64, 77, 83–86, 89, 221; general-interest intermediaries and, 84; group, 68, 70–79, 82–91, 93, 97, 118, 133, 146, 155, 234, 240, 253–54, 259, 277n67; groupism and, 63–68; hashtags and, 59, 79–82; heterogeneous society and, 84, 86, 88–89; homogeneous society and, 69, 86, 92; ideologies and, 61–62, 65, 81, 94–95; importance of group identity and, 75–78, 81; improving situation of, 213–14, 221; Instagram and, 79, 83, 89; Internet and, 59–60, 64–68, 70, 72, 76, 78–79, 86, 89; Jon Stewart strategy and, 77; liberals and, 61, 64, 68–70, 74, 84–85, 90, 94–95; limited argument pool and, 72, 76; loss aversion and, 59; newspapers and, 61, 66, 71, 84; niches and, 59–60; online, 76–79; overload and, 63–68; persuasive arguments and, 71–72; preferences and, 65, 68; producers and, 146; public forums and, 84, 88; racism and, 80–81; radicalization and, 45, 74–75, 235, 237, 241–42, 244–46; radio and, 64, 66, 71–73, 75, 83–85; Republicans and, 61–65, 70, 72, 76, 80–81, 83, 90, 95; reputational considerations and, 72–74; social media and, 59, 62–63, 66, 68, 70–71, 73, 75, 78–89, 93, 95; strong convictions and, 63, 66–67, 72, 95–97; television and, 62, 64, 66, 71–73, 75, 77, 83–84; terrorism and, 234, 238, 240; Twitter and, 59, 64, 71–72, 74, 79–83, 87, 89, 95, 278n16; unbalanced views and, 92–93; unfamiliar issues and, 95–96 Political Turbulence (Margetts, John, Hale, and Yasseri), 105–6 politics: activists and, 80, 82, 178, 234, 235, 242; authoritarianism and, x, 11, 38, 73, 98, 108, 160, 165, 254; campaign finance and, 193–94; Citizens United case and, 193–94; Clintons and, 15, 59, 104, 109, 117; Colorado experiment and, 68–70, 77; communications and, 54; communism and, ix, 4, 80, 164, 189, 248; confirmation bias and, 123; conservatives and, 61 (see also conservatives); cybercascades and, 104–8; democracy and, 4 (see also democracy); Democrats and, 10 (see also Democrats); Dennis v.


Capital Ideas Evolving by Peter L. Bernstein

Albert Einstein, algorithmic trading, Andrei Shleifer, asset allocation, business cycle, buy and hold, buy low sell high, capital asset pricing model, commodity trading advisor, computerized trading, creative destruction, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, diversification, diversified portfolio, endowment effect, equity premium, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, high net worth, hiring and firing, index fund, invisible hand, Isaac Newton, John Meriwether, John von Neumann, Joseph Schumpeter, Kenneth Arrow, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, mental accounting, money market fund, Myron Scholes, paper trading, passive investing, Paul Samuelson, price anchoring, price stability, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, statistical model, survivorship bias, systematic trading, technology bubble, The Wealth of Nations by Adam Smith, transaction costs, yield curve, Yogi Berra, zero-sum game

And * On a personal note, I f irst met Paul Samuelson about the time this paper appeared. Then in his early twenties, Samuelson had already made his reputation by having published more papers than he was years old. bern_c03.qxd 40 3/23/07 9:01 AM Page 40 THE THEORETICIANS then he adds, “There is a separate love for the sport of gambling. But that is independent of the way they respond to the more serious business of managing their wealth. There loss aversion prevails.” From Samuelson’s point of view, the existence of a positive alpha somewhere is not an exception to the Efficient Market Hypothesis but a kind of vindication of the logic of it. There are rare occasions when an investor succeeds in earning positive alpha—beating the market after adjustment for risk by gaining access to information earlier than other investors or by discovering mispriced assets other investors ignored.

“Y * Unless otherwise specif ied, all quotations are from personal interviews or correspondence. 100 bern_c08.qxd 3/23/07 9:05 AM Page 101 Harry Markowitz 101 Today’s Harry Markowitz has no preconceived notions about how “recognizable economic agents” actually make decisions and act, even though he has strong convictions on how they should act. After all, as he points out, you can look at stock prices swinging up and down every day, but what you observe reveals nothing about what is going on under the surface, such as the degree to which investors are succumbing to the overconfidence and loss aversion featured in Behavioral Finance. Markowitz has wanted to explore in detail how stock prices would behave in a market where some investors have behavioral quirks while others are coolly rational. He is also interested in studying the consequences for stock prices when some investors take on risks that differ from the risks other investors are taking. Markowitz believes none of this can be accomplished by modeling.

Thaler, Richard, 1992. The Winner ’s Curse: Paradoxes and Homilies of Economic Life, Princeton, NJ: Princeton University Press. Thaler, Richard, and Eric Johnson, 1990. “Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice,” Management Science, Vol. 36, No. 6 ( June), pp. 643– 660. Thaler, Richard, Daniel Kahneman, and J. L. Knetsch, 1992. “The Endowment Effect, Loss Aversion and Status Quo Bias,” in Richard Thaler, The Winner ’s Curse, Princeton, NJ: Princeton University Press. Temin, Peter, and Hans-Joachim Voth, 2003. “Riding the South Sea Bubble,” MIT Economics Department Working Paper No. 04-02 ( December). Treynor, Jack, 1961. “Toward a Theory of Market Value of Risky Assets.” Unpublished manuscript. Treynor, Jack, and Fischer Black, 1973. “How to Use Security Analysis to Improve Portfolio Selection,” Journal of Business, Vol. 46, pp. 66–73.


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Essentialism: The Disciplined Pursuit of Less by Greg McKeown

Albert Einstein, Clayton Christensen, Daniel Kahneman / Amos Tversky, deliberate practice, double helix, en.wikipedia.org, endowment effect, Isaac Newton, iterative process, Jeff Bezos, Lao Tzu, lateral thinking, loss aversion, low cost airline, Mahatma Gandhi, microcredit, minimum viable product, Nelson Mandela, North Sea oil, Peter Thiel, Ralph Waldo Emerson, Richard Thaler, Rosa Parks, Shai Danziger, side project, Silicon Valley, Silicon Valley startup, sovereign wealth fund, Stanford prison experiment, Steve Jobs, Vilfredo Pareto

Before the words “That sounds great, I’d love to” fly out of your mouth, ask yourself, “Is this essential?” If you’ve already made a casual commitment you’re regretting, find a nice way to worm your way out. Simply apologize and tell the person that when you made the commitment you didn’t fully realize what it would entail. GET OVER THE FEAR OF MISSING OUT We’ve seen ample evidence in this chapter suggesting that the majority of us are naturally very loss-averse. As a result, one of the obstacles to uncommitting ourselves from a present course is the fear of missing out on something great. TO FIGHT THIS FEAR, RUN A REVERSE PILOT One of the ideas that has grown popular in business circles in recent years is “prototyping.” Building a prototype, or large-scale model, allows companies to test-run an idea or product without making a huge investment up front.

“Ministers Knew Aircraft Would Not Make Money,” Independent, http://www.independent.co.uk/news/uk/ministers-knew-aircraft-would-not-make-money-concorde-thirty-years-ago-harold-macmillan-sacked-a-third-of-his-cabinet-concorde-was-approved-the-cuba-crisis-shook-the-world-and-ministers-considered-pit-closures-anthony-bevins-and-nicholas-timmins-review-highlights-from-1962-government-files-made-public-yesterday-1476025.html 3. Gillman, “Supersonic Bust.” 4. Michael Rosenfield, “NH Man Loses Life Savings on Carnival Game,” CBS Boston, April 29, 2013, http://boston.cbslocal.com/2013/04/29/nh-man-loses-life-savings-on-carnival-game/. 5. Daniel Kahneman, Jack L. Knetsch, and Richard H. Thaler, “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias,” Journal of Economic Perspective 5, no. 1 (1991): 193–206, http://users.tricity.wsu.edu/~achaudh/kahnemanetal.pdf. 6. Tom Stafford, “Why We Love to Hoard … and How You Can Overcome It,” BBC News, July 17, 2012, www.bbc.com/future/story/20120717-why-we-love-to-hoard. 7. I originally wrote this in a blog post for Harvard Business Review called “The Disciplined Pursuit of Less,” August 8, 2012, http://blogs.hbr.org/2012/08/the-disciplined-pursuit-of-less/. 8.


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Traffic: Why We Drive the Way We Do (And What It Says About Us) by Tom Vanderbilt

Albert Einstein, autonomous vehicles, availability heuristic, Berlin Wall, call centre, cellular automata, Cesare Marchetti: Marchetti’s constant, cognitive dissonance, computer vision, congestion charging, Daniel Kahneman / Amos Tversky, DARPA: Urban Challenge, endowment effect, extreme commuting, fundamental attribution error, Google Earth, hedonic treadmill, hindsight bias, hive mind, if you build it, they will come, impulse control, income inequality, Induced demand, invisible hand, Isaac Newton, Jane Jacobs, John Nash: game theory, Kenneth Arrow, lake wobegon effect, loss aversion, megacity, Milgram experiment, Nash equilibrium, Sam Peltzman, Silicon Valley, statistical model, the built environment, The Death and Life of Great American Cities, traffic fines, ultimatum game, urban planning, urban sprawl, women in the workforce, working poor

Waterson, “Are We Looking Where We Are Going? An Exploratory Examination of Eye Movement in High Speed Driving.” Paper 04-2602, Proceedings of the 83rd Annual Meeting of the Transportation Research Board (Washington D.C., January 2004). “loss aversion”: The notion of loss aversion was first hypothesized by Daniel Kahneman and Amos Tversky, “Prospect Theory: An Analysis of Decision Under Risk,” Econometrica, vol. 47 (1979), pp. 263–91. sensitive to loss: See Sabrina M. Tom, Craig R. Fox, Christopher Trepel, and Russell A. Poldrack, “The Neural Basis of Loss Aversion in Decision-Making Under Risk,” Science, vol. 315, no. 5811 (26 January 2007), pp. 515–18. See also William J. Gehring and Adrian R. Willoughby, “The Medial Frontal Cortex and the Rapid Processing of Monetary Gains and Losses,” Science, vol. 295, no. 5563 (2002), pp. 2279–82.

This includes, of course, the adjacent lane; estimates are that for every two glances we make at our own lane, we make one glance at the next lane—simply so we can actually stay in our lane. This means we are highly aware of vehicles passing us. We spend only about 6 percent of our driving time looking in the rearview mirror. In other words, we’re much more aware of what is passing us than what we have passed. The fact that we spend more time seeing losses than gains while driving in congestion plays perfectly into a well-known psychological theory called “loss aversion.” Any number of experiments have shown that humans register losses more powerfully than gains. Our brains even seem rigged to be more sensitive to loss. In what psychologist Daniel Kahneman has called the “endowment affect,” once people have been given something, they are instantly more hesitant to give it up. Do you remember the childlike glee you felt the last time you found a parking spot at the mall on a crowded day?


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A Mathematician Plays the Stock Market by John Allen Paulos

Benoit Mandelbrot, Black-Scholes formula, Brownian motion, business climate, business cycle, butter production in bangladesh, butterfly effect, capital asset pricing model, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversified portfolio, dogs of the Dow, Donald Trump, double entry bookkeeping, Elliott wave, endowment effect, Erdős number, Eugene Fama: efficient market hypothesis, four colour theorem, George Gilder, global village, greed is good, index fund, intangible asset, invisible hand, Isaac Newton, John Nash: game theory, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, mental accounting, Myron Scholes, Nash equilibrium, Network effects, passive investing, Paul Erdős, Paul Samuelson, Ponzi scheme, price anchoring, Ralph Nelson Elliott, random walk, Richard Thaler, Robert Shiller, Robert Shiller, short selling, six sigma, Stephen Hawking, stocks for the long run, survivorship bias, transaction costs, ultimatum game, Vanguard fund, Yogi Berra

The WorldCom chatrooms went into one of their typical frenzies and the price dropped further. My reaction, painful to recall, was, “At these prices I can finally get out of the hole.” I bought more shares even though I knew better. There was apparently a loose connection between my brain and my fingers, which kept clicking the buy button on my Schwab online account in an effort to avoid the losses that loomed. Outside of business, loss aversion plays a role as well. It’s something of a truism that the attempt to cover up a scandal often leads to a much worse scandal. Although most people know this, attempts to cover up are still common, presumably because, here too, people are much more willing to take risks to avoid losses than they are to obtain gains. Another chink in our cognitive apparatus is Richard Thaler’s notion of “mental accounts,” mentioned in the last chapter.

Petersburg paradox ultimatum games WorldCom board game Gans, Herbert Gates, Bill geometric mean illustrated by IPO purchases/sales rate of return “ghosts,” investors Gilder, George Gilovich, Thomas Godel, Kurt Goethe golden ratio Goodman, Nelson gossip Gould, Steven Jay Graham, Benjamin Greek mathematics Greenspan, Alan impact on stock and bond markets on irrational exuberance of investors growth investing vs. value investing growth stocks Grubman, Jack guessing games guilt and despair over market losses Hart, Sergiu “head and shoulders” pattern hedge funds herd-like nature, of stock market Hill, Ted How Nature Works (Bak) How We Know What Isn’t So (Gilovich) “The Imp in the Bottle” (Stevenson) In Search of Excellence (Peters) incompleteness theorem of mathematical logic index funds Efficient market theorists investing in as safe investment inflationary universe hypothesis Innumeracy (Paulos) insider trading attraction of stock manipulation by unexplained price movements and Institutional Investor insurance company example, expected value insurance put options interest rates, market predictability and internal rate of return Internet diameter (or interconnectedness) of “flocking effect,” as network of associations investment clubs investment strategies. see also predictability, of stock market based on Parrondo’s paradox contrarian investing dogs of the Dow fundamental analysis. see fundamental analysis momentum investing secrecy and value investing. see value investing investments. see also margin investments confirmation bias and considering utility of dollars invested vs. dollars themselves counter-intuitive emotions dictating guilt and despair over losses ignoring uniformity of positive ratings protective measures randomness vs. predictability and rumors and safe windfall money and investors. see also traders behavior as nonlinear systems beliefs of impact Efficient Market Hypothesis “blow up” and becoming “ghosts,” buying/selling puts on S&P common knowledge and gauging investors as important as gauging investments irrational exuberance/irrational despair online trading and price oscillation created by investor reactions to each other self description in bear and bull markets short-term IPOs alternative rates of return from as a pyramid scheme Salomon Smith Barney benefitting illegally from stock market in 1990s and strategy for buying and selling Jegadeesh, Narsimhan Jeong, Hawoong Judgment Under Uncertainty (Tversky, Kahneman, and Slovic) Kahneman, Daniel Keynes, John Maynard Kolmogorov, A. N. Kozlowski, Dennis Kraus, Karl Krauthammer, Charles Kudlow, Larry Lakonishok, Josef Landsburg, Steven Lay, Ken LeBaron, Blake Lefevre, Edwin Leibweber, David linguistics, power law and Lo, Andrew logistic curve lognormal distribution Long-Term Capital Management (LTCM) losing through winning loss aversion lotteries present value and as tax on stupidity Lynch, Peter MacKinlay, Craig mad money Malkiel, Burton management, manipulating stock prices Mandelbrot, Benoit margin calls margin investments buying on the margin as investment type margin calls selling on the margin market makers decimalization and World Class Options Market Maker (WCOMM) Markowitz, Harry mathematics, generally Greek movies and plays about outguessing the average guess risk and stock markets and Mathews, Eddie “maximization of expected value” principle mean value. see also expected value arithmetic mean deviation from the mean geometric mean regression to the mean using interchangeably with expected value media celebrities and crisis mentality and impact on market volatility median rate of return Merrill Lynch Merton, Robert mnemonic rules momentum investing money, categorizing into mental accounts Morgenson, Gretchen Motley Fool contrarian investment strategy PEG ratio and moving averages complications with evidence supporting example of generating buy-sell rules from getting the big picture with irrelevant in efficient market phlegmatic nature of mu (m) multifractal forgeries mutual funds expert picks and hedge funds index funds politically incorrect rationale for socially regressive funds mutual knowledge, contrasted with common knowledge Nash equilibrium Nash, John Neff, John negatively correlated stocks as basis of mutual fund selection as basis of stock selection stock portfolios and networks Internet as example of price movements and six degrees of separation and A New Kind of Science (Wolfram) Newcomb, Simon Newcombe, William Newcombe’s paradox Niederhoffer, Victor Nigrini, Mark nominal value A Non-Random Walk Down Wall Street (Lo and MacKinlay) nonlinear systems billiards example “butterfly effect” or sensitive dependence of chaos theory and fractals and investor behavior and normal distribution Nozick, Robert numbers anchoring effect Benford’s Law and Fibonacci numbers and off-shore entities, Enron Once Upon a Number (Paulos) online chatrooms online trading optimal portfolio balancing with risk-free portfolio Markowitz efficient frontier of options. see stock options Ormerod, Paul O’Shaughnessy, James P/B (price-to-book) ratio P/E ratio interpreting measuring future earnings expectations PEG variation on stock valuation and P/S (price to sales) ratio paradoxes Efficient Market Hypothesis and examples of Newcombe’s paradox Parrondo’s paradox St.


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I.O.U.: Why Everyone Owes Everyone and No One Can Pay by John Lanchester

asset-backed security, bank run, banking crisis, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Black-Scholes formula, Blythe Masters, Celtic Tiger, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, diversified portfolio, double entry bookkeeping, Exxon Valdez, Fall of the Berlin Wall, financial deregulation, financial innovation, fixed income, George Akerlof, greed is good, hedonic treadmill, hindsight bias, housing crisis, Hyman Minsky, intangible asset, interest rate swap, invisible hand, Jane Jacobs, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Meriwether, Kickstarter, laissez-faire capitalism, light touch regulation, liquidity trap, Long Term Capital Management, loss aversion, Martin Wolf, money market fund, mortgage debt, mortgage tax deduction, mutually assured destruction, Myron Scholes, negative equity, new economy, Nick Leeson, Norman Mailer, Northern Rock, Own Your Own Home, Ponzi scheme, quantitative easing, reserve currency, Right to Buy, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, South Sea Bubble, statistical model, The Great Moderation, the payments system, too big to fail, tulip mania, value at risk

I have a confession to make about Kahneman and Tversky. I’d never heard of them until Kahneman won the Nobel,* and when I first read about their work, it seemed to me to consist of things which were surprising only to economists. One of their interests was “hindsight bias,” the way in which a random sequence of events is given structure and narrative by the false perspective of looking back over it from its outcome. Another was “loss aversion,” the fact that people place a higher value on not losing money than on gaining it; another was on “the law of small numbers,” referring to people’s tendency to draw overconfident conclusions from small amounts of evidence. Their particular interest was in “heuristics,” the patterns of thinking people use to interpret data, and the strong conclusion they reached was that people’s heuristics are often wrong; we are much less accurate and less rational in our thinking than we believe ourselves to be.

., 115–17, 157–58 liabilities, 31–35 in balance sheets, 25–28, 31–34, 37 of banks, 25, 32–35, 37, 41, 204 of individuals, 27–28, 35 leverage and, 35, 41, 60 libel law, 93 life expectancies, 17, 213 liquidity, 212 housing and, 28–29, 90, 96–97 investments and, 60–61 Lloyds TSB, 36, 38–40 loans, lending, 74–76, 108–9 in balance sheets, 27, 30, 34 of banks, 22, 24, 27, 33–36, 41–42, 58–60, 67, 69–70, 74, 83–84, 91–94, 102, 117, 127, 129–30, 143, 146, 165, 187, 216–17, 229 credit and, 209, 216–17 derivatives and, 50–51, 55, 66–75, 80, 121–22 Exxon deal and, 67–68 interest rates and, 59–60, 66, 74, 102, 108, 145, 172–73 paying the bill and, 220–21 predatory, 122, 127–32 risk and, 66–67, 69–72, 74–75, 80, 95, 117, 145, 174 securitization in, 69, 74 see also mortgages London, 53, 84 housing in, 88–90 see also City of London Long-Term Capital Management (LTCM): collapse of, 142, 162, 164–65, 230–31 derivatives and, 54–56, 80 loss aversion, 137 Lovelock, James, 231 Lowenstein, Roger, 161 Macmillan, Harold, 216 Madoff, Bernard, 105, 171, 191–92, 195 Mailer, Norman, 172 Manias, Panics, and Crashes (Kindleberger), 104 manufacturing, 4, 13, 58, 109, 229 and financial vs. industrial interests, 197, 199 Marxist analysis of, 15–16 stocks and, 148–49 market discipline, 183–84 Markopolos, Harry, 192 Markowitz, Harry, 147–49, 158 mark to market, 42, 105–6 Marx, Karl, 15–16 Maryland, housing in, 125–31 Masters, Blythe, 68, 121 mathematics, 5, 231 derivatives and, 47–48, 52–54, 115–17, 166 risk and, 46, 55–56, 74, 133, 136, 146–50, 154, 158, 160–67, 202 of share pricing, 147–48 Meriwether, John, 54 Merrill Lynch, 39, 77, 120, 190, 227 Merton, Robert, 54–55 microeconomics, 137 Minsky, Hyman, 104 Monetary Policy Committee, 178–79 money: assumptions based on primacy of, 202–4 cost of, 102–3 flows of, 7–9, 26 inconceivable amounts of, 8 Money Machine, The (Coggan), 25 Moody’s Investors Service, 62, 70, 114, 119, 208, 210 Morgan, John Pierpont, 20, 64 Morgan Stanley, 40, 64, 227 Morris, Charles, 42 mortgages, 38–40, 83–87, 89–95, 97–102, 110–32 in balance sheets, 27–28 balloon payments on, 100 and buy-to-let properties, 177 conforming, 112, 124 credit ratings and, 123–24, 126 of Cutter family, 126–27 defaults on, 159–60, 163, 165, 229 derivatives and, 38, 57–58, 75–76, 112–22, 132, 157–60, 172, 210–12 discriminatory practices and, 99–101, 127 durations of, 95 endowment, 86–87, 89–90, 146 Iceland’s economic crisis and, 10–11 interest and, 8, 58, 86, 89, 91–92, 95, 100, 102, 108, 110, 112–14, 122, 128, 145–46, 174, 176, 212 “liar,” 126, 132 “no doc,” 132 No Income, No Job or Assets (NINJA), 126 piggyback, 132 predatory lending and, 122, 127–32 regulation and, 99–100, 185 risk and, 145, 158–60, 163–65 sizes of, 92–94 subprime, 38, 75, 83, 100, 113–19, 122–25, 127, 132, 157–59, 165, 202, 210 see also houses, housing, home ownership Nasdaq, 104 nationalization, 24, 39–40, 228–30 New York Times, The, 77, 98, 208 “Night in Tunisia, A,” 45 Nikkei 225, 51–52, 54 9/11 terrorist attacks, 2, 107 Northern Rock, 5, 39, 94, 194, 206 Obama, Barack, 77, 205 regulation and, 188, 190, 223–24 Objectivism, 142–43, 173 oil, 3–4, 107–8, 148–49 “On Default Correlation” (Li), 116 options, 50–52, 151, 174, 184 how they work, 46–47, 50–51 Osaka exchange, 54 Pacioli, Luca, 26 panic of 1893, 64 panic of 1907, 20, 64 Parker, Charlie, 45 Paulos, John Allen, 8 pensions, 76–77, 165, 204 in balance sheets, 27–28, 31 Phillips, Julia, 199 politics, politicians, 5–6, 19–21, 23–25, 81, 118–19, 169–70, 176–78, 217–26, 228–32 AIG bailout and, 76–78 banks and, 25, 33, 43, 182, 186, 195, 202, 207, 211, 217, 228–31 bonds and, 29–30, 61–62, 103, 109, 118, 144, 176–77, 208–9 derivatives and, 57, 183–86 financial industry’s ascent and, 19–20 free-market capitalism and, 14–15, 19, 21, 23–24 housing and, 87–89, 91, 96–101, 177–78 Iceland’s economic crisis and, 9–10, 12, 24, 223 interest rates and, 102–3, 107–8, 172–80, 221 paying the bill and, 219–23 regulation and, 15, 19–21, 24, 169, 180–92, 195, 199, 201, 223–26 risk and, 142–43, 164–66, 174, 184 Ponzi, Charles, 105 Ponzi schemes, 191–92 poor, poverty, 3–4, 13, 21, 82, 179, 196 housing and, 100, 113, 118, 121–23, 126–27, 130–31, 163 pork bellies, 48–49 portfolio insurance, 151–52, 162 “Portfolio Selection” (Markowitz), 147 Posner, Richard A., 120, 174, 182, 193 Powell, Anthony, 62 price, prices, 105–11, 203 and banking-and-credit crisis, 216–18, 220 bonds and, 61, 63, 102–3, 108–10, 144 derivatives and, 38, 46–52, 54, 56, 75, 158–59, 166 of houses, 5, 28–29, 37–38, 61, 71, 86–91, 101, 109–11, 113, 115, 125, 157, 160, 164–66, 173–76, 194, 208 of oil, 3–4, 107–8, 148–49 risk and, 145–50, 158–59, 164–66 of stocks, 102, 105–6, 109–10, 147–51, 158, 174 of toxic assets, 37–38, 42 volatility of, 47–48, 148–50 “Pricing of Options and Corporate Liabilities, The” (Black and Scholes), 45, 47–48, 147 probabilities, 46, 55, 74, 115, 141, 145, 153–55, 160–63 profits, 20, 28, 104–6, 110, 192, 226–28, 230 banks and, 33, 35, 67, 78, 227–28 and benefits of debt, 59–60 derivatives and, 50, 54, 57, 63, 65, 106, 114, 121–22 Enron and, 105–6 regulation and, 204, 226 risk and, 150, 226 Protection of Homeowners in Foreclosure Act, 131 “Quiet Coup, The” (Johnson), 19–20, 185–86 Ragtime (Doctorow), 64 Rand, Ayn, 142–43, 173 Reagan, Ronald, 14, 19–20, 24, 142, 185 recessions, 42, 89, 94, 142, 171, 175, 219 regulation, deregulation, 15, 19–22, 24, 169, 180–202 banking and, 21, 33, 180–91, 194–96, 199–200, 202, 204–5, 208, 211, 223–27 bond ratings and, 208–9 derivatives and, 68, 70, 73, 153, 183–86, 200–201 framework and regime of, 189–92 market discipline and, 183–84 mortgages and, 99–100, 185 proposals for, 223–26 risk and, 143, 153, 164, 187–88, 191, 195, 202, 204–5, 212, 224, 226 in U.K., 21–22, 105n, 180–82, 194–96, 199–201, 218 in U.S., 181, 184–92, 195, 199–200, 223–24, 227 Reykjavík, 10, 12, 170 risk, risks, 49–58, 66–76, 133–36, 141–67, 211–12, 219 AIG and, 75–76 assessment of, 46, 55–56, 74, 133, 135–36, 141–43, 145–67, 187–88, 191, 202, 205, 212, 216, 226 banks and, 19, 34–37, 41, 133, 135–36, 143, 150–54, 156–57, 160, 165–66, 174, 187–88, 191–95, 202, 204–7, 216, 224, 226, 228, 230 bonds and, 61–63, 103, 118, 144, 154, 208 derivatives and, 46–47, 49–52, 54–55, 57–58, 66–75, 78–80, 114–15, 117–22, 151, 153, 158–60, 163, 166–67, 184–85, 205, 212 desirability of, 144, 146, 150, 206–7 diversification and, 146–48 Greenspan and, 142–43, 164–66, 174, 184 hedging of, 49–50, 52, 58, 115, 205 historical data and, 163, 166 housing and, 88, 94–97, 112–13, 125, 129, 145, 158–60, 163–65 investing and, 5, 68, 70, 88, 103, 144, 146–53, 158, 165, 184, 190 leverage and, 35–36 LTCM and, 55–56 overconcentration of, 72–73 regulation and, 143, 153, 164, 187–88, 191, 195, 202, 204–5, 212, 224, 226 securitization and, 69–70, 163, 165 of stairs, 134–35 VAR and, 151–57, 162–63 risk-adjusted return on capital (RAROC), 150–51 Ritholtz, Barry, 219–20 Robinson, Phillip, 128–31 Rogers, Jim, 221 Royal Bank of Scotland (RBS), 34–36, 120, 227 bailout of, 32, 40, 204 Russia, 3, 15–16, 18, 53 bond default of, 55–56, 162, 164–65 Salomon Brothers, 63 Sanford, Charles, 150 Santander, 40 savings, 28, 86, 107, 177, 179, 187 savings and loan crisis, 73, 185, 220 Scholes, Myron, 45, 47–48, 54–55, 147 Securities and Exchange Commission (SEC), 195 credit ratings and, 209–10 regulation and, 153, 186, 189–92 securitization, 20, 22, 200 derivatives and, 69–70, 74, 113–14, 117–19, 122, 212 risk and, 69–70, 125, 163, 165, 212, 224 selling, sales, 34, 42, 104, 174, 203 of bonds, 59, 61–63, 144 derivatives and, 46–50, 52, 56, 65, 67–68, 73–74, 120 of equity, 58–59 of houses, 28–29, 71, 89–90 risk and, 151–52, 165, 224 Shiller, Robert, 106, 145n, 194 Simon, David, 83–84 Singapore exchange, 54 Skilling, Jeffrey, 106 small numbers, law of, 137 Sociét Générale, 51, 77 solvency, insolvency, 28–29 of banks, 36–38, 40–43, 64, 74–75, 120 Spain, 15, 40, 177, 214 contracting economy of, 222–23 housing in, 92, 110 special purpose vehicles (SPVs), 70, 120 stairs, deaths caused by, 134–35 Standard & Poor’s (S&P), 62, 114, 151, 209 statistics, 160–62 Stefánsdóttir, Rakel, 9–10, 12 stock market, stocks, 22, 54–55, 61, 76, 80, 101–11, 115, 226 bubbles and implosions in, 3, 42, 103–9, 142, 175–76 derivatives and, 50–52, 54 investing in, 59, 73, 101–7, 111, 146–52, 158, 175, 192 new-economy, 103 1929 crash of, 152, 199, 213 October 1987 crash of, 142, 151–52, 161–62, 164–65 prices of, 102, 105–6, 109–10, 147–51, 158, 174 structured investment vehicles (SIVs), 120 Summa de Arithmetica (Pacioli), 26 Summers, Lawrence, 43, 74, 188 Taleb, Nassim, 53, 155–56 Tax Reform Act of 1986 (TRA), 100 technology, 42, 104, 149, 155, 166 terrorism, 2, 12, 18, 107 Tett, Gillian, 121, 193 Thatcher, Margaret, 199, 217, 222 free-market capitalism and, 14, 21, 24 on housing, 87, 91, 98 regulation and, 21, 195–96 torture, end of ban on, 18 tranching, 117–18, 122 Treasury, British, 181–82 Treasury, U.S., 43, 54, 64, 74, 76–78 AIG bailout and, 76, 78 regulation and, 188–90 Treasury bills (T-bills), 29–30, 62, 103, 118, 144, 208 China’s investment in, 109, 176–77 Trichet, Jean-Claude, 92 Trillion Dollar Meltdown, The (Morris), 42 Troubled Assets Relief Program (TARP), 37, 189 Turner, Adair, 181 Tversky, Amos, 136–38, 141 UBS, 36, 120 uncertainty, 96 fair value theory and, 147–48 risk and, 55–56, 153, 163 United Kingdom, 9, 11–12, 18, 28–29, 61, 122–24, 134, 139, 194–202, 216–18 banking in, 5, 11, 32–36, 38–40, 51–54, 76–77, 89, 94, 120, 146, 180, 194–96, 199, 202, 204–6, 211–12, 217, 227–28 bill of, 220–22, 224 and City of London, 21–22, 32, 195–97, 200, 217–18 credit ratings and, 123–24, 209 derivatives and, 72, 200–201 financial vs. industrial interests in, 196–99 free-market capitalism in, 14–15, 21, 230 GDP of, 32, 214, 220 Goodwin’s pension and, 76–77 housing in, 38, 87–98, 110, 122, 177–78 interest rates in, 102, 177–80 personal debt in, 221–22 prosperity of, 214, 216 regulation in, 21–22, 105n, 180–82, 194–96, 199–201, 218 United Nations, 4 United States, 17–22, 34, 62–71, 120–31, 134n, 165, 199–201 AIG bailout and, 76–78 banks of, 36–37, 39–40, 43, 63–71, 73, 75, 77–78, 84, 116, 120–21, 127, 150, 152, 163, 183, 185, 190, 195, 204, 211–12, 219–20, 225, 227–28 bill of, 219–20 China’s investment in, 109, 176–77 credit and, 109, 123–24, 195, 208–9, 211 free-market capitalism in, 14–15, 230 housing in, 37, 82–86, 95, 97–101, 109–10, 114–15, 122, 125–31, 157–58, 163 interest rates in, 102, 107–8, 173–77 regulation in, 181, 184–92, 195, 199–200, 223–24, 227 urban desolation in, 81–86 value, values, 42, 74–75, 78–80, 103–4, 179, 181, 217–18, 220, 227 bonds and, 61, 103 derivatives and, 38, 48–49, 185, 201 housing and, 28–29, 71, 90, 92–95, 111, 176 investing and, 60–61, 104, 198 LTCM and, 55–56 notional, 38, 48–49, 80 value at risk (VAR), 151–57, 162–63 Vietnam War, 18, 220 Viniar, David, 163 volatility, 20, 158 risk and, 47–48, 148–50, 161 Volcker, Paul, 20 Waldrow, Mary, 127 Wall Street, 22, 53, 64, 129, 188 Washington Post, The, 18 wealth, 4, 10, 19–21, 64, 204, 206 financial industry’s ascent and, 20–21 in free-market capitalism, 15, 19, 230 housing and, 87, 90, 121 Keynes’s predictions on, 214–15 in West, 218–19 Weatherstone, Dennis, 152 Wells Fargo, 84, 127 Wessex Water, 105n West, 14–18, 43, 213, 231 conflict between Communist bloc and, 16–18 free-market capitalism in, 14–15, 17, 21, 23 wealth in, 218–19 wheat, 49n, 52 When Genius Failed (Lowenstein), 161 Williams, John Burr, 147 Wilson, Lashawn, 130–31 Wire, The, 83–84 World Bank, 58, 65, 69 * GDP, which will be mentioned quite a few times in this story, sounds complicated but isn’t: it’s nothing more than the value of all the goods and services produced in an economy.


pages: 260 words: 77,007

Are You Smart Enough to Work at Google?: Trick Questions, Zen-Like Riddles, Insanely Difficult Puzzles, and Other Devious Interviewing Techniques You ... Know to Get a Job Anywhere in the New Economy by William Poundstone

affirmative action, Albert Einstein, big-box store, Buckminster Fuller, car-free, cloud computing, creative destruction, en.wikipedia.org, full text search, hiring and firing, index card, Isaac Newton, Johannes Kepler, John von Neumann, lateral thinking, loss aversion, mental accounting, new economy, Paul Erdős, RAND corporation, random walk, Richard Feynman, rolodex, Rubik’s Cube, Silicon Valley, Silicon Valley startup, sorting algorithm, Steve Ballmer, Steve Jobs, The Spirit Level, Tony Hsieh, why are manhole covers round?, William Shockley: the traitorous eight

“It was my first instinctive choice and if I was wrong, oh well. But if I switched and was wrong it would be that much worse.” “I would really regret it if I switched and lost. It’s best to stay with your first choice.” These are expressions of loss aversion. It’s universal human nature to recoil from a decision that might leave one worse off, even when the odds are favorable. “Better safe than sorry.” Anyone who invents new products would do well to keep this in mind. The consumer thinking of switching boxes or brands may be motivated by reasons that have nothing to do with logic. Math geniuses are as loss averse as everyone else. It’s said that the famed mathematician Paul Erdös got this puzzle wrong the first time he heard it. “Even Nobel physicists systematically give the wrong answer,” said the psychologist Massimo Piattelli-Palmarini, “and… they insist on it, and they are ready to berate in print those who propose the right answer.” ?


pages: 290 words: 76,216

What's Wrong with Economics? by Robert Skidelsky

"Robert Solow", additive manufacturing, agricultural Revolution, Black Swan, Bretton Woods, business cycle, Cass Sunstein, central bank independence, cognitive bias, conceptual framework, Corn Laws, corporate social responsibility, correlation does not imply causation, creative destruction, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, disruptive innovation, Donald Trump, full employment, George Akerlof, George Santayana, global supply chain, global village, Gunnar Myrdal, happiness index / gross national happiness, hindsight bias, Hyman Minsky, income inequality, index fund, inflation targeting, information asymmetry, Internet Archive, invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, knowledge economy, labour market flexibility, loss aversion, Mark Zuckerberg, market clearing, market friction, market fundamentalism, Martin Wolf, means of production, moral hazard, paradox of thrift, Pareto efficiency, Paul Samuelson, Philip Mirowski, precariat, price anchoring, principal–agent problem, rent-seeking, Richard Thaler, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, shareholder value, Silicon Valley, Simon Kuznets, survivorship bias, technoutopianism, The Chicago School, The Market for Lemons, The Nature of the Firm, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Thorstein Veblen, transaction costs, transfer pricing, Vilfredo Pareto, Washington Consensus, Wolfgang Streeck, zero-sum game

Behavioural economists identify the following ‘systemic’ errors that people make. 1. Survivorship bias We tend to look only at what was successful. Think of a newspaper article that claims it can help you imitate Mark Zuckerberg’s morning routine. The obvious implication is that you too could become a billionaire if you just wore grey t-shirts and ate the right breakfast, but this ignores the multitudes of non-billionaires doing just that. 2. Loss aversion It is fairly well established that people hate losing something more than they love gaining it. Dropping a $10 note is more bitter than finding one is sweet. We are hard-wired, to some extent, to hold on to what we’ve got. Students given coffee mugs free from the campus bookstore will not part with them for $6 even though this junk fell out of the sky, and had they desired them they could have got them at the nearby store for the price of $6. 3.

The inverse to this is automation bias: thinking that automated instructions must be correct even when common sense tells you they are wrong. A bunch of Japanese tourists drove their car into the sea because their satnav told them they were on a road. Airplane crashes have happened because pilots trusted their faulty navigation systems rather than the evidence of their eyes. 6. Sunk cost fallacy This is a combination of anchoring and loss aversion. People will keep on ploughing money into a failed investment, because they can’t face the psychological pain of admitting that it had failed, or carry on waging a war that they should have abandoned long ago, because they cannot bring themselves to admit that it was in vain. 7. Hindsight bias This is central to human thinking and makes the social and economic worlds appear much more predictable and less erratic than they really are.


pages: 483 words: 141,836

Red-Blooded Risk: The Secret History of Wall Street by Aaron Brown, Eric Kim

activist fund / activist shareholder / activist investor, Albert Einstein, algorithmic trading, Asian financial crisis, Atul Gawande, backtesting, Basel III, Bayesian statistics, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Black Swan, business cycle, capital asset pricing model, central bank independence, Checklist Manifesto, corporate governance, creative destruction, credit crunch, Credit Default Swap, disintermediation, distributed generation, diversification, diversified portfolio, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, experimental subject, financial innovation, illegal immigration, implied volatility, index fund, Long Term Capital Management, loss aversion, margin call, market clearing, market fundamentalism, market microstructure, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, natural language processing, open economy, Pierre-Simon Laplace, pre–internet, quantitative trading / quantitative finance, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, road to serfdom, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, special drawing rights, statistical arbitrage, stochastic volatility, stocks for the long run, The Myth of the Rational Market, Thomas Bayes, too big to fail, transaction costs, value at risk, yield curve

The effect has been demonstrated in many controlled and real-world settings, with both humans and animals, including birds and insects. There is no doubt that it is both real and important. Among other things, it explains part of loss aversion. Losing something you have is more painful than getting something equivalent is pleasurable. This is not inconsistent with utility theory, but it requires that individuals’ utility function change as they acquire or lose goods. The simple version of utility theory that says all risk is bad cannot accommodate that, but sophisticated modern utility theory has no difficulty. Why would evolution allow animals—including humans—to hold inconsistent values? The weight of the evidence is that loss aversion evolved to reduce intraspecies fighting and to allow investment. Animal behaviorists have identified many examples of competition among individuals in the same species for resources: territory, nests, pools of water, even shafts of sunlight breaking through trees.

(Livio) Jackknife, the Bootstrap, and Other Resampling Plans, The (Efron) Jackpot Nation (Hoffer) Jessup, Richard John Bogle on Investing (Bogle) Johnson, Barry Johnson, Simon JPMorgan Junk bonds Kahneman, Daniel Kamensky, Jane Kaplan, Michael Kassouf, Sheen Kelly, John Kelly bets/levels of risk Kelly principles/investors Keynes, John Maynard Key performance indicators (KPIs) Key risk indicators (KRIs) King of a Small World (Bennet) Korajczyk, Robert Knetsch, Jack Knight, Frank Kraitchik, Maurice Krüger, Lorenz Laplace, Pierre-Simon Lehman Brothers Leitzes, Adam Lepercq de Neuflize Leverage Levine, David Levinson, Horace Lewis, Michael Limits of Safety, The (Sagan) Liquidity Livio, Mario Logic of Failure, The (Dorner) Long-Run Collaboration on Games with Long-Run Patient Players, A (Fudenberg and Levine) Loss aversion Lowenstein, Roger Mackay, Charles Madoff, Bernie Mallaby, Sebastian Man with the Golden Arm, The (Bennet) Managed futures Managing risk Mandelbrot, Benoit Market: “beating” the efficiency (see also Efficient markets theory) equilibrium (see Equilibrium) portfolio prices return sympathy Mark-to-market accounting Markowitz, Harry.


pages: 511 words: 132,682

Competition Overdose: How Free Market Mythology Transformed Us From Citizen Kings to Market Servants by Maurice E. Stucke, Ariel Ezrachi

affirmative action, Airbnb, Albert Einstein, Andrei Shleifer, Bernie Sanders, Boeing 737 MAX, Cass Sunstein, choice architecture, cloud computing, commoditize, corporate governance, Corrections Corporation of America, Credit Default Swap, crony capitalism, delayed gratification, Donald Trump, en.wikipedia.org, George Akerlof, gig economy, Goldman Sachs: Vampire Squid, Google Chrome, greed is good, hedonic treadmill, income inequality, income per capita, information asymmetry, invisible hand, job satisfaction, labor-force participation, late fees, loss aversion, low skilled workers, Lyft, mandatory minimum, Mark Zuckerberg, market fundamentalism, mass incarceration, Menlo Park, meta analysis, meta-analysis, Milgram experiment, mortgage debt, Network effects, out of africa, payday loans, Ponzi scheme, precariat, price anchoring, price discrimination, profit maximization, profit motive, race to the bottom, Richard Thaler, ride hailing / ride sharing, Robert Bork, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, Shoshana Zuboff, Silicon Valley, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Stanford prison experiment, Stephen Hawking, The Chicago School, The Market for Lemons, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, Thomas Davenport, Thorstein Veblen, Tim Cook: Apple, too big to fail, transaction costs, Uber and Lyft, uber lyft, ultimatum game, Vanguard fund, winner-take-all economy

Once we’ve got that price of $26 in our head, we fail to adjust our “perception of the ‘value of the offer’ sufficiently as more costs are revealed.”32 Drip pricing also taps into a second weakness. Although as we shop for a hotel room we haven’t actually purchased that reservation for $26, some part of us feels like we have and we now feel attached to it. With drip pricing, a former chief economist of the UK competition authority noted, “Consumers feel they’ve already made the decision to purchase [which] creates loss aversion—consumers have committed time and effort to the search before being hit with extra charges.”33 A third weakness is something we often perceive as a strength, namely commitment and consistency. Here, after having invested a lot of time and effort into this purchase, we want to see the purchase through to its end.34 Economists call this the sunk cost fallacy. Finally, drip pricing taps into brain fatigue.

See also CoreCivic Costco and other club stores, 102–3 cream skimming, 169–70, 175, 183–87 credit card industry, 68, 69, 70–71, 75–77 credit default swaps, 128 criminal sentencing, 80–81, 176–77 crony capitalism, 160, 163, 230, 285 Cruz, Ted, 266 cultural conditioning college as route to social mobility, 29–30 competition delivers quality at a low price, 47–48, 49 competition is always good, x, 284 embarrassment for gullibility, 70 and escalation paradigm, 35–36 lifelong superior achievement goal, 32–33 to love competition, 125 to not compete, 122 self-interest, 71, 235–36 and status competition, 28 See also human nature culture, x–xi Dalai Lama, 253 Dale, Stacy, 36–37 D’Angelo, Jonathan, 112–13 Dartmouth College, 25 Darwin, Charles, 39 data for Amazon’s personal recommendations, 105–6, 107 analytical power of, 218–19 children’s data gleaned for advertisers, 193–95 college scorecard data, 300–304, 318n86 on consumers’ behavior, 87–91, 204–5, 207–9 Gamemakers attract bidders/advertisers, 207–9 Gamemakers’ harvesting techniques, 194, 203–7 in Las Vegas, 87–91 dating services, online overview, 108–9 competition levels, 109–12, 111 InterActiveCorp, 109–11, 111, 115–16 and marriage, 114–15 profiting from choice overload, 113–14, 115–16 slow dating, 117 deadbeat customers, 70–71 Dear Genevieve effect, 12–15, 16, 19–20, 38–39 death bonds, 245 decision aids for choice overload, 101–2 de-escalating the arms race colleges and universities, 25–27, 40, 133–34 collegiate sports, 134–38, 140–41 students and parents, 27–34, 40 Deloitte, 277 deregulation of banks, 126–30 derivatives market, 261–63 diaper apps, 197 digital ad market, 210 diminishing returns, 96–97 dissent, noncompliance, and change, 284–87 divergence of individual and collective interests, 12–20, 39–40, 242–43, 263 DOJ (US Department of Justice), 128, 172–73, 174, 232 do not track features on mobile phones, 212–13 Dostoyevsky, Fyodor, 71 drip pricing overview, 147 and anchor value, 80–81 and brain fatigue, 81–82 Caesars opposition to, 84–87 casino lobbyists combat FTC’s plan, 150–52 vs. consumer’s ability to compare prices, 155–57 consumers’ loss aversion, 81 countries with laws against, 148 FTC attempt to legalize, 148–50 in hotels, 78–80, 82–84, 147, 148–54 lobbyists use competition ideology, 150–52 and sunk cost fallacy, 81 Duhigg, Charles, 227 Duke University, 16–17, 24 dynamic ads, 204–5 Easterbrook, Frank H., 234–35 Economist, 197 Eliot, T. S., 20 Elliott, Chris, 46–47 Ellis, George, xi–xii, 256–58, 257 Enron, 246–47 ethical values.

., 36–37 Krugman, Paul, 128–29 kudzu and kudzu-ing overview, xiii, 146–47 competition ideology for deregulating, 155–57 lack of competition in private prison market, 176–77 with lobbying, money, and competition ideology, 160 politicians fighting legislation to end price dripping in the US, 152–53 by Trump, to financial regulations to protect consumers, 268–69, 285–86 and UK privatizing some health services, 184–87 labor and pressure to lower prices, 54 laptop cameras and data harvesting, 214 Lay, Ken, 246 lemon markets, 63–64, 124 Lepper, Mark, 98–99, 100 life satisfaction levels, 247–49, 252 Little Ivies staying out of collegiate sports arms race, 138–39, 140 lobbyists, 146–61 overview, xiii casino lobbyists oppose ending drip pricing, 150–51 and Citizens United case in US Supreme Court, 155 kudzu and kudzu-ing the competition, 146–47 and money suffocating democratic values, 160 for private prisons, 173–76 local economies, supporting, 289–91 loss aversion, 81 low-value customers, 87 Mactaggart, Alastair, 286 MacTavish, Craig, 4 marginal benefit and marginal cost, 96–97 market economy competition ideologues relying on, 127 derivatives market, 261–63 farmers markets, 287–89 regulation of the market, 260 social capital necessary for, 249–51 social outcome of, 124, 125 trust and fairness as foundation, 244 marketing, 59–60, 67–68 marriage and online dating, 114–15 “Massive-Scale Emotional Contagion” study by FB, 219 Match.com, 108–9, 113–14 matriculation from elite private schools, 31–34, 296–98 McCaskill, Claire, 150, 154 McDonald’s, 52 McNamee, Roger, 199–200 measuring success colleges and universities, 15, 34, 38–39 InterActiveCorp, 109–11, 111, 115–16 public school ranking system, 7–9, 282 Medicaid expansion by states, 286 mental health and stress of superior achievement goal, 34 MGM Grand Hotel, Las Vegas, 154 middle class net worth, 160 Milgram, Stanley, 279–82, 285 Mill, John Stuart, 94 minimum wage increases by states, 286 mobile phones, 107–8, 196–98, 212–13 Moore, Don, 35 morality continuum, 257–58.


pages: 287 words: 80,050

The Wisdom of Frugality: Why Less Is More - More or Less by Emrys Westacott

Airbnb, back-to-the-land, Bertrand Russell: In Praise of Idleness, Bonfire of the Vanities, carbon footprint, clean water, Community Supported Agriculture, corporate raider, Daniel Kahneman / Amos Tversky, dark matter, Diane Coyle, discovery of DNA, Downton Abbey, dumpster diving, financial independence, full employment, greed is good, happiness index / gross national happiness, haute cuisine, hedonic treadmill, income inequality, invisible hand, Isaac Newton, loss aversion, McMansion, means of production, move fast and break things, move fast and break things, negative equity, New Urbanism, paradox of thrift, Ralph Waldo Emerson, Thales and the olive presses, Thales of Miletus, the market place, The Spirit Level, Thorstein Veblen, Upton Sinclair, Veblen good, Zipcar

And he won’t allow the second to value or admire anything but wealth and wealthy people or to have any ambition other than the acquisition of wealth or whatever might contribute to getting it.8 The “sunk cost” fallacy: Research by psychologists Daniel Kahneman and Amos Tversky in the 1970s led them to conclude that for most human beings a concern to avoid losses is a more powerful motivator than the desire to realize gains. Many other psychologists have followed in their footsteps and investigated the phenomenon of loss aversion. A study by Hal Arkes and Catherine Blumer is representative and revealing. Participants in their study were asked to imagine that they had bought two nonrefundable tickets, a $100 ticket for a skiing trip to Michigan, and a $50 ticket for a skiing trip to Wisconsin. They were then told that the dates of these trips conflicted, so they could go on only one of them. Even though they were informed that the Wisconsin trip would be the more enjoyable, most participants opted for the trip to Michigan.

See self-sufficiency individualism, 173, 284 inequality, 151–52, 172–73, 218, 240, 285 Irvine, William, 7 Islam, 31, 78 It’s a Wonderful Life, 97 Jackson, Michael, 169 Jains, 31, 272 Jesus, 44, 45, 63, 103, 104, 141, 201, 283 Johnson, Samuel, 10, 65 Judaism, 31, 78 Kahneman, Daniel, 144, 153, 222 Kant, Immanuel, 35, 273 Kardashian, Kim, 214 karma, 74 Kazez, Jean, 88 Keynes, John Maynard, 80, 166, 241, 242 kibbutzim, 22 Kozlowski, Dennis, 168–69 Krugman, Paul, 226 Kublai Kahn, 147 Lafargue, Paul, 80, 81 Laham, Simon, 114 leisure, 77, 242. See also work Lichtenberg, Judith, 246 Linder, Staffan, 242 living cheaply, 14–18, 21, 37, 276. See also frugality; simple living locavorism, 261–64 loss aversion, 144 Louv, Richard, 132 luxuries: definition of, 177–78. See also luxury luxury, 33, 140, 146–47, 158–59, 171, 216; dangers of, 52, 55, 56, 111–16, 208–10 Lycurgus, 53 magnificence, 193 Mahavira, 32 Mandela, Nelson, 64 Mandeville, Bernard, 158–59, 216 Marcus Aurelius, 7, 24, 50, 57, 75, 98, 103, 117, 120, 148, 275 Marie Antoinette, 169 Marley, Bob, 102–4 Marx, Karl, 83, 87, 212, 281–82 materialism, 68, 99, 167, 173 material security: of modern life, 201–2, 204–5, 253 McCartney, Paul, 161 McCoy, Travie, 161 Mead, Rebecca, 198 Menedemus, 63 mercenariness, 142–44 Mill, John Stuart, 69–71, 74 Minnelli, Liza, 168–69, 177 Les Misérables, 63 miserliness, 143 Mittal, Lakshmi, 197 monasteries, 22, 31, 35, 45, 56 monastic orders, 53.


pages: 272 words: 83,798

A Little History of Economics by Niall Kishtainy

"Robert Solow", Alvin Roth, British Empire, Capital in the Twenty-First Century by Thomas Piketty, car-free, central bank independence, clean water, Corn Laws, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, Eugene Fama: efficient market hypothesis, first-price auction, floating exchange rates, follow your passion, full employment, George Akerlof, greed is good, Hyman Minsky, inflation targeting, invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, loss aversion, market clearing, market design, means of production, moral hazard, Nash equilibrium, new economy, Occupy movement, Pareto efficiency, Paul Samuelson, prisoner's dilemma, RAND corporation, rent-seeking, Richard Thaler, rising living standards, road to serfdom, Robert Shiller, Robert Shiller, Ronald Reagan, sealed-bid auction, second-price auction, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, trade route, Vickrey auction, Vilfredo Pareto, washing machines reduced drudgery, wealth creators, Winter of Discontent

All economics is about behaviour, of course, but behavioural economics was new because it built its theories around the quirks in people’s actual decision-making, rather than simply assuming that they were completely rational. One quirk is that people weigh up gains and losses differently. Rationally, a gain of $50 should exactly offset a loss of $50. However, people seem to hate losses more than they love gains. When he was still a student, the behavioural economist Richard Thaler (b. 1945) noticed ‘loss aversion’ in one of his own economics professors! The professor, a wine lover, was willing to pay a high price for a bottle of a certain wine to add to his collection. But he really hated giving one up: even if you offered him three times what he’d paid, he wouldn’t sell a bottle to you. Thaler and Kahneman did an experiment on a group of people to see what was going on. Some of them were given a mug and then asked how much they’d sell it for.

(i), (ii) Kerala (India) (i) Keynes, John Maynard (i), (ii), (iii), (iv), (v), (vi) Keynesian theory (i), (ii), (iii) Klemperer, Paul (i) Krugman, Paul (i), (ii) Kydland, Finn (i), (ii) labour (i) in ancient Greece (i) and market clearing (i) women as unpaid (i) labour theory of value (i), (ii) laissez-faire (i) landowners (i), (ii), (iii) Lange, Oskar (i) law of demand (i), (ii) leakage of spending (i) Lehman Brothers (i) leisure class (i) leisured, women as (i) Lenin, Vladimir Ilyich (i), (ii) Lerner, Abba (i) Lewis, Arthur (i) Lincoln, Abraham (i) List, Friedrich (i) loss aversion (i) Lucas, Robert (i), (ii) MacKay, Charles (i) Macmillan, Harold (i) macro/microeconomics (i) Malaysia, and speculators (i) Malthus, Thomas (i), (ii), (iii) Malynes, Gerard de (i), (ii) manufacturing (i), (ii) division of labour (i) see also Industrial Revolution margin (i) marginal costs (i), (ii) marginal principle (i), (ii), (iii) marginal revenue (i) marginal utility (i), (ii) market, the (i) market clearing (i) market design (i) market failure (i), (ii), (iii), (iv) ‘Market for Lemons, The’ (Akerlof) (i) market power (i) markets, currency (i), (ii) Marshall, Alfred (i), (ii), (iii), (iv), (v) Marx, Karl (i), (ii), (iii), (iv), (v), (vi), (vii) Marxism (i) mathematics (i), (ii), (iii) means of production (i) mercantilism (i), (ii) Mesopotamia (i) Mexico, pegged currency (i) micro/macroeconomics (i) Microsoft (i) Midas fallacy (i) minimum wage (i) Minsky, Hyman (i) Minsky moment (i), (ii) Mirabeau, Marquis de (i), (ii), (iii) Mises, Ludwig von (i), (ii), (iii), (iv) mixed economies (i), (ii) Mobutu Sese Seko (i) model villages (i) models (economic) (i), (ii), (iii), (iv) modern and traditional economies (i), (ii) monetarism (i) monetary policy (i), (ii) money (i), (ii), (iii), (iv), (v), (vi) see also coins; currency money illusion (i) money wages (i) moneylending see usury monopolies (i), (ii) monopolistic competition (i), (ii) monopoly, theory of (i) monopoly capitalism (i), (ii), (iii) monopsony (i) moral hazard (i), (ii) multiplier (i) Mun, Thomas (i), (ii), (iii) Muth, John (i) Nash, John (i), (ii) Nash equilibrium (i) national income (i), (ii), (iii), (iv), (v) National System of Political Economy (List) (i) Nelson, Julie (i) neoclassical economics (i) net product (i) Neumann, John von (i) New Christianity, The (Saint-Simon) (i) new classical economics (i) New Harmony (Indiana) (i) New Lanark (Scotland) (i) Nkrumah, Kwame (i), (ii) non-rival good (i) Nordhaus, William (i), (ii) normative economics (i), (ii) Obstfeld, Maurice (i) Occupy movement (i) oligopolies (i) opportunity cost (i), (ii) organ transplant (i) output per person (i) Owen, Robert (i) paper money (i), (ii) Pareto, Vilfredo (i) pareto efficiency (i), (ii) pareto improvement (i) Park Chung-hee (i) partial equilibrium (i) pegged exchange rate (i) perfect competition (i), (ii), (iii), (iv), (v) perfect information (i) periphery (i) phalansteries (i) Phillips, Bill (i) Phillips curve (i), (ii), (iii), (iv), (v), (vi), (vii) physiocracy (i), (ii) Pigou, Arthur Cecil (i), (ii), (iii) Piketty, Thomas (i), (ii), (iii) Plato (i), (ii), (iii) policy discretion (i) Ponzi, Charles (i) Ponzi finance (i) population and food supply (i), (ii), (iii) of women (i) positive economics (i) poverty (i), (ii), (iii), (iv), (v) in Cuba (i) Sen on (i) and utopian thinkers (i) Prebisch, Raúl (i) predicting (i) Prescott, Edward (i), (ii) price wars (i), (ii) primary products (i) prisoners’ dilemma (i) private costs and benefits (i) privatisation (i) productivity (i), (ii), (iii) profit (i), (ii), (iii), (iv) and capitalism (i), (ii) proletariat (i), (ii) property (private) (i), (ii), (iii), (iv), (v) and communism (i), (ii), (iii), (iv) protection (i), (ii), (iii) provisioning (i) public choice theory (i) public goods (i) quantity theory of money (i) Quesnay, François (i) Quincey, Thomas de (i), (ii) racism (i) Rand, Ayn (i) RAND Corporation (i), (ii) rate of return (i), (ii) rational economic man (i), (ii), (iii), (iv), (v) rational expectations (i), (ii), (iii), (iv), (v) real wages (i), (ii), (iii) recession (i) and governments (i), (ii), (iii) Great Recession (i) Keynes on (i), (ii) Mexican (i) redistribution of wealth (i) reference points (i) relative poverty (i) rent on land (i), (ii), (iii) rents/rent-seeking (i) resources (i), (ii) revolution (i), (ii), (iii), (iv) Cuban (i) French (i), (ii), (iii), (iv) Russian (i), (ii) Ricardo, David (i), (ii), (iii) risk aversion (i) Road to Serfdom, The (Hayek) (i) robber barons (i) Robbins, Lionel (i) Robinson, Joan (i) Roman Empire (i) Romer, Paul (i) Rosenstein-Rodan, Paul (i) Roth, Alvin (i), (ii) rule by nature (i) rules of the game (i) Sachs, Jeffrey (i) Saint-Simon, Henri de (i) Samuelson, Paul (i), (ii) savings (i), (ii) and Say’s Law (i) Say’s Law (i) scarcity (i), (ii), (iii), (iv), (v), (vi) Schumpeter, Joseph (i), (ii) sealed bid auction (i) second price auction (i) Second World War (i) securitisation (i) self-fulfilling crises (i) self-interest (i) Sen, Amartya (i), (ii) missing women (i), (ii), (iii) services (i) shading bids (i), (ii) shares (i), (ii), (iii), (iv), (v), (vi) see also stock market Shiller, Robert (i), (ii) signalling (i) in auctions (i) Smith, Adam (i), (ii), (iii), (iv), (v) social costs and benefits (i) Social Insurance and Allied Services (Beveridge) (i) social security (i), (ii) socialism (i), (ii), (iii), (iv), (v) socialist commonwealth (i) Socrates (i) Solow, Robert (i) Soros, George (i), (ii), (iii) South Africa, war with Britain (i) South Korea, and the big push (i) Soviet Union and America (i) and communism (i), (ii) speculation (i) speculative lending (i) Spence, Michael (i) spending government (fiscal policy) (i), (ii), (iii), (iv), (v), (vi), (vii) and recessions (i), (ii) and Say’s Law (i) see also investment stagflation (i), (ii) Stalin, Joseph (i) standard economics (i), (ii), (iii), (iv) Standard Oil (i) Stiglitz, Joseph (i) stock (i) stock market (i), (ii), (iii), (iv), (v) stockbrokers (i) Strassmann, Diana (i), (ii) strategic interaction (i), (ii) strikes (i) subprime loans (i) subsidies (i), (ii) subsistence (i) sumptuary laws (i) supply curve (i) supply and demand (i), (ii), (iii), (iv) and currencies (i) and equilibrium (i), (ii) in recession (i), (ii), (iii) supply-side economics (i) surplus value (i), (ii) Swan, Trevor (i) tariff (i) taxes/taxation (i) and budget deficit (i) carbon (i) and carbon emissions (i) and France (i) and public goods (i) redistribution of wealth (i) and rent-seeking (i) technology as endogenous/exogenous (i) and growth (i) and living standards (i) terms of trade (i) Thailand (i) Thaler, Richard (i) theory (i) Theory of the Leisure Class, The (Veblen) (i) Theory of Monopolistic Competition (Chamberlain) (i) Thompson, William Hale ‘Big Bill’ (i) threat (i) time inconsistency (i), (ii) time intensity (i) Tocqueville, Alexis de (i) totalitarianism (i) trade (i), (ii), (iii) and dependency theory (i) free (i), (ii), (iii) trading permit, carbon (i) traditional and modern economies (i), (ii) transplant, organ (i) Treatise of the Canker of England’s Common Wealth, A (Malynes) (i) Tversky, Amos (i), (ii) underdeveloped countries (i) unemployment in Britain (i) and the government (i) and the Great Depression (i) and information economics (i) and Keynes (i) and market clearing (i) and recession (i) unions (i), (ii) United States of America and free trade (i) and growth of government (i) industrialisation (i) and Latin America (i) Microsoft (i) recession (i), (ii) and the Soviet Union (i) and Standard Oil (i) stock market (i) wealth in (i) women in the labour force (i) unpaid labour, and women (i) usury (i), (ii), (iii) utility (i), (ii), (iii), (iv) utopian thinkers (i), (ii) Vanderbilt, Cornelius (i), (ii) Veblen, Thorstein (i), (ii), (iii) velocity of circulation (i), (ii) Vickrey, William (i) wage, minimum (i) Walras, Léon (i) Waring, Marilyn (i) wealth (i) and Aristotle (i), (ii) and Christianity (i) Piketty on (i) and Plato (i) Smith on (i) Wealth of Nations, The (Smith) (i), (ii) welfare benefits (i), (ii), (iii), (iv) welfare economics (i) Who Pays for the Kids?


pages: 261 words: 86,905

How to Speak Money: What the Money People Say--And What It Really Means by John Lanchester

asset allocation, Basel III, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Swan, blood diamonds, Bretton Woods, BRICs, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, commoditize, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Dava Sobel, David Graeber, disintermediation, double entry bookkeeping, en.wikipedia.org, estate planning, financial innovation, Flash crash, forward guidance, Gini coefficient, global reserve currency, high net worth, High speed trading, hindsight bias, income inequality, inflation targeting, interest rate swap, Isaac Newton, Jaron Lanier, joint-stock company, joint-stock limited liability company, Kodak vs Instagram, liquidity trap, London Interbank Offered Rate, London Whale, loss aversion, margin call, McJob, means of production, microcredit, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, negative equity, neoliberal agenda, New Urbanism, Nick Leeson, Nikolai Kondratiev, Nixon shock, Northern Rock, offshore financial centre, oil shock, open economy, paradox of thrift, plutocrats, Plutocrats, Ponzi scheme, purchasing power parity, pushing on a string, quantitative easing, random walk, rent-seeking, reserve currency, Richard Feynman, Right to Buy, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, sovereign wealth fund, Steve Jobs, survivorship bias, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, trickle-down economics, Washington Consensus, wealth creators, working poor, yield curve

Instead of the big broad models used in economics, in which “rational actors” behave in ways designed to “maximize their utility,” behavioral economics studies the kinds of calculations people make in real life, with a particular emphasis on things we do that are demonstrably not rational in the strict economic sense. An example is “loss aversion,” in which people are provably more unwilling to take risks that involve losses than to take risks involving gains, even when the outcomes are, in mathematical terms, identical. The fact that people don’t always behave rationally may not come as news in the wider world, but the intellectual challenge provided to conventional economics by behavioral economics is big and important. It’s also a field that offers useful takeaways for the ordinary person, because you can catch yourself doing some of the things described by behavioral economists, such as loss aversion and “hindsight bias,” i.e., the tendency to explain things that happened in terms of how they turned out, rather than how they seemed at the time.


pages: 1,351 words: 385,579

The Better Angels of Our Nature: Why Violence Has Declined by Steven Pinker

1960s counterculture, affirmative action, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, availability heuristic, Berlin Wall, Bonfire of the Vanities, British Empire, Broken windows theory, business cycle, California gold rush, Cass Sunstein, citation needed, clean water, cognitive dissonance, colonial rule, Columbine, computer age, conceptual framework, correlation coefficient, correlation does not imply causation, crack epidemic, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, demographic transition, desegregation, Doomsday Clock, Douglas Hofstadter, Edward Glaeser, en.wikipedia.org, European colonialism, experimental subject, facts on the ground, failed state, first-past-the-post, Flynn Effect, food miles, Francis Fukuyama: the end of history, fudge factor, full employment, George Santayana, ghettoisation, Gini coefficient, global village, Henri Poincaré, Hobbesian trap, humanitarian revolution, impulse control, income inequality, informal economy, Intergovernmental Panel on Climate Change (IPCC), invention of the printing press, Isaac Newton, lake wobegon effect, libertarian paternalism, long peace, longitudinal study, loss aversion, Marshall McLuhan, mass incarceration, McMansion, means of production, mental accounting, meta analysis, meta-analysis, Mikhail Gorbachev, moral panic, mutually assured destruction, Nelson Mandela, open economy, Peace of Westphalia, Peter Singer: altruism, QWERTY keyboard, race to the bottom, Ralph Waldo Emerson, random walk, Republic of Letters, Richard Thaler, Ronald Reagan, Rosa Parks, Saturday Night Live, security theater, Skype, Slavoj Žižek, South China Sea, Stanford marshmallow experiment, Stanford prison experiment, statistical model, stem cell, Steven Levy, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, theory of mind, transatlantic slave trade, Turing machine, twin studies, ultimatum game, uranium enrichment, Vilfredo Pareto, Walter Mischel, WikiLeaks, women in the workforce, zero-sum game

(Of course, paying a self-imposed cost would be worthwhile only if the prize is especially valuable to him, or if he had reason to believe that he could prevail over his opponent if the contest escalated.) In the case of a war of attrition, one can imagine a leader who has a changing willingness to suffer a cost over time, increasing as the conflict proceeds and his resolve toughens. His motto would be: “We fight on so that our boys shall not have died in vain.” This mindset, known as loss aversion, the sunk-cost fallacy, and throwing good money after bad, is patently irrational, but it is surprisingly pervasive in human decision-making.65 People stay in an abusive marriage because of the years they have already put into it, or sit through a bad movie because they have already paid for the ticket, or try to reverse a gambling loss by doubling their next bet, or pour money into a boondoggle because they’ve already poured so much money into it.

This mindset, known as loss aversion, the sunk-cost fallacy, and throwing good money after bad, is patently irrational, but it is surprisingly pervasive in human decision-making.65 People stay in an abusive marriage because of the years they have already put into it, or sit through a bad movie because they have already paid for the ticket, or try to reverse a gambling loss by doubling their next bet, or pour money into a boondoggle because they’ve already poured so much money into it. Though psychologists don’t fully understand why people are suckers for sunk costs, a common explanation is that it signals a public commitment. The person is announcing: “When I make a decision, I’m not so weak, stupid, or indecisive that I can be easily talked out of it.” In a contest of resolve like an attrition game, loss aversion could serve as a costly and hence credible signal that the contestant is not about to concede, preempting his opponent’s strategy of outlasting him just one more round. I already mentioned some evidence from Richardson’s dataset which suggests that combatants do fight longer when a war is more lethal: small wars show a higher probability of coming to an end with each succeeding year than do large wars.66 The magnitude numbers in the Correlates of War Dataset also show signs of escalating commitment: wars that are longer in duration are not just costlier in fatalities; they are costlier than one would expect from their durations alone.67 If we pop back from the statistics of war to the conduct of actual wars, we can see the mechanism at work.

I already mentioned some evidence from Richardson’s dataset which suggests that combatants do fight longer when a war is more lethal: small wars show a higher probability of coming to an end with each succeeding year than do large wars.66 The magnitude numbers in the Correlates of War Dataset also show signs of escalating commitment: wars that are longer in duration are not just costlier in fatalities; they are costlier than one would expect from their durations alone.67 If we pop back from the statistics of war to the conduct of actual wars, we can see the mechanism at work. Many of the bloodiest wars in history owe their destructiveness to leaders on one or both sides pursuing a blatantly irrational loss-aversion strategy. Hitler fought the last months of World War II with a maniacal fury well past the point when defeat was all but certain, as did Japan. Lyndon Johnson’s repeated escalations of the Vietnam War inspired a protest song that has served as a summary of people’s understanding of that destructive war: “We were waist-deep in the Big Muddy; The big fool said to push on.” The systems biologist Jean-Baptiste Michel has pointed out to me how escalating commitments in a war of attrition could produce a power-law distribution.


pages: 470 words: 148,730

Good Economics for Hard Times: Better Answers to Our Biggest Problems by Abhijit V. Banerjee, Esther Duflo

"Robert Solow", 3D printing, affirmative action, Affordable Care Act / Obamacare, Airbnb, basic income, Bernie Sanders, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, charter city, correlation does not imply causation, creative destruction, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, decarbonisation, Deng Xiaoping, Donald Trump, Edward Glaeser, en.wikipedia.org, endowment effect, energy transition, Erik Brynjolfsson, experimental economics, experimental subject, facts on the ground, fear of failure, financial innovation, George Akerlof, high net worth, immigration reform, income inequality, Indoor air pollution, industrial cluster, industrial robot, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Jane Jacobs, Jean Tirole, Jeff Bezos, job automation, Joseph Schumpeter, labor-force participation, land reform, loss aversion, low skilled workers, manufacturing employment, Mark Zuckerberg, mass immigration, Network effects, new economy, New Urbanism, non-tariff barriers, obamacare, offshore financial centre, open economy, Paul Samuelson, place-making, price stability, profit maximization, purchasing power parity, race to the bottom, RAND corporation, randomized controlled trial, Richard Thaler, ride hailing / ride sharing, Robert Gordon, Ronald Reagan, school choice, Second Machine Age, secular stagnation, self-driving car, shareholder value, short selling, Silicon Valley, smart meter, social graph, spinning jenny, Steve Jobs, technology bubble, The Chicago School, The Future of Employment, The Market for Lemons, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, total factor productivity, trade liberalization, transaction costs, trickle-down economics, universal basic income, urban sprawl, very high income, War on Poverty, women in the workforce, working-age population, Y2K

These vagaries make them unhappy, but perhaps not as unhappy as making an active choice that ends up, purely as a result of bad luck, making them worse off than if they had done nothing. The status quo, the outcome of letting things be, serves as a natural benchmark. Any loss relative to that benchmark is particularly painful. This concept was named loss aversion by Daniel Kahneman and Amos Tversky, two psychologists who have been incredibly influential in economics. (Kahneman won the Nobel Prize in economics in 2002 and Tversky would probably have as well, but for his untimely demise.) Since their original work, a vast literature has demonstrated the existence of loss aversion and its ability to explain many apparently strange behaviors. For example, most people pay a huge premium on their home insurance plans to get a low deductible.67 This allows them to avoid that painful moment when, after some accident has damaged their house, they have to pay a large sum out of pocket (the high deductible).

For example, most people pay a huge premium on their home insurance plans to get a low deductible.67 This allows them to avoid that painful moment when, after some accident has damaged their house, they have to pay a large sum out of pocket (the high deductible). By comparison, the fact that they may be paying a lot extra now (to get the policy with the low deductible) is painless because they will never discover if it was a mistake. The same logic also explains why gullible buyers often end up with outrageously expensive “extended warranties.” In essence, loss aversion makes us extremely worried about any risk, even small, that is a consequence of our active choice. Migration, unless everyone else is doing it, is one of these active choices, and a big one; it is easy to imagine many will be chary of trying. Finally, failure in migration is something people take personally. They have heard too many success stories, admiringly told, to not feel that failure would reveal something about them to themselves, if not to the world.


pages: 299 words: 92,782

The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing by Michael J. Mauboussin

Amazon Mechanical Turk, Atul Gawande, Benoit Mandelbrot, Black Swan, Checklist Manifesto, Clayton Christensen, cognitive bias, commoditize, Daniel Kahneman / Amos Tversky, David Brooks, deliberate practice, disruptive innovation, Emanuel Derman, fundamental attribution error, Gini coefficient, hindsight bias, hiring and firing, income inequality, Innovator's Dilemma, Long Term Capital Management, loss aversion, Menlo Park, mental accounting, moral hazard, Network effects, prisoner's dilemma, random walk, Richard Thaler, risk-adjusted returns, shareholder value, Simon Singh, six sigma, Steven Pinker, transaction costs, winner-take-all economy, zero-sum game, Zipf's Law

When you buy a stock at $30, for instance, you effectively open a mental account. You have a gain if the stock rises above $30 and a loss if it drops below that price. Rather than viewing the value of the stock in the context of a larger portfolio, the natural tendency is to consider each stock relative to its reference point. Loss aversion is another feature of prospect theory. We suffer roughly two times more from a loss than we enjoy a gain of the same size. The combination of the reference point and loss aversion leads investors to hold on to losing stocks and sell winners, because it is painful to take losses.34 Because good decisions can have bad outcomes, not everyone has a temperament that is well suited to making decisions about activities that involve luck. But Seth Klarman has the right temperament. He's the founder and president of a highly successful hedge fund called the Baupost Group.


pages: 312 words: 93,836

Barometer of Fear: An Insider's Account of Rogue Trading and the Greatest Banking Scandal in History by Alexis Stenfors

Asian financial crisis, asset-backed security, bank run, banking crisis, Big bang: deregulation of the City of London, bonus culture, capital controls, collapse of Lehman Brothers, credit crunch, Credit Default Swap, Eugene Fama: efficient market hypothesis, eurozone crisis, financial deregulation, financial innovation, fixed income, game design, Gordon Gekko, inflation targeting, information asymmetry, interest rate derivative, interest rate swap, London Interbank Offered Rate, loss aversion, mental accounting, millennium bug, Nick Leeson, Northern Rock, oil shock, price stability, profit maximization, regulatory arbitrage, reserve currency, Rubik’s Cube, Snapchat, the market place, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, Y2K

As the behavioural finance professor Daniel Kahneman notes: ‘Utility cannot be divorced from emotion.’2 Most people do not like playing roulette or games in which you have to guess whether the next person crossing the street is male or female. Even if the odds are exactly even, the frustration of losing a thousand dollars feels more powerful than the joy of winning a thousand. As a trader, I always felt more like a loser following a day when I had lost $10,000 or $100,000 than I felt like a ‘winner’ when I had made the same amount. The fact that losses loom larger than gains is called ‘loss aversion’. Nobody likes losing, of course, but a potential loss (or ‘negative’ reward) changes the way we approach risk taking. Another bias that complicates standard economics and finance theory is called ‘mental accounting’.3 In a nutshell, it refers to the way in which we often segregate different gambles into different accounts, and in so doing use very different criteria to assess how we utilise the various accounts.

., General Theory of Employment, 102 Kipling, Rudyard, 127 KLIBOR (Kuala Lumpur), 37 Knight, Angela, 107 Lapavitsas, Costas, 6–7 layering, 204 Leeson, Nick, 250 ‘legacy issues’, 236 Lehman Brothers, 2, 10, 48–9, 59, 105, 162, 272; bankruptcy filing, 160; collapse of aftermath, 96 Lewis, Ken, 164 LIBOR, 19, 28, 76–7, 104, 127, 130, 147, 209, 234, 265; anti-competitive process, 186; banking lobby regulated, 180–1; ‘barometer of fear’, 96; benchmark significance, 192, 225; central banks perfection assumption, 49; controls deception, 184; crisis-induced ‘stickiness’, 106; crucial price, 13; daily individual quotes, 97; derivatives, see below; ‘Eurodollar futures’ origin, 126; FCA regulated, 282; ‘fear’ index, 15; fixing panels, see below; future direction of, 38; inaccuracy possibilities, 74; interbank money market gauge, 39; jurisdiction issue, 115; manipulation, 7, 12, 14, 78; manipulation impossibility assumption, 81; market-determined perception, 88, 149; mechanism, 104; minute change importance, 73; new unpredictability, 62; 1980s invention, 111; objective process ‘evidence’, 148; perception of, 119; players as referees, 80; post 2007 interest, 53; pre-2013 unregulated, 118; predicting difficulty, 70; regulatory oversight lack, 179; retail credit impact, 277; sanctioned secrecy, 181–2; savings and borrowings dominance, 107; scandal breaking, 81; state measure use, 151; three-months, 71; ‘too big to fail’, 279; use of limited post-scandal, 278 LIBOR derivatives market, 8, 45, 137–8, 232; autonomous development of, 111; banks made, 125; ‘community’, 190; -FX connected, 189; imaginary money market, 148; increased abstraction of, 144–6 LIBOR panel banks, 74–5, 79, 98, 118, 172, 282; -LIBOR implications, 52 big banks dominated, 173, 179–80; fixing process, 75; membership criteria, 184–5; punishment idea, 108; post-scandal membership, 186 LIBOR scandal, 77, 152, 167, 245; correctness attempts, 277; post- definition unchanged, 278; breaking of, 81; Wall Street Journal on, 238 LIBOR-OIS spread(s), 51, 54–5, 99, 151 LIFFE, 126–7 liquidity: and credit crunch 2008, 2; credit issues, 45; informal norms need, 284; provision ‘duty’ 229; risk, 42–3, 55, 70 Lloyds Bank, 153, 183; LIBOR fine, 83 long/short positions, 26 Lukes, Steven, 186 makers, price, 24 Malaysia, financial crisis, 36 Mankell, Henning, 235 ‘marked to market’ trading books, 62 market, the financial: ‘colour’ 202; ‘conventions’, 228–33; ‘courtroom’, 171; interbank spread choosing ‘image’, 229; liquidity risk, 42–3; making, see below; perfections of, 15; relationships dependent, 225–6; risks limits management failure, 281 market makers/making, 24, 72, 117, 201, 206, 217, 226–7, 257; ‘ability’, 185; cash-settled derivatives, 133; failure to manage, 281; NIBOR IRS, 132; profession of, 200; two-way price quoting, 228; visibility of, 202 Martin Brokers, 85 Mathew, Jonathan, 139 McAdams, Richard, 231 McDermott, Tracey, 282 Meitan Tradition, 100, 175 Merita Bank, 56 Merrill Lynch, 2–3, 8–9, 12, 46, 49, 59–60, 62, 64, 69, 92–3, 96, 140, 153, 155, 160–1, 164, 188, 272, 285; Bank of America takeover, 67; bonuses, 10, 162–3; financial centre, 48; International Bank Limited Dublin, 4; mismarking, 68; risk taking encouraged, 281; silence rule, 242 Midland Montagu (Midland Bank Stockholm Branch), 20, 22–3, 27, 29; Stockholm, 22, 29 ‘Millenium bug’ fears, LIBOR impact, 44 mismarking, 9 mistakes, fear of, 26 Mollenkamp, Carrick, 98 ‘monetary transmission mechanism’, 39 money market(s): decentralised, 224; freeze, 110; international basis, 112; ‘risk premium’, 42; stable illusion-making, 106; -state link, 224 Moody’s, 96 morals, 66; morality, 69 Morgan Stanley, 49, 193, 223, 272 mortgage bonds, 21 NASDAQ stock exchange, transparency, 220 New York 2001 attacks, 263 New York Times, 4, 9, 11, 163, 241, 243 NIBOR (Norwegian Interbank Offered Rate), 28, 72, 130–1; fixing dates, 76; inaccurate fixing, 74; IRS market, 132; new unpredictability, 62; one month IRS market, 136 nicknames, use of, 25–6 Nordbanken, nationalised, 27 Nordic bank branches, 30 Norges Bank, NIBOR use, 152 Norinchukin Bank, 153 Northern Rock, Newcastle queues, 109 Norway, banking system, 131 ‘objective’ fact, LIBOR, 149 ‘off-balance-sheet’, trading, 137–8 official interest rate, predicting, 38 OIS (overnight index swap), 51; see also LIBOR-OIS one month IRS market, 136 OPEC (Organization of the Petroleum Exporting Countries), US dollar surpluses, 113 options desk, FX, 214 ‘over-the-counter’ trades, 63 derivatives, 129, 134; interest rate options, 130; markets, 227 Philippines, financial crisis, 37 Philips, cassette launch, 111 PIBOR (Paris Interbank Offered Rate), 19, 127 post scandals, reforms, 282 price(s), as interactions, 200; brokers indications role, 87; ‘resolution hypothesis’, 218 primary dealers, 175, 178 privacy, individual rights to, 167 Rabobank, LIBOR fine, 83, 153, 282 RBC, bank, 223 RBS, bank, 92, 153, 185, 188, 192, 220–1, 223, 284; LIBOR scandal fine, 83 reciprocity: -and trust, 226, 284; informal agreements, 228 regret, fear of, 258 regulatory arbitrage: Eurodollar market prompting, 118; platform for, 114 ‘reputation’, 185 respect, among traders, 267 Reuters, 19, 79, 151; Dealing, 41, 195, 260; Dealing 2000–2, 29, 34, 194; indicative prices, 62; screen price, 53 risk, 135; buzz of, 261–2; limits breaking, 274; ‘loss aversion’, 255; managers, 253; organizational limits, 250; pressures for, 63 risk taking: addictive, 262; enjoyment of, 260; fear control, 263; increase, 73; individualistic, 262; reward anticipation, 254; reward interpretation, 259; supervision need, 253 risk takers, 270; respect among, 268–9 Robert, Alain, 260 ‘rogue traders’, 1, 237; ‘bad apples’ narrative, 237, 240, 246, 279; fame, 252; fascination with, 246; losses, 259; ranking list, 250; risk list, 251; scandals, 258; stigma, 247 rogue trading, 274; definitions, 249; labelling, 248; risk link, 250 Royal Bank of Canada, 153 RP Martins, 153 rules of the game, loyalty to, 25 ‘run-throughs’, 87–9, 226–7 Russia, financial crisis, 36 Ryan, Ian, 3, 9, 68 Sanford C.


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The Price of Everything: And the Hidden Logic of Value by Eduardo Porter

Alvin Roth, Asian financial crisis, Ayatollah Khomeini, banking crisis, barriers to entry, Berlin Wall, British Empire, capital controls, Carmen Reinhart, Cass Sunstein, clean water, Credit Default Swap, Deng Xiaoping, Edward Glaeser, European colonialism, Fall of the Berlin Wall, financial deregulation, Ford paid five dollars a day, full employment, George Akerlof, Gordon Gekko, guest worker program, happiness index / gross national happiness, housing crisis, illegal immigration, immigration reform, income inequality, income per capita, informal economy, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jean Tirole, John Maynard Keynes: technological unemployment, Joshua Gans and Andrew Leigh, Kenneth Rogoff, labor-force participation, laissez-faire capitalism, longitudinal study, loss aversion, low skilled workers, Martin Wolf, means of production, Menlo Park, Mexican peso crisis / tequila crisis, Monkeys Reject Unequal Pay, new economy, New Urbanism, peer-to-peer, pension reform, Peter Singer: altruism, pets.com, placebo effect, price discrimination, price stability, rent-seeking, Richard Thaler, rising living standards, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, Silicon Valley, stem cell, Steve Jobs, Stewart Brand, superstar cities, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, trade route, transatlantic slave trade, ultimatum game, unpaid internship, urban planning, Veblen good, women in the workforce, World Values Survey, Yom Kippur War, young professional, zero-sum game

But only a quarter say they are seriously trying to lose weight. In the 1980s a new discipline called Prospect Theory—also known as behavioral economics—deployed the tools of psychology to analyze economic behavior. It found all sorts of peculiar behaviors that don’t fit economics’ standard understanding of what makes us happy. For instance, losing something reduces our happiness more than winning the same thing increases it—a quirk known as loss aversion. We are unable to distinguish between choices that have slightly different odds of making us happy. We extrapolate from a few experiences to arrive at broad, mostly wrong conclusions. We herd, imitating successful behaviors around us. Still, it remains generally true that we pursue what we think makes us happy—and though some of our choices may not make us happy, some will. Legend has it that Abraham Lincoln was riding in a carriage one rainy evening, telling a friend that he agreed with economists’ theory that people strove to maximize their happiness, when he caught sight of a pig stuck in a muddy riverbank.

electricity elephant-seal cows Elías, Julio Jorge e-mail, spam and Emergency Highway Energy Conservation Act (1974) Empire State Stem Cell Board encyclopedias, free energy engagement rings engineers England environment see also climate change; pollution Environmental Protection Agency (EPA) Epson ESP printers Essay on the Principle of Population, An (Malthus) Ethiopia Ethnographic Atlas (Murdock) eToys Eurobarometer surveys Europe Catholic Church in decline of polygamy in happiness in lack of sprawl in U.S. compared with work hours in see also Western Europe European Climate Exchange European Union evangelical Christianity executive pay ExxonMobil faith benefits of cheap cost of Fallaci, Oriana families changes to culture and income of of 9/11 victims size of Fanning, Shawn (the Napster) Federal Communications Commission Federal Food, Drug, and Cosmetic Act, Delaney Clause to (1958) Federal Reserve Federal Trade Commission (FTC) “Feeding the Illusion of Growth and Happiness” (Easterlin) Feinberg, Kenneth fertility decline in female file sharing film financial crises financial services fines fire departments fishing floors Florence foeticide food culture and faith and preparation of price increases for surpluses of Food and Agriculture Organization Food Quality Protection Act (1996) Ford Ford, Henry Foreign Corrupt Practices Act Fourier, Charles France happiness in work hours in Frank, Robert Free (Anderson) Freedom Communications free lunch, use of term free rider problem free things broadcast TV and movies music and Napstering the world and profiting from ideas freeware Freud, Sigmund fuel see also gas Fundamentalist Church of Jesus Christ of Latter-day Saints future ethics of mispricing nature and price of Gabaix, Xavier Gallup polls Gandhi garbage gas price of General Motors (GM) General Social Survey General Theory of Employment, Interest and Money, The (Keynes) genetics, genes Germany happiness in Germany, Nazi Gershom ben Judah Ghosts I-IV (album) gifts Glass-Steagall Act (1933) GlaxoSmithKline globalization global warming Goa God Goldin, Claudia goods Google Google News Gore, Al Gorton, Mark government hostility toward intervention of resource allocation of Great Britain bubbles in gas prices in happiness in politics in Great Depression Greece, ancient green revolution (1960s and 1970s) Greenspan, Alan gross national happiness (GNH) index Haiti Hammurabi Hanna, Mark happiness faith and genetics and life-cycle curve of loss aversion and money and problems with defining of right-left gap in U.S. trade-off and Hare Krishna Society Harvard University Haryana health health care health insurance Health Ministry, New Zealand Healthway Heinrich, Armin Hindus, Hinduism HIV homeland security, U.S. Homeland Security Department, U.S. Hoover, Herbert horse meat House of Representatives, U.S. housing, homes bubble price of HP human papillomavirus Hume, David Hungary hunting I Am Rich Iannaccone, Larry IBM Iceland ideas Illinois illustrators Illy iMacs immigrants illegal Immigration Reform and Control Act (1986) improvement income family happiness and inequality of marriage and national redistribution of tax on technological progress and indentured servants India future of marriage in sex ratios in Indonesia indulgences industrialization inequality income Inevitable Rise and Liberation of Niggy Tardust!


pages: 374 words: 97,288

The End of Ownership: Personal Property in the Digital Economy by Aaron Perzanowski, Jason Schultz

3D printing, Airbnb, anti-communist, barriers to entry, bitcoin, blockchain, carbon footprint, cloud computing, conceptual framework, crowdsourcing, cryptocurrency, Donald Trump, Edward Snowden, en.wikipedia.org, endowment effect, Firefox, George Akerlof, Hush-A-Phone, information asymmetry, intangible asset, Internet Archive, Internet of things, Isaac Newton, loss aversion, Marc Andreessen, means of production, minimum wage unemployment, new economy, peer-to-peer, price discrimination, Richard Thaler, ride hailing / ride sharing, rolodex, self-driving car, sharing economy, Silicon Valley, software as a service, software patent, software studies, speech recognition, Steve Jobs, subscription business, telemarketer, The Market for Lemons, transaction costs, winner-take-all economy

When presented the opportunity to sell or trade their mugs to other participants, mug owners demanded nearly twice as much compensation as nonowners were willing to pay.34 Subjectively, they valued the mugs they owned well above the market rate. What explains these vastly different assessments of the value of an otherwise ordinary mug? Some have suggested that the endowment effect is the result of loss aversion—the idea that people are more motivated by the fear or regret associated with loss of an item than the enjoyment of gaining it. But more recent research shows that we place greater value on the things we own because we own them.35 The association between an item and its owner means that we value things we own far more than things we simply use. And as that sense of ownership grows stronger, so does the value we place on the item.

Taylor Swift, “For Taylor Swift, the Future of Music Is a Love Story,” Wall Street Journal, July 7, 2014, http://www.wsj.com/articles/for-taylor-swift-the-future-of-music-is-a-love-story-1404763219, accessed June 15, 2015. 34. Daniel Kahneman, Jack L. Knetsch, and Richard H. Thaler, “Experimental Tests of the Endowment Effect and the Coase Theorem,” Journal of Political Economy 98, no. 6 (1990): 1325–1348. 35. Carey K. Morewedge et al., “Bad Riddance or Good Rubbish? Ownership and Not Loss Aversion Causes the Endowment Effect,” Journal of Experimental Psychology 45, no. 4 (July 2009): 947–951. 36. Yannick Ferreira De Sousa and Alistair Munro, “Truck, Barter, and Exchange versus the Endowment Effect: Virtual Field Experiments in an Online Game Environment,” Journal of Economic Psychology 33, no. 3 (June 2012): 482–493. Although this experiment found that the endowment effect was reduced among experienced players of an online role-playing game, that finding is consistent with experiments in the offline world. 37.


pages: 297 words: 96,509

Time Paradox by Philip G. Zimbardo, John Boyd

Albert Einstein, cognitive dissonance, Drosophila, endowment effect, hedonic treadmill, impulse control, indoor plumbing, loss aversion, mental accounting, meta analysis, meta-analysis, Necker cube, Ronald Reagan, science of happiness, The Wealth of Nations by Adam Smith, twin studies

Tversky, “Prospect Theory: An Analysis of Decision Under Risk,” Econometrica 47: 263–91 (1979); A. Tversky and D. Kahneman, “The Framing of Decisions and the Psychology of Choice,” Science 211: 453–58 (1981); and A. Tversky and D. Kahneman, “Loss Aversion in Riskless Choice: A Reference-Dependent Model,” Quarterly Journal of Economics 106: 1039–61 (1991). 35. D. Kahneman, J. L. Knetsch, and R. H. Thaler, “Experimental Tests of the Endowment Effect and the Coase Theorem,” Journal of Political Economy 98: 1325–48 (1990); and D. Kahneman, J. Kentsch, and D. Thaler, “The Endowment Effect, Loss Aversion, and Status Quo Bias,” Journal of Economic Perspectives 5: 193–206 (1991). 36. L. van Boven, D. Dunning, and G. F. Loewenstein, “Egocentric Empathy Gaps Between Owners and Buyers: Misperceptions of the Endowment Effect,” Journal of Personality and Social Psychology 79: 66–76 (2000); and Z.


pages: 349 words: 98,868

Nervous States: Democracy and the Decline of Reason by William Davies

active measures, Affordable Care Act / Obamacare, Amazon Web Services, bank run, banking crisis, basic income, business cycle, Capital in the Twenty-First Century by Thomas Piketty, citizen journalism, Climategate, Climatic Research Unit, Colonization of Mars, continuation of politics by other means, creative destruction, credit crunch, decarbonisation, deindustrialization, discovery of penicillin, Dominic Cummings, Donald Trump, drone strike, Elon Musk, failed state, Filter Bubble, first-past-the-post, Frank Gehry, gig economy, housing crisis, income inequality, Isaac Newton, Jeff Bezos, Johannes Kepler, Joseph Schumpeter, knowledge economy, loss aversion, low skilled workers, Mahatma Gandhi, Mark Zuckerberg, mass immigration, meta analysis, meta-analysis, Mont Pelerin Society, mutually assured destruction, Northern Rock, obamacare, Occupy movement, pattern recognition, Peace of Westphalia, Peter Thiel, Philip Mirowski, planetary scale, post-industrial society, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, road to serfdom, Robert Mercer, Ronald Reagan, sentiment analysis, Silicon Valley, Silicon Valley startup, smart cities, statistical model, Steve Jobs, the scientific method, Turing machine, Uber for X, universal basic income, University of East Anglia, Valery Gerasimov, We are the 99%, WikiLeaks, women in the workforce, zero-sum game

“The vanquished sinks much further below the original line of equilibrium than the conqueror raises himself above it,” he noted.22 On a cultural and psychological level, war is fundamentally a question of who is destroyed, not of who gains. In more prosaic contexts, this is an insight that has been confirmed by behavioral economists. Experiments show that, all else being equal, people place greater value on not losing that which they already have, than on gaining something of equivalent value. As these behavioral economists would say, we are fundamentally “loss-averse” creatures. Where victory is enjoyed and then quickly taken for granted, the experience of loss shapes our identity, forging a melancholic sense of nostalgia. Paradoxically, this melancholic sense of having lost can have its own mobilizing effect, if it can be triggered in the right way. Clausewitz wondered whether “through the loss of a great battle, forces are not perhaps roused into existence, which otherwise would never have come to life.”23 The pain of defeat produces a feeling of victimhood through which national cohesion starts to emerge.

., Martin Luther, 21, 224 knowledge economy, 84, 85, 88, 151–2, 217 known knowns, 132, 138 Koch, Charles and David, 154, 164, 174 Korean War (1950–53), 178 Kraepelin, Emil, 139 Kurzweil, Ray, 183–4 Labour Party, 5, 6, 65, 80, 81, 221 Lagarde, Christine, 64 Le Bon, Gustave, 8–12, 13, 15, 16, 20, 24, 25, 38 Le Pen, Marine, 27, 79, 87, 92, 101–2 Leadbeater, Charles, 84 Leeds, West Yorkshire, 85 Leicester, Leicestershire, 85 Leviathan (Hobbes), 34, 39, 45 liberal elites, 20, 58, 88, 89, 161 libertarianism, 15, 151, 154, 158, 164, 173, 196, 209, 226 Liberty Fund, 158 Libya, 143 lie-detection technology, 136 life expectancy, 62, 68–71, 72, 92, 100–101, 115, 224 Lindemann, Frederick Alexander, 1st Viscount Cherwell, 138 Lloyds Bank, 29 London, England bills of mortality, 68–71, 75, 79–80, 81, 89, 127 Blitz (1940–41), 119, 143, 180 EU referendum (2016), 85 Great Fire (1666), 67 Grenfell Tower fire (2017), 10 and gross domestic product (GDP), 77, 78 housing crisis, 84 insurance sector, 59 knowledge economy, 84 life expectancy, 100 newspapers, early, 48 Oxford Circus terror scare (2017), ix–x, xiii, 41 plagues, 67–71, 75, 79–80, 81, 89, 127 Unite for Europe march (2017), 23 London School of Economics (LSE), 160 loss aversion, 145 Louis XIV, King of France, 73, 127 Louisiana, United States, 151, 221 Ludwig von Mises Institute, 154 MacLean, Nancy, 158 Macron, Emmanuel, 33 mainstream media, 197 “Make America Great Again,” 76, 145 Manchester, England, 85 Mann, Geoff, 214 maps, 182 March For Our Lives (2018), 21 March for Science (2017), 23–5, 27, 28, 210, 211 marketing, 14, 139–41, 143, 148, 169 Mars, 175, 226 Marxism, 163 Massachusetts Institute of Technology (MIT), 179 Mayer, Jane, 158 McCarthy, Joseph, 137 McGill Pain Questionnaire, 104 McKibben, William “Bill,” 213 Megaface, 188–9 memes, 15, 194 Menger, Carl, 154 mental illness, 103, 107–17, 139 mercenaries, 126 Mercer, Robert, 174, 175 Mexico, 145 Million-Man March (1995), 4 mind-reading technology, 136 see also telepathy Mirowski, Philip, 158 von Mises, Ludwig, 154–63, 166, 172, 173 Missing Migrants Project, 225 mobilization, 5, 7, 126–31 and Corbyn, 81 and elections, 81, 124 and experts, 27–8 and Internet, 15 and Le Bon’s crowd psychology, 11, 12, 16, 20 and loss, 145 and Napoleonic Wars, xv, 127–30, 141, 144 and Occupy movement, 5 and populism, 16, 22, 60 and violence, opposition to, 21 Moniteur Universel, Le, 142 monopoly on violence, 42 Mont Pelerin Society, 163, 164 moral emotion, 21 morphine, 105 multiculturalism, 84 Murs, Oliver “Olly,” ix Musk, Elon, 175, 176, 178, 183, 226 Nanchang, Jiangxi, 13 Napoleonic Wars (1803–15), 126–30 chappe system, 129, 182 and conscription, 87, 126–7, 129 and disruption, 170–71, 173, 174, 175, 226 and great leader ideal, 146–8 and intelligence, 134 and mobilization, xv, 126–30, 141, 144 and nationalism, 87, 128, 129, 144, 183, 211 and propaganda, 142 Russia, invasion of (1812), 128, 133 Spain, invasion of (1808), 128 National Aeronautics and Space Administration (NASA), 23, 175 National Audit Office (NAO), 29–30 national citizenship, 71 National Defense Research Committee, 180 National Health Service (NHS), 30, 93 National Park Service, 4 National Security Agency (NSA), 152 national sovereignty, 34, 53 nationalism, 87, 141, 210–12 and conservatism, 144 and disempowerment, 118–19 and elites, 22–3, 60–61, 145 ethnic, 15 and health, 92, 211–12, 224 and imagined communities, 87 and inequality, 78 and loss, 145 and markets, 167 and promises, 221 and resentment, 145, 197, 198 and war, 7, 20–21, 118–19, 143–6, 210–11 nativism, 61 natural philosophy, 35–6 nature, 86 see also environment Nazi Germany (1933–45), 137, 138, 154 Netherlands, 48, 56, 129 Neurable, 176 neural networking, 216 Neuralink, 176 neurasthenia, 139 Neurath, Otto, 153–4, 157, 160 neurochemistry, 108, 111, 112 neuroimaging, 176–8, 181 Nevada, United States, 194 new atheism, 209 New Orleans, Louisiana, 151 New Right, 164 New York, United States and climate change, 205 and gross domestic product (GDP), 78 housing crisis, 84 JFK Airport terror scare (2016), x, xiii, 41 knowledge economy, 84 September 11 attacks (2001), 17, 18 New York Times, 3, 27, 85 newspapers, 48, 71 Newton, Isaac, 35 Nietzsche, Friedrich, 217 Nixon, Robert, 206 no-platforming, 22, 208 Nobel Prize, 158–9 non-combatants, 43, 143, 204 non-violence, 224 North Atlantic Treaty Organization (NATO), 123, 145, 214 North Carolina, United States, 84 Northern Ireland, 43, 85 Northern League, 61 Northern Rock, 29 Norwich, Norfolk, 85 nostalgia, xiv, 143, 145, 210, 223 “Not in my name,” 27 nuclear weapons, 132, 135, 137, 180, 183, 192, 196, 204 nudge techniques, 13 Obama, Barack, 3, 24, 76, 77, 79, 158, 172 Obamacare, 172 objectivity, xiv, 13, 75, 136, 223 and crowd-based politics, 5, 7, 24–5 and death, 94 and Descartes, 37 and experts, trust in, 28, 32, 33, 51, 53, 64, 86, 89 and Hayek, 163, 164, 170 and markets, 169, 170 and photography, 8 and Scientific Revolution, 48, 49 and statistics, 72, 74, 75, 82, 88 and telepathic communication, 179 and war, 58, 125, 134, 135, 136, 146 Occupy movement, 5, 10, 24, 61 Oedipus complex, 109 Office for National Statistics, 63, 133 Ohio, United States, 116 oil crisis (1973), 166 “On Computable Numbers” (Turing), 181 On War (Clausewitz), 130 Open Society and Its Enemies, The (Popper), 171 opiates, 105, 116, 172–3 opinion polling, 65, 80–81, 191 Orbán, Viktor, 87, 146 Organisation for Economic Co-operation and Development (OECD), 72 Oxford, Oxfordshire, 85 Oxford Circus terror scare (2017), ix–x, xiii, 41 Oxford University, 56, 151 OxyContin, 105, 116 pacifism, 8, 20, 44, 151 pain, 102–19, 172–3, 224 see also chronic pain painkillers, 104, 105, 116, 172–3 Palantir, 151, 152, 175, 190 parabiosis, 149 Paris climate accord (2015), 205, 207 Paris Commune (1871), 8 Parkland attack (2018), 21 Patriot Act (2001), 137 Paul, Ronald, 154 PayPal, 149 Peace of Westphalia (1648), 34, 53 peer reviewing, 48, 139, 195, 208 penicillin, 94 Pentagon, 130, 132, 135, 136, 214, 216 pesticides, 205 Petty, William, 55–9, 67, 73, 85, 167 pharmacology, 142 Pielke Jr., Roger, 24, 25 Piketty, Thomas, 74 Pinker, Stephen, 207 plagues, 56, 67–71, 75, 79–80, 81, 89, 95 pleasure principle, 70, 109, 110, 224 pneumonia, 37, 67 Podemos, 5, 202 Poland, 20, 34, 60 Polanyi, Michael, 163 political anatomy, 57 Political Arithmetick (Petty), 58, 59 political correctness, 20, 27, 145 Popper, Karl, 163, 171 populism xvii, 211–12, 214, 220, 225–6 and central banks, 33 and crowd-based politics, 12 and democracy, 202 and elites/experts, 26, 33, 50, 152, 197, 210, 215 and empathy, 118 and health, 99, 101–2, 224–5 and immediate action, 216 in Kansas (1880s), 220 and markets, 167 and private companies, 174 and promises, 221 and resentment, 145 and statistics, 90 and unemployment, 88 and war, 148, 212 Porter, Michael, 84 post-traumatic stress disorder (PTSD), 111–14, 117, 209 post-truth, 167, 224 Potsdam Conference (1945), 138 power vs. violence, 19, 219 predictive policing, 151 presidential election, US (2016), xiv and climate change, 214 and data, 190 and education, 85 and free trade, 79 and health, 92, 99 and immigration, 79, 145 and inequality, 76–7 and Internet, 190, 197, 199 “Make America Great Again,” 76, 145 and opinion polling, 65, 80 and promises, 221 and relative deprivation, 88 and Russia, 199 and statistics, 63 and Yellen, 33 prisoners of war, 43 promises, 25, 31, 39–42, 45–7, 51, 52, 217–18, 221–2 Propaganda (Bernays), 14–15 propaganda, 8, 14–16, 83, 124–5, 141, 142, 143 property rights, 158, 167 Protestantism, 34, 35, 45, 215 Prussia (1525–1947), 8, 127–30, 133–4, 135, 142 psychiatry, 107, 139 psychoanalysis, 107, 139 Psychology of Crowds, The (Le Bon), 9–12, 13, 15, 16, 20, 24, 25 psychosomatic, 103 public-spending cuts, 100–101 punishment, 90, 92–3, 94, 95, 108 Purdue, 105 Putin, Vladimir, 145, 183 al-Qaeda, 136 quality of life, 74, 104 quantitative easing, 31–2, 222 quants, 190 radical statistics, 74 RAND Corporation, 183 RBS, 29 Reagan, Ronald, 15, 77, 154, 160, 163, 166 real-time knowledge, xvi, 112, 131, 134, 153, 154, 165–70 Reason Foundation, 158 Red Vienna, 154, 155 Rees-Mogg, Jacob, 33, 61 refugee crisis (2015–), 60, 225 relative deprivation, 88 representative democracy, 7, 12, 14–15, 25–8, 61, 202 Republican Party, 77, 79, 85, 154, 160, 163, 166, 172 research and development (R&D), 133 Research Triangle, North Carolina, 84 resentment, 5, 226 of elites/experts, 32, 52, 61, 86, 88–9, 161, 186, 201 and nationalism/populism, 5, 144–6, 148, 197, 198 and pain, 94 Ridley, Matt, 209 right to remain silent, 44 Road to Serfdom, The (Hayek), 160, 166 Robinson, Tommy, ix Roosevelt, Franklin Delano, 52 Royal Exchange, 67 Royal Society, 48–52, 56, 68, 86, 133, 137, 186, 208, 218 Rumsfeld, Donald, 132 Russian Empire (1721–1917), 128, 133 Russian Federation (1991–) and artificial intelligence, 183 Gerasimov Doctrine, 43, 123, 125, 126 and information war, 196 life expectancy, 100, 115 and national humiliation, 145 Skripal poisoning (2018), 43 and social media, 15, 18, 199 troll farms, 199 Russian Revolution (1917), 155 Russian SFSR (1917–91), 132, 133, 135–8, 155, 177, 180, 182–3 safe spaces, 22, 208 Sands, Robert “Bobby,” 43 Saxony, 90 scarlet fever, 67 Scarry, Elaine, 102–3 scenting, 135, 180 Schneier, Bruce, 185 Schumpeter, Joseph, 156–7, 162 Scientific Revolution, 48–52, 62, 66, 95, 204, 207, 218 scientist, coining of term, 133 SCL, 175 Scotland, 64, 85, 172 search engines, xvi Second World War, see World War II securitization of loans, 218 seismology, 135 self-employment, 82 self-esteem, 88–90, 175, 212 self-harm, 44, 114–15, 117, 146, 225 self-help, 107 self-interest, 26, 41, 44, 61, 114, 141, 146 Semi-Automatic Ground Environment (SAGE), 180, 182, 200 sentiment analysis, xiii, 12–13, 140, 188 September 11 attacks (2001), 17, 18 shell shock, 109–10 Shrecker, Ted, 226 Silicon Fen, Cambridgeshire, 84 Silicon Valley, California, xvi, 219 and data, 55, 151, 185–93, 199–201 and disruption, 149–51, 175, 226 and entrepreneurship, 149–51 and fascism, 203 and immortality, 149, 183–4, 224, 226 and monopolies, 174, 220 and singularity, 183–4 and telepathy, 176–8, 181, 185, 186, 221 and weaponization, 18, 219 singularity, 184 Siri, 187 Skripal poisoning (2018), 43 slavery, 59, 224 smallpox, 67 smart cities, 190, 199 smartphone addiction, 112, 186–7 snowflakes, 22, 113 social indicators, 74 social justice warriors (SJWs), 131 social media and crowd psychology, 6 emotional artificial intelligence, 12–13, 140–41 and engagement, 7 filter bubbles, 66 and propaganda, 15, 18, 81, 124 and PTSD, 113 and sentiment analysis, 12 trolls, 18, 20–22, 27, 40, 123, 146, 148, 194–8, 199, 209 weaponization of, 18, 19, 22, 194–5 socialism, 8, 20, 154–6, 158, 160 calculation debate, 154–6, 158, 160 Socialism (Mises), 160 Society for Freedom in Science, 163 South Africa, 103 sovereignty, 34, 53 Soviet Russia (1917–91), 132, 133, 135–8, 177, 180, 182–3 Spain, 5, 34, 84, 128, 202 speed of knowledge, xvi, 112, 124, 131, 134, 136, 153, 154, 165–70 Spicer, Sean, 3, 5 spy planes, 136, 152 Stalin, Joseph, 138 Stanford University, 179 statactivism, 74 statistics, 62–91, 161, 186 status, 88–90 Stoermer, Eugene, 206 strong man leaders, 16 suicide, 100, 101, 115 suicide bombing, 44, 146 superbugs, 205 surveillance, 185–93, 219 Sweden, 34 Switzerland, 164 Sydenham, Thomas, 96 Syriza, 5 tacit knowledge, 162 talking cure, 107 taxation, 158 Tea Party, 32, 50, 61, 221 technocracy, 53–8, 59, 60, 61, 78, 87, 89, 90, 211 teenage girls, 113, 114 telepathy, 39, 176–9, 181, 185, 186 terrorism, 17–18, 151, 185 Charlottesville attack (2017), 20 emergency powers, 42 JFK Airport terror scare (2016), x, xiii, 41 Oxford Circus terror scare (2017), ix–x, xiii, 41 September 11 attacks (2001), 17, 18 suicide bombing, 44, 146 vehicle-ramming attacks, 17 war on terror, 131, 136, 196 Thames Valley, England, 85 Thatcher, Margaret, 154, 160, 163, 166 Thiel, Peter, 26, 149–51, 153, 156, 174, 190 Thirty Years War (1618–48), 34, 45, 53, 126 Tokyo, Japan, x torture, 92–3 total wars, 129, 142–3 Treaty of Westphalia (1648), 34, 53 trends, xvi, 168 trigger warnings, 22, 113 trolls, 18, 20–22, 27, 40, 123, 146, 148, 194–8, 199, 209 Trump, Donald, xiv and Bannon, 21, 60–61 and climate change, 207 and education, 85 election campaign (2016), see under presidential election, US and free trade, 79 and health, 92, 99 and immigration, 145 inauguration (2017), 3–5, 6, 9, 10 and inequality, 76–7 “Make America Great Again,” 76, 145 and March for Science (2017), 23, 24, 210 and media, 27 and opinion polling, 65, 80 and Paris climate accord, 207 and promises, 221 and relative deprivation, 88 and statistics, 63 and Yellen, 33 Tsipras, Alexis, 5 Turing, Alan, 181, 183 Twitter and Corbyn’s rallies, 6 and JFK Airport terror scare (2016), x and Oxford Circus terror scare (2017), ix–x and Russia, 18 and sentiment analysis, 188 and trends, xvi and trolls, 194, 195 Uber, 49, 185, 186, 187, 188, 191, 192 UK Independence Party, 65, 92, 202 underemployment, 82 unemployment, 61, 62, 72, 78, 81–3, 87, 88, 203 United Kingdom austerity, 100 Bank of England, 32, 33, 64 Blitz (1940–41), 119, 143, 180 Brexit (2016–), see under Brexit Cameron government (2010–16), 33, 73, 100 Center for Policy Studies, 164 Civil Service, 33 climate-gate (2009), 195 Corbyn’s rallies, 5, 6 Dunkirk evacuation (1940), 119 education, 85 financial crisis (2007–9), 29–32, 100 first past the post, 13 general election (2015), 80, 81 general election (2017), 6, 65, 80, 81, 221 Grenfell Tower fire (2017), 10 gross domestic product (GDP), 77, 79 immigration, 63, 65 Irish hunger strike (1981), 43 life expectancy, 100 National Audit Office (NAO), 29 National Health Service (NHS), 30, 93 Office for National Statistics, 63, 133 and opiates, 105 Oxford Circus terror scare (2017), ix–x, xiii, 41 and pain, 102, 105 Palantir, 151 Potsdam Conference (1945), 138 quantitative easing, 31–2 Royal Society, 138 Scottish independence referendum (2014), 64 Skripal poisoning (2018), 43 Society for Freedom in Science, 163 Thatcher government (1979–90), 154, 160, 163, 166 and torture, 92 Treasury, 61, 64 unemployment, 83 Unite for Europe march (2017), 23 World War II (1939–45), 114, 119, 138, 143, 180 see also England United Nations, 72, 222 United States Bayh–Dole Act (1980), 152 Black Lives Matter, 10, 225 BP oil spill (2010), 89 Bush Jr. administration (2001–9), 77, 136 Bush Sr administration (1989–93), 77 Bureau of Labor, 74 Central Intelligence Agency (CIA), 3, 136, 151, 199 Charlottesville attack (2017), 20 Civil War (1861–5), 105, 142 and climate change, 207, 214 Clinton administration (1993–2001), 77 Cold War, see Cold War Defense Advanced Research Projects Agency (DARPA), 176, 178 Defense Intelligence Agency, 177 drug abuse, 43, 100, 105, 115–16, 131, 172–3 education, 85 Federal Bureau of Investigation (FBI), 137 Federal Reserve, 33 Fifth Amendment (1789), 44 financial crisis (2007–9), 31–2, 82, 158 first past the post, 13 Government Accountability Office, 29 gross domestic product (GDP), 75–7, 82 health, 92, 99–100, 101, 103, 105, 107, 115–16, 158, 172–3 Heritage Foundation, 164, 214 Iraq War (2003–11), 74, 132 JFK Airport terror scare (2016), x, xiii, 41 Kansas populists (1880s), 220 libertarianism, 15, 151, 154, 158, 164, 173 life expectancy, 100, 101 March For Our Lives (2018), 21 March for Science (2017), 23–5, 27, 28, 210 McCarthyism (1947–56), 137 Million-Man March (1995), 4 National Aeronautics and Space Administration (NASA), 23, 175 National Defense Research Committee, 180 National Park Service, 4 National Security Agency (NSA), 152 Obama administration (2009–17), 3, 24, 76, 77, 79, 158 Occupy Wall Street (2011), 5, 10, 61 and opiates, 105, 172–3 and pain, 103, 105, 107, 172–3 Palantir, 151, 152, 175, 190 Paris climate accord (2015), 205, 207 Parkland attack (2018), 21 Patriot Act (2001), 137 Pentagon, 130, 132, 135, 136, 214, 216 presidential election (2016), see under presidential election, US psychiatry, 107, 111 quantitative easing, 31–2 Reagan administration (1981–9), 15, 77, 154, 160, 163, 166 Rumsfeld’s “unknown unknowns” speech (2002), 132 Semi-Automatic Ground Environment (SAGE), 180, 182, 200 September 11 attacks (2001), 17, 18 Tea Party, 32, 50, 61, 221 and torture, 93 Trump administration (2017–), see under Trump, Donald unemployment, 83 Vietnam War (1955–75), 111, 130, 136, 138, 143, 205 World War I (1914–18), 137 World War II (1939–45), 137, 180 universal basic income, 221 universities, 151–2, 164, 169–70 University of Cambridge, 84, 151 University of Chicago, 160 University of East Anglia, 195 University of Oxford, 56, 151 University of Vienna, 160 University of Washington, 188 unknown knowns, 132, 133, 136, 138, 141, 192, 212 unknown unknowns, 132, 133, 138 “Use of Knowledge in Society, The” (Hayek), 161 V2 flying bomb, 137 vaccines, 23, 95 de Vauban, Sébastien Le Prestre, Marquis de Vauban, 73 vehicle-ramming attacks, 17 Vesalius, Andreas, 96 Vienna, Austria, 153–5, 159 Vietnam War (1955–75), 111, 130, 136, 138, 143, 205 violence vs. power, 19, 219 viral marketing, 12 virtual reality, 183 virtue signaling, 194 voice recognition, 187 Vote Leave, 50, 93 Wainright, Joel, 214 Wales, 77, 90 Wall Street, New York, 33, 190 War College, Berlin, 128 “War Economy” (Neurath), 153–4 war on drugs, 43, 131 war on terror, 131, 136, 196 Watts, Jay, 115 weaponization, 18–20, 22, 26, 75, 118, 123, 194, 219, 223 weapons of mass destruction, 132 wearable technology, 173 weather control, 204 “What Is An Emotion?”


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Software Engineering at Google: Lessons Learned From Programming Over Time by Titus Winters, Tom Manshreck, Hyrum Wright

anti-pattern, computer vision, continuous integration, defense in depth, en.wikipedia.org, job automation, loss aversion, microservices, transaction costs, Turing complete

In many cases these products are a clear net benefit, but when we’re operating at such a scale even small discrepancies in usability, accessibility, fairness, or potential for abuse are magnified - often to the detriment of groups that are already marginalized. Software pervades so many aspects of society and culture, it is wise for us to be aware of both the good and the bad that we enable when making product and technical decisions. We discuss this much more in “Engineering for Equity.” In addition to the above costs (or our estimate of them), there are biases: status quo bias, loss aversion, etc. When we evaluate cost, we need to keep all of the above in mind: the health of an organization isn’t just whether there is money in the bank, it’s also whether its members are feeling valued and productive. In highly creative and lucrative fields like software engineering, financial cost is usually not the limiting factor: personnel cost usually is. Efficiency gains from keeping engineers happy, focused, and engaged can easily dominate other factors, simply because focus and productivity are so variable and a 10-20% difference is easy to imagine.


pages: 139 words: 33,246

Money Moments: Simple Steps to Financial Well-Being by Jason Butler

Albert Einstein, asset allocation, buy and hold, Cass Sunstein, diversified portfolio, estate planning, financial independence, fixed income, happiness index / gross national happiness, index fund, intangible asset, longitudinal study, loss aversion, Lyft, Mark Zuckerberg, mortgage debt, passive income, placebo effect, Richard Thaler, ride hailing / ride sharing, Steve Jobs, time value of money, traffic fines, Travis Kalanick, Uber and Lyft, uber lyft, Vanguard fund, Yogi Berra

This risk, in the form of a wide range of potential return outcomes, is actually the source of their higher expected return over the long-term compared to cash deposits and fixed income securities. You therefore need to get used to seeing your capital fall in value on a regular basis if you want to earn a higher return. But this is easier said than done, mainly because people prefer avoiding losses to acquiring gains – a phenomenon known as loss aversion.29 Research shows that people give twice the weight to the pain of loss than they do the pleasure of gain. This means we seek risk when pursuing gains but become risk adverse in relation to losses, and are more likely to act if threatened with loss than promised gain. As long as you have a big enough cash reserve, a long enough time horizon and have a good spread of global companies, all you need to control is your emotions when investment markets take a tumble.


pages: 319 words: 106,772

Irrational Exuberance: With a New Preface by the Author by Robert J. Shiller

Andrei Shleifer, asset allocation, banking crisis, Benoit Mandelbrot, business cycle, buy and hold, computer age, correlation does not imply causation, Daniel Kahneman / Amos Tversky, demographic transition, diversification, diversified portfolio, equity premium, Everybody Ought to Be Rich, experimental subject, hindsight bias, income per capita, index fund, Intergovernmental Panel on Climate Change (IPCC), Joseph Schumpeter, Long Term Capital Management, loss aversion, mandelbrot fractal, market bubble, market design, market fundamentalism, Mexican peso crisis / tequila crisis, Milgram experiment, money market fund, moral hazard, new economy, open economy, pattern recognition, Ponzi scheme, price anchoring, random walk, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, Small Order Execution System, spice trade, statistical model, stocks for the long run, survivorship bias, the market place, Tobin tax, transaction costs, tulip mania, urban decay, Y2K

Securities and Exchange Commission, “Special Study: On-Line Brokerage: Keeping Apace of Cyberspace,” 1999, http://www.sec.gov/pdf/ cybrtrnd.pdf. 35. See Kenneth R. French and Richard Roll, “Stock Return Variances: The Arrival of Information and the Reaction of Traders,” Journal of Financial Economics, 17 (1986): 5–26; see also Richard Roll, “Orange Juice and Weather,” American Economic Review, 74 (1984): 861–80. 36. See Shlomo Benartzi and Richard H. Thaler, “Myopic Loss Aversion and the Equity Premium Puzzle,” Quarterly Journal of Economics, 110(1) (1995): 73–92. 37. Data are from the National Gambling Impact Study Commission, Final Report, Washington D.C., 1999, http://www.ngisc.gov/reports/exsum_1-7.pdf. 38. See also William N. Thompson, Legalized Gambling: A Reference Handbook (Santa Barbara, Calif.: ABC-CLIO, 1994), pp. 52–53. 39. Quantitative evidence on gambling behavior is hard to come by for the 1920s.

“The International Diversification Puzzle Is Worse Than You Think,” American Economic Review, 87 (1997): 177–80. Bell, David E. “Regret in Decision Making under Uncertainty.” Operations Research, 30(5) (1982): 961–81. Benartzi, Shlomo. “Why Do Employees Invest Their Retirement Savings in Company Stock?” Unpublished paper, Anderson School, University of California, Los Angeles, 1999. Benartzi, Shlomo, and Richard H. Thaler. “Myopic Loss Aversion and the Equity Premium Puzzle.” Quarterly Journal of Economics, 110(1) (1995): 73–92. ———. “Naive Diversification Strategies in Defined Contribution Plans.” Unpublished paper, University of Chicago, 1998. RE F E RE N CE S 271 Bikhchandani, S. D., David Hirshleifer, and Ivo Welch. “A Theory of Fashion, Social Custom and Cultural Change.” Journal of Political Economy, 81 (1992): 637–54. Blanchard, Olivier, and Stanley Fischer.


pages: 383 words: 108,266

Predictably Irrational, Revised and Expanded Edition: The Hidden Forces That Shape Our Decisions by Dan Ariely

air freight, Al Roth, Bernie Madoff, Burning Man, butterfly effect, Cass Sunstein, collateralized debt obligation, computer vision, corporate governance, credit crunch, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, endowment effect, financial innovation, fudge factor, Gordon Gekko, greed is good, housing crisis, IKEA effect, invisible hand, lake wobegon effect, late fees, loss aversion, market bubble, Murray Gell-Mann, payday loans, placebo effect, price anchoring, Richard Thaler, second-price auction, Silicon Valley, Skype, The Wealth of Nations by Adam Smith, Upton Sinclair

RELATED READINGS Richard Thaler, “Toward a Positive Theory of Consumer Choice,” Journal of Economic Behavior and Organization (1980). Jack Knetsch, “The Endowment Effect and Evidence of Nonreversible Indifference Curves,” American Economic Review, Vol. 79 (1989), 1277–1284. Daniel Kahneman, Jack Knetsch, and Richard Thaler, “Experimental Tests of the Endowment Effect and the Coase Theorem,” Journal of Political Economy (1990). Daniel Kahneman, Jack Knetsch, and Richard H. Thaler, “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias,” Journal of Economic Perspectives, Vol. 5 (1991), 193–206. Chapter 8: Keeping Doors Open BASED ON Jiwoong Shin and Dan Ariely, “Keeping Doors Open: The Effect of Unavailability on Incentives to Keep Options Viable,” Management Science (2004). RELATED READINGS Sheena Iyengar and Mark Lepper, “When Choice Is De-motivating: Can One Desire Too Much of a Good Thing?”

., 273–74 job performance. 320–24 public scrutiny and, 322 relationship between compensation and, 320–21, 322–24 Jobst suit, 192–94 Johnston, David Cay, 204 JP Morgan Chase, 280 judgment and decision making (JDM), xxviii see also behavioral economics “Just say no” campaign, 100, 101 K Kahneman, Daniel, 19, 129 Keeney, Ralph, 264 knee surgery, arthroscopic, 174–76 Knetsch, Jack, 129 Knight-McDowell, Victoria, 277 Koran, 215 L “Lake Wobegone Effect,” 268–69 Latin America, lack of trust in, 214 Lay, Kenneth, 219 learned helplessness, 312–16 experiments on, 312–14 in financial meltdown, 314–16 recovering from, 315–16 Leaves of Grass (Whitman), 40–41 Lee, Leonard, 21, 157–59, 161, 337 legal profession: attempts at improving ethics of, 213–14 decline of ethics and values in, 209–10 Lehman Brothers, 280, 310 leisure, blurring of partition between work and, 80, 81 Leland, John, 122–23 Leo III, Pope, 188 Leonardo da Vinci, 274 Levav, Jonathan, 231–37, 337 Levitt, Steven, xvi Li, Jian, 166–68 Lincoln, Abraham, 177 Linux, 81 List, John, xvi loans: punitive finance practices and, 300–301, 304 see also mortgages lobbyists, congressional restrictions on, 205 Loewenstein, George, 21, 26, 30–31, 39, 89,, 320–21, 337–38 Logic of Life, The (Harford), 291–92 Lorenz, Konrad, 25, 43 loss: aversion to, 134, 137, 138, 148–49 fear of, 54–55 Lost World, The (Crichton), 317–18 loyalty: in business-customer relations, 78–79 of employees to their companies, 80–84 M Macbeth (Shakespeare), 188 Madoff, Bernard, 291 Maier, Steve, 312-13 major, college students’ choice of, 141–42 manufacturer’s suggested retail price (MSRP), 30, 45 marketing: high price tag and, 24–25 hype of, related to satisfaction derived from product, 186–87, 190–91 relativity and, 1–6, 9–10 “trial” promotions and, 136–37 zero cost and, 49–50 market norms, 67–88 companies’ relations with their customers and, 78–80 companies’ relations with their employees and, 80–84, 252–54 doing away with, 86–88 education and, 85 mere mention of money and, 73–75 mixing signals of social norms and, 69, 73–74, 75–77, 79, 214, 250–52 reducing emphasis on, 88 social norms kept separate from, 67–69, 75–76, 77–78 willingness to risk life and, 84 working for gifts and, 72–74 working under social norms vs., 69–72 Maryland Judicial Task Force, 210 Mazar, Nina, 196–97, 206, 219–20, 224, 320–21, 338 McClure, Sam, 166–68 Mead, Nicole, 74–75 medical benefits, recent cuts in, 82 medical care, see health care medical profession: conflicts of interest and, 293, 295 decline of ethics and values in, 210 salaries of, as practicing physicians vs.


pages: 407 words: 104,622

The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman

affirmative action, Affordable Care Act / Obamacare, Albert Einstein, Andrew Wiles, automated trading system, backtesting, Bayesian statistics, beat the dealer, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, blockchain, Brownian motion, butter production in bangladesh, buy and hold, buy low sell high, Claude Shannon: information theory, computer age, computerized trading, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversified portfolio, Donald Trump, Edward Thorp, Elon Musk, Emanuel Derman, endowment effect, Flash crash, George Gilder, Gordon Gekko, illegal immigration, index card, index fund, Isaac Newton, John Meriwether, John Nash: game theory, John von Neumann, Loma Prieta earthquake, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, Mark Zuckerberg, More Guns, Less Crime, Myron Scholes, Naomi Klein, natural language processing, obamacare, p-value, pattern recognition, Peter Thiel, Ponzi scheme, prediction markets, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, Robert Mercer, Ronald Reagan, self-driving car, Sharpe ratio, Silicon Valley, sovereign wealth fund, speech recognition, statistical arbitrage, statistical model, Steve Jobs, stochastic process, the scientific method, Thomas Bayes, transaction costs, Turing machine

In the 1970s, Israeli psychologists Amos Tversky and Daniel Kahneman had explored how individuals make decisions, demonstrating how prone most are to act irrationally. Later, economist Richard Thaler used psychological insights to explain anomalies in investor behavior, spurring the growth of the field of behavioral economics, which explored the cognitive biases of individuals and investors. Among those identified: loss aversion, or how investors generally feel the pain from losses twice as much as the pleasure from gains; anchoring, the way judgment is skewed by an initial piece of information or experience; and the endowment effect, how investors assign excessive value to what they already own in their portfolios. Kahneman and Thaler would win Nobel Prizes for their work. A consensus would emerge that investors act more irrationally than assumed, repeatedly making similar mistakes.

., 31, 78 Kepler Financial Management, 133–34, 157, 166–67 kernel methods, 84–86, 96 Kirtland Air Force Base, 170–71 Klein, Naomi, 321 Koch, Charles, 278 Koch, David, 278 Kochen, Simon, 69–70, 71, 103 Kononenko, Alexey, 236–37, 241–43, 262–63, 270–71 Kostant, Bertram, 18, 20 Kovner, Bruce, 140 Kurz, Christopher, 121–22 Kushner, Jared, 281, 292 Lackman, Abe, 286 Laufer, Henry, xi, 101 background of, 140–41 Long Island Sound estate of, 227–28 at Renaissance, 109, 141–44, 149–50, 201, 229–31, 233 at Stony Brook, 77, 78, 84–85, 141–42 trading models, 77, 107–18, 142–43, 149–50, 156, 168, 189, 197, 229–30, 253, 258 Laufer, Marsha Zlatin, 141–42 Law of Vibration, 123 Lawrence School, 13 Leave.EU, 280–81 L’eggs, 162 Lehman Brothers, 173, 264, 309 Leibler, Dick, 26, 30–31, 32 Leinweber, David, 204 Leo, Leonard, 290 Let’s Make a Deal (TV show), 211 leverage, 188 Lewinsky, Monica, 208 Lieberman, Louis, 46 Limroy, 50–51, 53, 54, 55, 58, 98, 346 linear regression, 83–84 liquidity, 229 Lo, Andrew, 123, 124 locals, 110 Loma Prieta earthquake of 1989, 107 Long-Term Capital Management (LTCM), 209–11, 212–13, 226, 256 Lord Jim, The (yacht), 60 loss aversion, 152 Lott, John R., Jr., 207 Lourie, Robert, 11, 228, 257 Lux, Hal, 218 Lynch, Carolyn, 162 Lynch, Peter, xvi, 3, 161–63 McCain, John, 304 McCarthy, David, 154 McCarthy, Eugene, 74 McGrayne, Sharon, 202 machine learning, 4–5, 47–48, 144, 205, 215, 315 McNulty, Bill, 295 Macrae, Kenny, 267 macro investors, 164 “macroscopic variables,” 29 Madoff, Bernard, 146n, 198 Magellan Fund, 161–63, 333 Magerman, David, xi background of, 182–84 computer hacking of, 191–93, 213 confrontational behavior of, 235, 270 education of, 183–85 at IBM, 177, 181, 185, 191–92 Mercers and, 195, 213–14, 232, 277, 291–99, 318 at Penn, 270 philanthropic activity of, 270, 318 presidential election of 2016 and Trump, 290–94 Magerman, David, at Renaissance Brown and, 181–82, 191–95, 241, 294, 296, 297, 299, 318 computer bug, 194–95, 213 departures, 262–63, 269–70 firing, 317–18 Kononenko and, 237, 241–43, 262–63, 270–71 lawsuit and financial settlement, 318–19 misgivings of, 269–70 recruitment of, 181–82, 186–87 return to, 270–71 Simons and, 181–82, 186–87, 234–35, 237, 296–99 tech bubble, 215–17 trading system, 186–87, 191–95, 213–17, 234–36 Magerman, Debra, 291, 292 Magerman, Melvin, 182–83, 184 Mahlmann, Karsten, 114 Malloy, Martin, 259 management fees, 115n, 248 Man AHL, 313 Mandelbrot, Benoit, 127 Man for All Markets, A (Thorp), 128 Manhattan Fund, 123 market neutral, 166–67, 211, 255 Markov chains, 46–48, 81 Markov model, xx, 29, 174 Markowitz, Harry, 30 Massachusetts Institute of Technology (MIT), 9, 14–16, 17, 20–21, 89–91, 325–26 Mathematical Sciences Research Institute, 236–37 Math for America, 269, 296–99, 321 Matrix, The (movie), 307 Mattone, Vinny, 210–11 Mayer, Jane, 280 Mayer, Jimmy, 15, 16–17, 21, 38–39, 50 Mazur, Barry, 15 Medallion Fund basket options, 225–27 fees, 145–46, 235–36, 271, 315–16 financial crisis and, 257–61, 263–64 GAM Investments, 153–54 launch of, 98 move into stock investing, 157–58 returns, xvi, 140, 145–46, 151, 153, 156, 157, 215, 217–18, 223–24, 225, 247–48, 255, 271, 315–16, 319, 331–32 returns comparison, 333 Sharpe ratio, 218, 223–24, 245 size limit, 246–47 trading models, 107–9, 113, 138–40, 142–43, 156–57, 168, 197–205, 271–74 Media Research Center, 304 Mercer, Diana, 179, 186, 214, 228, 288 Mercer, Heather Sue, 207, 214, 228 Mercer, Jennifer “Jenji,” 179, 186, 228 Mercer, Rebekah, xi, 228 Bannon and Breitbart News, 278–83, 288–90, 294–95, 301–2 emergence as right-wing donor, 277–79, 301–2 Magerman and, 214, 291, 293, 298, 299 political blowback and, 301–2, 303–5 presidential election of 2016 and Trump, xviii, 279–86, 288–90, 294–95 at Renaissance, 214 Mercer, Robert, xi background of, 169–70 education of, 169–70 emergence as right-wing donor, xviii, 276–86, 325–26 at IBM, 4–5, 169, 171–81, 187–88, 202 interest in computers, 170–71 at Kirtland Air Force Base, 170–71 libertarian views of, 171, 207–8, 232, 235, 275–77 presidential election of 2016 and Trump, xviii, 279–87, 291–95, 299–300, 302 Stony Brook Harbor estate (Owl’s Nest), 228, 275, 288–89, 295 Mercer, Robert, at Renaissance client presentations, 251 as co-CEO, xviiin, 231, 290, 301 equity stake, 201 financial crisis and, 257–61 Magerman and, 195, 213–14, 232, 277, 291–99, 318 management, 230–31, 232–33, 237, 241–43, 254–55, 289–90 political blowback and, 291–305 recruitment of, 169, 179–80 resignation of, 301–2, 319 statistical-arbitrage trading system, 4–5, 187–91, 193–95, 197–99, 205–8, 213–14, 221–22, 223, 229–32, 255, 272 tech bubble, 215–17 Mercer, Thomas, 169, 179 Mercer, Virginia, 169 Mercer Family Foundation, 276 Meriwether, John, 209–11, 212 Merrill Lynch, 19–20, 54, 96 Merton, Robert C., 209 Mexico–United States border wall, 290–91 Microsoft, 38, 59 Milken, Michael, 105–6, 129 Millennium Management, 238, 252–54 minimal varieties, 26–28, 38 “Minimal Varieties in Riemannian Manifolds” (Simons), 28 Mirochnikoff, Sylvain, 278 Mississippi, 13–14 Mnuchin, Steve, 282 Monemetrics Ax at, 34, 51–52, 72–73 Baum at, 45, 49–60, 63–65 founding and naming of, 44–45 Hullender at, 54–59, 74 name change to Renaissance, 61.


pages: 464 words: 117,495

The New Trading for a Living: Psychology, Discipline, Trading Tools and Systems, Risk Control, Trade Management by Alexander Elder

additive manufacturing, Atul Gawande, backtesting, Benoit Mandelbrot, buy and hold, buy low sell high, Checklist Manifesto, computerized trading, deliberate practice, diversification, Elliott wave, endowment effect, loss aversion, mandelbrot fractal, margin call, offshore financial centre, paper trading, Ponzi scheme, price stability, psychological pricing, quantitative easing, random walk, risk tolerance, short selling, South Sea Bubble, systematic trading, The Wisdom of Crowds, transaction costs, transfer pricing, traveling salesman, tulip mania, zero-sum game

They go into risky gambles to postpone taking losses. It is human nature to take profits quickly and losses slowly. The irrational behavior increases when people feel under pressure. According to Dr. Shapiro, at the racetrack, “bets on long shots increase in the last two races of the day.” Prof. Daniel Kahneman writes in his book Thinking, Fast and Slow: “The sure loss is very aversive, and this drives you to take the risk … Considerable loss aversion exists even when the amount at risk is minuscule relative to your wealth … losses loom larger than corresponding gains.” He adds: “Animals, including people, fight harder to prevent losses than to achieve gains” and spells it out: “People who face very bad options take desperate gambles, accepting a high probability of making things worse in exchange for a small hope of avoiding a large loss.

See also Timeframes; individual indicators Intrinsic value (options) Inverse ETFs Inversions (futures) Investing (long-term trading) Investors Intelligence Iron Triangle of risk control, the Isolation in trading J Japanese candlesticks Japanese Candlestick Charting Techniques (Steve Nison) K Kahneman, Daniel Kangaroo tails (fingers) Kaufman, Josh Keelan, Brian Key demands for trades Keynes, John Maynard L Lag, of moving averages Lane, George Large speculators Larsen, Max Leaders: of crowds and fear of uncertainty gurus dead followers of magic method market cycle loyalty to Learning trading skills LeBon, Gustave Letter writers (financial) Leverage, in forex Leveraged ETFs Leveraged inverse ETFs Life, taking charge of Limits, on futures Limit orders Liquidity Long-term price cycles Long-term timeframe Long-term trading (investing) Look-back windows (New High–New Low Index) Losers: AA principles for denial by emotional responses of and emotional trading fantasies of autopilot myth brain myth cult of personality undercapitalization myth pain and regret felt by and self-control vs. controlling markets self-destructive and volume of trading wishful thinking by Losers Anonymous Losses: in account as a whole businessman's risks vs. on CFDs cutting of former institutional traders inability to manage on options per share, limiting psychological effect of 6% Rule to limit 2% Rule to limit Loss aversion Lovvorn, Kerry Low-priced stocks, indictors based on volume of “Low” volume M MAs, see Moving averages MACD, see Moving Average Convergence-Divergence MACD-Histogram combined with channels divergences in Impulse system and market psychology peaks and valleys seasons of semiautomatic divergence scanner slope of time windows of trading rules in Triple Screen system MACD Lines crossover of Signal lines and MACD line in divergences and market psychology trading rules Mackay, Charles MacMillan, Lawrence Magic method gurus Managing trades forecasting vs.


pages: 403 words: 111,119

Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist by Kate Raworth

"Robert Solow", 3D printing, Asian financial crisis, bank run, basic income, battle of ideas, Berlin Wall, bitcoin, blockchain, Branko Milanovic, Bretton Woods, Buckminster Fuller, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, choice architecture, clean water, cognitive bias, collapse of Lehman Brothers, complexity theory, creative destruction, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, dematerialisation, disruptive innovation, Douglas Engelbart, Douglas Engelbart, en.wikipedia.org, energy transition, Erik Brynjolfsson, Ethereum, ethereum blockchain, Eugene Fama: efficient market hypothesis, experimental economics, Exxon Valdez, Fall of the Berlin Wall, financial deregulation, Financial Instability Hypothesis, full employment, global supply chain, global village, Henri Poincaré, hiring and firing, Howard Zinn, Hyman Minsky, income inequality, Intergovernmental Panel on Climate Change (IPCC), invention of writing, invisible hand, Isaac Newton, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kickstarter, land reform, land value tax, Landlord’s Game, loss aversion, low skilled workers, M-Pesa, Mahatma Gandhi, market fundamentalism, Martin Wolf, means of production, megacity, mobile money, Mont Pelerin Society, Myron Scholes, neoliberal agenda, Network effects, Occupy movement, off grid, offshore financial centre, oil shale / tar sands, out of africa, Paul Samuelson, peer-to-peer, planetary scale, price mechanism, quantitative easing, randomized controlled trial, Richard Thaler, Ronald Reagan, Second Machine Age, secular stagnation, shareholder value, sharing economy, Silicon Valley, Simon Kuznets, smart cities, smart meter, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, statistical model, Steve Ballmer, The Chicago School, The Great Moderation, the map is not the territory, the market place, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, too big to fail, Torches of Freedom, trickle-down economics, ultimatum game, universal basic income, Upton Sinclair, Vilfredo Pareto, wikimedia commons

His findings, augmented by those of psychologists Daniel Kahneman and Amos Tversky in the 1970s, gave birth to the field now known as behavioural economics, which studies the many kinds of ‘cognitive bias’ that systematically cause humans to deviate from the ideal model of rationality. Examples abound. We (the WEIRD ones, at least) typically exhibit: availability bias – making decisions on the basis of more recent and more accessible information; loss aversion – the strong preference to avoid a loss rather than to make an equivalent gain; selective cognition – taking on board facts and arguments that fit with our existing frames; and risk bias – underestimating the likelihood of extreme events, while overestimating our ability to cope with them. There are many more. Indeed one Wikipedia page lists over 160 cognitive biases, like a jumbo-size game of spot-the-difference between rational economic man and his fallible human equivalent.36 What to do in the face of such irrational shortcomings?

Page numbers in italics denote illustrations A Aalborg, Denmark, 290 Abbott, Anthony ‘Tony’, 31 ABCD group, 148 Abramovitz, Moses, 262 absolute decoupling, 260–61 Acemoglu, Daron, 86 advertising, 58, 106–7, 112, 281 Agbodjinou, Sénamé, 231 agriculture, 5, 46, 72–3, 148, 155, 178, 181, 183 Alaska, 9 Alaska Permanent Fund, 194 Alperovitz, Gar, 177 alternative enterprise designs, 190–91 altruism, 100, 104 Amazon, 192, 196, 276 Amazon rainforest, 105–6, 253 American Economic Association, 3 American Enterprise Institute, 67 American Tobacco Corporation, 107 Andes, 54 animal spirits, 110 Anthropocene epoch, 48, 253 anthropocentrism, 115 Apertuso, 230 Apple, 85, 192 Archer Daniels Midland (ADM), 148 Arendt, Hannah, 115–16 Argentina, 55, 274 Aristotle, 32, 272 Arrow, Kenneth, 134 Articles of Association and Memoranda, 233 Arusha, Tanzania, 202 Asia Wage Floor Alliance, 177 Asian financial crisis (1997), 90 Asknature.org, 232 Athens, 57 austerity, 163 Australia, 31, 103, 177, 180, 211, 224–6, 255, 260 Austria, 263, 274 availability bias, 112 AXIOM, 230 Axtell, Robert, 150 Ayres, Robert, 263 B B Corp, 241 Babylon, 13 Baker, Josephine, 157 balancing feedback loops, 138–41, 155, 271 Ballmer, Steve, 231 Bangla Pesa, 185–6, 293 Bangladesh, 10, 226 Bank for International Settlements, 256 Bank of America, 149 Bank of England, 145, 147, 256 banking, see under finance Barnes, Peter, 201 Barroso, José Manuel, 41 Bartlett, Albert Allen ‘Al’, 247 basic income, 177, 194, 199–201 basic personal values, 107–9 Basle, Switzerland, 80 Bauwens, Michel, 197 Beckerman, Wilfred, 258 Beckham, David, 171 Beech-Nut Packing Company, 107 behavioural economics, 11, 111–14 behavioural psychology, 103, 128 Beinhocker, Eric, 158 Belgium, 236, 252 Bentham, Jeremy, 98 Benyus, Janine, 116, 218, 223–4, 227, 232, 237, 241 Berger, John, 12, 281 Berlin Wall, 141 Bermuda, 277 Bernanke, Ben, 146 Bernays, Edward, 107, 112, 281–3 Bhopal gas disaster (1984), 9 Bible, 19, 114, 151 Big Bang (1986), 87 billionaires, 171, 200, 289 biodiversity, 10, 46, 48–9, 52, 85, 115, 155, 208, 210, 242, 299 as common pool resource, 201 and land conversion, 49 and inequality, 172 and reforesting, 50 biomass, 73, 118, 210, 212, 221 biomimicry, 116, 218, 227, 229 bioplastic, 224, 293 Birmingham, West Midlands, 10 Black, Fischer, 100–101 Blair, Anthony ‘Tony’, 171 Blockchain, 187, 192 blood donation, 104, 118 Body Shop, The, 232–4 Bogotá, Colombia, 119 Bolivia, 54 Boston, Massachusetts, 3 Bowen, Alex, 261 Bowles, Sam, 104 Box, George, 22 Boyce, James, 209 Brasselberg, Jacob, 187 Brazil, 124, 226, 281, 290 bread riots, 89 Brisbane, Australia, 31 Brown, Gordon, 146 Brynjolfsson, Erik, 193, 194, 258 Buddhism, 54 buen vivir, 54 Bullitt Center, Seattle, 217 Bunge, 148 Burkina Faso, 89 Burmark, Lynell, 13 business, 36, 43, 68, 88–9 automation, 191–5, 237, 258, 278 boom and bust, 246 and circular economy, 212, 215–19, 220, 224, 227–30, 232–4, 292 and complementary currencies, 184–5, 292 and core economy, 80 and creative destruction, 142 and feedback loops, 148 and finance, 183, 184 and green growth, 261, 265, 269 and households, 63, 68 living metrics, 241 and market, 68, 88 micro-businesses, 9 and neoliberalism, 67, 87 ownership, 190–91 and political funding, 91–2, 171–2 and taxation, 23, 276–7 workers’ rights, 88, 91, 269 butterfly economy, 220–42 C C–ROADS (Climate Rapid Overview and Decision Support), 153 C40 network, 280 calculating man, 98 California, United States, 213, 224, 293 Cambodia, 254 Cameron, David, 41 Canada, 196, 255, 260, 281, 282 cancer, 124, 159, 196 Capital Institute, 236 carbon emissions, 49–50, 59, 75 and decoupling, 260, 266 and forests, 50, 52 and inequality, 58 reduction of, 184, 201, 213, 216–18, 223–7, 239–41, 260, 266 stock–flow dynamics, 152–4 taxation, 201, 213 Cargill, 148 Carney, Mark, 256 Caterpillar, 228 Catholic Church, 15, 19 Cato Institute, 67 Celts, 54 central banks, 6, 87, 145, 146, 147, 183, 184, 256 Chang, Ha-Joon, 82, 86, 90 Chaplin, Charlie, 157 Chiapas, Mexico, 121–2 Chicago Board Options Exchange (CBOE), 100–101 Chicago School, 34, 99 Chile, 7, 42 China, 1, 7, 48, 154, 289–90 automation, 193 billionaires, 200, 289 greenhouse gas emissions, 153 inequality, 164 Lake Erhai doughnut analysis, 56 open-source design, 196 poverty reduction, 151, 198 renewable energy, 239 tiered pricing, 213 Chinese Development Bank, 239 chrematistics, 32, 273 Christianity, 15, 19, 114, 151 cigarettes, 107, 124 circular economy, 220–42, 257 Circular Flow diagram, 19–20, 28, 62–7, 64, 70, 78, 87, 91, 92, 93, 262 Citigroup, 149 Citizen Reaction Study, 102 civil rights movement, 77 Cleveland, Ohio, 190 climate change, 1, 3, 5, 29, 41, 45–53, 63, 74, 75–6, 91, 141, 144, 201 circular economy, 239, 241–2 dynamics of, 152–5 and G20, 31 and GDP growth, 255, 256, 260, 280 and heuristics, 114 and human rights, 10 and values, 126 climate positive cities, 239 closed systems, 74 coffee, 221 cognitive bias, 112–14 Colander, David, 137 Colombia, 119 common-pool resources, 82–3, 181, 201–2 commons, 69, 82–4, 287 collaborative, 78, 83, 191, 195, 196, 264, 292 cultural, 83 digital, 82, 83, 192, 197, 281 and distribution, 164, 180, 181–2, 205, 267 Embedded Economy, 71, 73, 77–8, 82–4, 85, 92 knowledge, 197, 201–2, 204, 229, 231, 292 commons and money creation, see complementary currencies natural, 82, 83, 180, 181–2, 201, 265 and regeneration, 229, 242, 267, 292 and state, 85, 93, 197, 237 and systems, 160 tragedy of, 28, 62, 69, 82, 181 triumph of, 83 and values, 106, 108 Commons Trusts, 201 complementary currencies, 158, 182–8, 236, 292 complex systems, 28, 129–62 complexity science, 136–7 Consumer Reaction Study, 102 consumerism, 58, 102, 121, 280–84 cooking, 45, 80, 186 Coote, Anna, 278 Copenhagen, Denmark, 124 Copernicus, Nicolaus, 14–15 copyright, 195, 197, 204 core economy, 79–80 Corporate To Do List, 215–19 Costa Rica, 172 Council of Economic Advisers, US, 6, 37 Cox, Jo, 117 cradle to cradle, 224 creative destruction, 142 Cree, 282 Crompton, Tom, 125–6 cross-border flows, 89–90 crowdsourcing, 204 cuckoos, 32, 35, 36, 38, 40, 54, 60, 159, 244, 256, 271 currencies, 182–8, 236, 274, 292 D da Vinci, Leonardo, 13, 94–5 Dallas, Texas, 120 Daly, Herman, 74, 143, 271 Danish Nudging Network, 124 Darwin, Charles, 14 Debreu, Gerard, 134 debt, 37, 146–7, 172–3, 182–5, 247, 255, 269 decoupling, 193, 210, 258–62, 273 defeat device software, 216 deforestation, 49–50, 74, 208, 210 degenerative linear economy, 211–19, 222–3, 237 degrowth, 244 DeMartino, George, 161 democracy, 77, 171–2, 258 demurrage, 274 Denmark, 180, 275, 290 deregulation, 82, 87, 269 derivatives, 100–101, 149 Devas, Charles Stanton, 97 Dey, Suchitra, 178 Diamond, Jared, 154 diarrhoea, 5 differential calculus, 131, 132 digital revolution, 191–2, 264 diversify–select–amplify, 158 double spiral, 54 Doughnut model, 10–11, 11, 23–5, 44, 51 and aspiration, 58–9, 280–84 big picture, 28, 42, 61–93 distribution, 29, 52, 57, 58, 76, 93, 158, 163–205 ecological ceiling, 10, 11, 44, 45, 46, 49, 51, 218, 254, 295, 298 goal, 25–8, 31–60 and governance, 57, 59 growth agnosticism, 29–30, 243–85 human nature, 28–9, 94–128 and population, 57–8 regeneration, 29, 158, 206–42 social foundation, 10, 11, 44, 45, 49, 51, 58, 77, 174, 200, 254, 295–6 systems, 28, 129–62 and technology, 57, 59 Douglas, Margaret, 78–9 Dreyfus, Louis, 148 ‘Dumb and Dumber in Macroeconomics’ (Solow), 135 Durban, South Africa, 214 E Earning by Learning, 120 Earth-system science, 44–53, 115, 216, 288, 298 Easter Island, 154 Easterlin, Richard, 265–6 eBay, 105, 192 eco-literacy, 115 ecological ceiling, 10, 11, 44, 45, 46, 49, 51, 218, 254, 295, 298 Ecological Performance Standards, 241 Econ 101 course, 8, 77 Economics (Lewis), 114 Economics (Samuelson), 19–20, 63–7, 70, 74, 78, 86, 91, 92, 93, 262 Economy for the Common Good, 241 ecosystem services, 7, 116, 269 Ecuador, 54 education, 9, 43, 45, 50–52, 85, 169–70, 176, 200, 249, 279 economic, 8, 11, 18, 22, 24, 36, 287–93 environmental, 115, 239–40 girls’, 57, 124, 178, 198 online, 83, 197, 264, 290 pricing, 118–19 efficient market hypothesis, 28, 62, 68, 87 Egypt, 48, 89 Eisenstein, Charles, 116 electricity, 9, 45, 236, 240 and Bangla Pesa, 186 cars, 231 Ethereum, 187–8 and MONIAC, 75, 262 pricing, 118, 213 see also renewable energy Elizabeth II, Queen of the United Kingdom, 145 Ellen MacArthur Foundation, 220 Embedded Economy, 71–93, 263 business, 88–9 commons, 82–4 Earth, 72–6 economy, 77–8 finance, 86–8 household, 78–81 market, 81–2 power, 91–92 society, 76–7 state, 84–6 trade, 89–90 employment, 36, 37, 51, 142, 176 automation, 191–5, 237, 258, 278 labour ownership, 188–91 workers’ rights, 88, 90, 269 Empty World, 74 Engels, Friedrich, 88 environment and circular economy, 220–42, 257 conservation, 121–2 and degenerative linear economy, 211–19, 222–3 degradation, 5, 9, 10, 29, 44–53, 74, 154, 172, 196, 206–42 education on, 115, 239–40 externalities, 152 fair share, 216–17 and finance, 234–7 generosity, 218–19, 223–7 green growth, 41, 210, 243–85 nudging, 123–5 taxation and quotas, 213–14, 215 zero impact, 217–18, 238, 241 Environmental Dashboard, 240–41 environmental economics, 7, 11, 114–16 Environmental Kuznets Curve, 207–11, 241 environmental space, 54 Epstein, Joshua, 150 equilibrium theory, 134–62 Ethereum, 187–8 ethics, 160–62 Ethiopia, 9, 226, 254 Etsy, 105 Euclid, 13, 15 European Central Bank, 145, 275 European Commission, 41 European Union (EU), 92, 153, 210, 222, 255, 258 Evergreen Cooperatives, 190 Evergreen Direct Investing (EDI), 273 exogenous shocks, 141 exponential growth, 39, 246–85 externalities, 143, 152, 213 Exxon Valdez oil spill (1989), 9 F Facebook, 192 fair share, 216–17 Fama, Eugene, 68, 87 fascism, 234, 277 Federal Reserve, US, 87, 145, 146, 271, 282 feedback loops, 138–41, 143, 148, 155, 250, 271 feminist economics, 11, 78–81, 160 Ferguson, Thomas, 91–2 finance animal spirits, 110 bank runs, 139 Black–Scholes model, 100–101 boom and bust, 28–9, 110, 144–7 and Circular Flow, 63–4, 87 and complex systems, 134, 138, 139, 140, 141, 145–7 cross-border flows, 89 deregulation, 87 derivatives, 100–101, 149 and distribution, 169, 170, 173, 182–4, 198–9, 201 and efficient market hypothesis, 63, 68 and Embedded Economy, 71, 86–8 and financial-instability hypothesis, 87, 146 and GDP growth, 38 and media, 7–8 mobile banking, 199–200 and money creation, 87, 182–5 and regeneration, 227, 229, 234–7 in service to life, 159, 234–7 stakeholder finance, 190 and sustainability, 216, 235–6, 239 financial crisis (2008), 1–4, 5, 40, 63, 86, 141, 144, 278, 290 and efficient market hypothesis, 87 and equilibrium theory, 134, 145 and financial-instability hypothesis, 87 and inequality, 90, 170, 172, 175 and money creation, 182 and worker’s rights, 278 financial flows, 89 Financial Times, 183, 266, 289 financial-instability hypothesis, 87, 146 First Green Bank, 236 First World War (1914–18), 166, 170 Fisher, Irving, 183 fluid values, 102, 106–9 food, 3, 43, 45, 50, 54, 58, 59, 89, 198 food banks, 165 food price crisis (2007–8), 89, 90, 180 Ford, 277–8 foreign direct investment, 89 forest conservation, 121–2 fossil fuels, 59, 73, 75, 92, 212, 260, 263 Foundations of Economic Analysis (Samuelson), 17–18 Foxconn, 193 framing, 22–3 France, 43, 165, 196, 238, 254, 256, 281, 290 Frank, Robert, 100 free market, 33, 37, 67, 68, 70, 81–2, 86, 90 free open-source hardware (FOSH), 196–7 free open-source software (FOSS), 196 free trade, 70, 90 Freeman, Ralph, 18–19 freshwater cycle, 48–9 Freud, Sigmund, 107, 281 Friedman, Benjamin, 258 Friedman, Milton, 34, 62, 66–9, 84–5, 88, 99, 183, 232 Friends of the Earth, 54 Full World, 75 Fuller, Buckminster, 4 Fullerton, John, 234–6, 273 G G20, 31, 56, 276, 279–80 G77, 55 Gal, Orit, 141 Gandhi, Mohandas, 42, 293 Gangnam Style, 145 Gardens of Democracy, The (Liu & Hanauer), 158 gender equality, 45, 51–2, 57, 78–9, 85, 88, 118–19, 124, 171, 198 generosity, 218–19, 223–9 geometry, 13, 15 George, Henry, 149, 179 Georgescu-Roegen, Nicholas, 252 geothermal energy, 221 Gerhardt, Sue, 283 Germany, 2, 41, 100, 118, 165, 189, 211, 213, 254, 256, 260, 274 Gessel, Silvio, 274 Ghent, Belgium, 236 Gift Relationship, The (Titmuss), 118–19 Gigerenzer, Gerd, 112–14 Gintis, Herb, 104 GiveDirectly, 200 Glass–Steagall Act (1933), 87 Glennon, Roger, 214 Global Alliance for Tax Justice, 277 global material footprints, 210–11 Global Village Construction Set, 196 globalisation, 89 Goerner, Sally, 175–6 Goffmann, Erving, 22 Going for Growth, 255 golden rule, 91 Goldman Sachs, 149, 170 Gómez-Baggethun, Erik, 122 Goodall, Chris, 211 Goodwin, Neva, 79 Goody, Jade, 124 Google, 192 Gore, Albert ‘Al’, 172 Gorgons, 244, 256, 257, 266 graffiti, 15, 25, 287 Great Acceleration, 46, 253–4 Great Depression (1929–39), 37, 70, 170, 173, 183, 275, 277, 278 Great Moderation, 146 Greece, Ancient, 4, 13, 32, 48, 54, 56–7, 160, 244 green growth, 41, 210, 243–85 Greenham, Tony, 185 greenhouse gas emissions, 31, 46, 50, 75–6, 141, 152–4 and decoupling, 260, 266 and Environmental Kuznets Curve, 208, 210 and forests, 50, 52 and G20, 31 and inequality, 58 reduction of, 184, 201–2, 213, 216–18, 223–7, 239–41, 256, 259–60, 266, 298 stock–flow dynamics, 152–4 and taxation, 201, 213 Greenland, 141, 154 Greenpeace, 9 Greenspan, Alan, 87 Greenwich, London, 290 Grenoble, France, 281 Griffiths, Brian, 170 gross domestic product (GDP), 25, 31–2, 35–43, 57, 60, 84, 164 as cuckoo, 32, 35, 36, 38, 40, 54, 60, 159, 244, 256, 271 and Environmental Kuznets Curve, 207–11 and exponential growth, 39, 53, 246–85 and growth agnosticism, 29–30, 240, 243–85 and inequality, 173 and Kuznets Curve, 167, 173, 188–9 gross national product (GNP), 36–40 Gross World Product, 248 Grossman, Gene, 207–8, 210 ‘grow now, clean up later’, 207 Guatemala, 196 H Haifa, Israel, 120 Haldane, Andrew, 146 Han Dynasty, 154 Hanauer, Nick, 158 Hansen, Pelle, 124 Happy Planet Index, 280 Hardin, Garrett, 69, 83, 181 Harvard University, 2, 271, 290 von Hayek, Friedrich, 7–8, 62, 66, 67, 143, 156, 158 healthcare, 43, 50, 57, 85, 123, 125, 170, 176, 200, 269, 279 Heilbroner, Robert, 53 Henry VIII, King of England and Ireland, 180 Hepburn, Cameron, 261 Herbert Simon, 111 heuristics, 113–14, 118, 123 high-income countries growth, 30, 244–5, 254–72, 282 inequality, 165, 168, 169, 171 labour, 177, 188–9, 278 overseas development assistance (ODA), 198–9 resource intensive lifestyles, 46, 210–11 trade, 90 Hippocrates, 160 History of Economic Analysis (Schumpeter), 21 HIV/AIDS, 123 Holocene epoch, 46–8, 75, 115, 253 Homo economicus, 94–103, 109, 127–8 Homo sapiens, 38, 104, 130 Hong Kong, 180 household, 78 housing, 45, 59, 176, 182–3, 269 Howe, Geoffrey, 67 Hudson, Michael, 183 Human Development Index, 9, 279 human nature, 28 human rights, 10, 25, 45, 49, 50, 95, 214, 233 humanistic economics, 42 hydropower, 118, 260, 263 I Illinois, United States, 179–80 Imago Mundi, 13 immigration, 82, 199, 236, 266 In Defense of Economic Growth (Beckerman), 258 Inclusive Wealth Index, 280 income, 51, 79–80, 82, 88, 176–8, 188–91, 194, 199–201 India, 2, 9, 10, 42, 124, 164, 178, 196, 206–7, 242, 290 Indonesia, 90, 105–6, 164, 168, 200 Indus Valley civilisation, 48 inequality, 1, 5, 25, 41, 63, 81, 88, 91, 148–52, 209 and consumerism, 111 and democracy, 171 and digital revolution, 191–5 and distribution, 163–205 and environmental degradation, 172 and GDP growth, 173 and greenhouse gas emissions, 58 and intellectual property, 195–8 and Kuznets Curve, 29, 166–70, 173–4 and labour ownership, 188–91 and land ownership, 178–82 and money creation, 182–8 and social welfare, 171 Success to the Successful, 148, 149, 151, 166 inflation, 36, 248, 256, 275 insect pollination services, 7 Institute of Economic Affairs, 67 institutional economics, 11 intellectual property rights, 195–8, 204 interest, 36, 177, 182, 184, 275–6 Intergovernmental Panel on Climate Change, 25 International Monetary Fund (IMF), 170, 172, 173, 183, 255, 258, 271 Internet, 83–4, 89, 105, 192, 202, 264 Ireland, 277 Iroquois Onondaga Nation, 116 Israel, 100, 103, 120 Italy, 165, 196, 254 J Jackson, Tim, 58 Jakubowski, Marcin, 196 Jalisco, Mexico, 217 Japan, 168, 180, 211, 222, 254, 256, 263, 275 Jevons, William Stanley, 16, 97–8, 131, 132, 137, 142 John Lewis Partnership, 190 Johnson, Lyndon Baines, 37 Johnson, Mark, 38 Johnson, Todd, 191 JPMorgan Chase, 149, 234 K Kahneman, Daniel, 111 Kamkwamba, William, 202, 204 Kasser, Tim, 125–6 Keen, Steve, 146, 147 Kelly, Marjorie, 190–91, 233 Kennedy, John Fitzgerald, 37, 250 Kennedy, Paul, 279 Kenya, 118, 123, 180, 185–6, 199–200, 226, 292 Keynes, John Maynard, 7–8, 22, 66, 69, 134, 184, 251, 277–8, 284, 288 Kick It Over movement, 3, 289 Kingston, London, 290 Knight, Frank, 66, 99 knowledge commons, 202–4, 229, 292 Kokstad, South Africa, 56 Kondratieff waves, 246 Korzybski, Alfred, 22 Krueger, Alan, 207–8, 210 Kuhn, Thomas, 22 Kumhof, Michael, 172 Kuwait, 255 Kuznets, Simon, 29, 36, 39–40, 166–70, 173, 174, 175, 204, 207 KwaZulu Natal, South Africa, 56 L labour ownership, 188–91 Lake Erhai, Yunnan, 56 Lakoff, George, 23, 38, 276 Lamelara, Indonesia, 105–6 land conversion, 49, 52, 299 land ownership, 178–82 land-value tax, 73, 149, 180 Landesa, 178 Landlord’s Game, The, 149 law of demand, 16 laws of motion, 13, 16–17, 34, 129, 131 Lehman Brothers, 141 Leopold, Aldo, 115 Lesotho, 118, 199 leverage points, 159 Lewis, Fay, 178 Lewis, Justin, 102 Lewis, William Arthur, 114, 167 Lietaer, Bernard, 175, 236 Limits to Growth, 40, 154, 258 Linux, 231 Liu, Eric, 158 living metrics, 240–42 living purpose, 233–4 Lomé, Togo, 231 London School of Economics (LSE), 2, 34, 65, 290 London Underground, 12 loss aversion, 112 low-income countries, 90, 164–5, 168, 173, 180, 199, 201, 209, 226, 254, 259 Lucas, Robert, 171 Lula da Silva, Luiz Inácio, 124 Luxembourg, 277 Lyle, John Tillman, 214 Lyons, Oren, 116 M M–PESA, 199–200 MacDonald, Tim, 273 Machiguenga, 105–6 MacKenzie, Donald, 101 macroeconomics, 36, 62–6, 76, 80, 134–5, 145, 147, 150, 244, 280 Magie, Elizabeth, 149, 153 Malala effect, 124 malaria, 5 Malawi, 118, 202, 204 Malaysia, 168 Mali, Taylor, 243 Malthus, Thomas, 252 Mamsera Rural Cooperative, 190 Manhattan, New York, 9, 41 Mani, Muthukumara, 206 Manitoba, 282 Mankiw, Gregory, 2, 34 Mannheim, Karl, 22 Maoris, 54 market, 81–2 and business, 88 circular flow, 64 and commons, 83, 93, 181, 200–201 efficiency of, 28, 62, 68, 87, 148, 181 and equilibrium theory, 131–5, 137, 143–7, 155, 156 free market, 33, 37, 67–70, 90, 208 and households, 63, 69, 78, 79 and maxi-max rule, 161 and pricing, 117–23, 131, 160 and rational economic man, 96, 100–101, 103, 104 and reciprocity, 105, 106 reflexivity of, 144–7 and society, 69–70 and state, 84–6, 200, 281 Marshall, Alfred, 17, 98, 133, 165, 253, 282 Marx, Karl, 88, 142, 165, 272 Massachusetts Institute of Technology (MIT), 17–20, 152–5 massive open online courses (MOOCs), 290 Matthew Effect, 151 Max-Neef, Manfred, 42 maxi-max rule, 161 maximum wage, 177 Maya civilisation, 48, 154 Mazzucato, Mariana, 85, 195, 238 McAfee, Andrew, 194, 258 McDonough, William, 217 Meadows, Donella, 40, 141, 159, 271, 292 Medusa, 244, 257, 266 Merkel, Angela, 41 Messerli, Elspeth, 187 Metaphors We Live By (Lakoff & Johnson), 38 Mexico, 121–2, 217 Michaels, Flora S., 6 micro-businesses, 9, 173, 178 microeconomics, 132–4 microgrids, 187–8 Micronesia, 153 Microsoft, 231 middle class, 6, 46, 58 middle-income countries, 90, 164, 168, 173, 180, 226, 254 migration, 82, 89–90, 166, 195, 199, 236, 266, 286 Milanovic, Branko, 171 Mill, John Stuart, 33–4, 73, 97, 250, 251, 283, 284, 288 Millo, Yuval, 101 minimum wage, 82, 88, 176 Minsky, Hyman, 87, 146 Mises, Ludwig von, 66 mission zero, 217 mobile banking, 199–200 mobile phones, 222 Model T revolution, 277–8 Moldova, 199 Mombasa, Kenya, 185–6 Mona Lisa (da Vinci), 94 money creation, 87, 164, 177, 182–8, 205 MONIAC (Monetary National Income Analogue Computer), 64–5, 75, 142, 262 Monoculture (Michaels), 6 Monopoly, 149 Mont Pelerin Society, 67, 93 Moral Consequences of Economic Growth, The (Friedman), 258 moral vacancy, 41 Morgan, Mary, 99 Morogoro, Tanzania, 121 Moyo, Dambisa, 258 Muirhead, Sam, 230, 231 MultiCapital Scorecard, 241 Murphy, David, 264 Murphy, Richard, 185 musical tastes, 110 Myriad Genetics, 196 N national basic income, 177 Native Americans, 115, 116, 282 natural capital, 7, 116, 269 Natural Economic Order, The (Gessel), 274 Nedbank, 216 negative externalities, 213 negative interest rates, 275–6 neoclassical economics, 134, 135 neoliberalism, 7, 62–3, 67–70, 81, 83, 84, 88, 93, 143, 170, 176 Nepal, 181, 199 Nestlé, 217 Netherlands, 211, 235, 224, 226, 238, 277 networks, 110–11, 117, 118, 123, 124–6, 174–6 neuroscience, 12–13 New Deal, 37 New Economics Foundation, 278, 283 New Year’s Day, 124 New York, United States, 9, 41, 55 Newlight Technologies, 224, 226, 293 Newton, Isaac, 13, 15–17, 32–3, 95, 97, 129, 131, 135–7, 142, 145, 162 Nicaragua, 196 Nigeria, 164 nitrogen, 49, 52, 212–13, 216, 218, 221, 226, 298 ‘no pain, no gain’, 163, 167, 173, 204, 209 Nobel Prize, 6–7, 43, 83, 101, 167 Norway, 281 nudging, 112, 113, 114, 123–6 O Obama, Barack, 41, 92 Oberlin, Ohio, 239, 240–41 Occupy movement, 40, 91 ocean acidification, 45, 46, 52, 155, 242, 298 Ohio, United States, 190, 239 Okun, Arthur, 37 onwards and upwards, 53 Open Building Institute, 196 Open Source Circular Economy (OSCE), 229–32 open systems, 74 open-source design, 158, 196–8, 265 open-source licensing, 204 Organisation for Economic Co-operation and Development (OECD), 38, 210, 255–6, 258 Origin of Species, The (Darwin), 14 Ormerod, Paul, 110, 111 Orr, David, 239 Ostrom, Elinor, 83, 84, 158, 160, 181–2 Ostry, Jonathan, 173 OSVehicle, 231 overseas development assistance (ODA), 198–200 ownership of wealth, 177–82 Oxfam, 9, 44 Oxford University, 1, 36 ozone layer, 9, 50, 115 P Pachamama, 54, 55 Pakistan, 124 Pareto, Vilfredo, 165–6, 175 Paris, France, 290 Park 20|20, Netherlands, 224, 226 Parker Brothers, 149 Patagonia, 56 patents, 195–6, 197, 204 patient capital, 235 Paypal, 192 Pearce, Joshua, 197, 203–4 peer-to-peer networks, 187, 192, 198, 203, 292 People’s QE, 184–5 Perseus, 244 Persia, 13 Peru, 2, 105–6 Phillips, Adam, 283 Phillips, William ‘Bill’, 64–6, 75, 142, 262 phosphorus, 49, 52, 212–13, 218, 298 Physiocrats, 73 Pickett, Kate, 171 pictures, 12–25 Piketty, Thomas, 169 Playfair, William, 16 Poincaré, Henri, 109, 127–8 Polanyi, Karl, 82, 272 political economy, 33–4, 42 political funding, 91–2, 171–2 political voice, 43, 45, 51–2, 77, 117 pollution, 29, 45, 52, 85, 143, 155, 206–17, 226, 238, 242, 254, 298 population, 5, 46, 57, 155, 199, 250, 252, 254 Portugal, 211 post-growth society, 250 poverty, 5, 9, 37, 41, 50, 88, 118, 148, 151 emotional, 283 and inequality, 164–5, 168–9, 178 and overseas development assistance (ODA), 198–200 and taxation, 277 power, 91–92 pre-analytic vision, 21–2 prescription medicines, 123 price-takers, 132 prices, 81, 118–23, 131, 160 Principles of Economics (Mankiw), 34 Principles of Economics (Marshall), 17, 98 Principles of Political Economy (Mill), 288 ProComposto, 226 Propaganda (Bernays), 107 public relations, 107, 281 public spending v. investment, 276 public–private patents, 195 Putnam, Robert, 76–7 Q quantitative easing (QE), 184–5 Quebec, 281 Quesnay, François, 16, 73 R Rabot, Ghent, 236 Rancière, Romain, 172 rating and review systems, 105 rational economic man, 94–103, 109, 111, 112, 126, 282 Reagan, Ronald, 67 reciprocity, 103–6, 117, 118, 123 reflexivity of markets, 144 reinforcing feedback loops, 138–41, 148, 250, 271 relative decoupling, 259 renewable energy biomass energy, 118, 221 and circular economy, 221, 224, 226, 235, 238–9, 274 and commons, 83, 85, 185, 187–8, 192, 203, 264 geothermal energy, 221 and green growth, 257, 260, 263, 264, 267 hydropower, 118, 260, 263 pricing, 118 solar energy, see solar energy wave energy, 221 wind energy, 75, 118, 196, 202–3, 221, 233, 239, 260, 263 rentier sector, 180, 183, 184 reregulation, 82, 87, 269 resource flows, 175 resource-intensive lifestyles, 46 Rethinking Economics, 289 Reynebeau, Guy, 237 Ricardo, David, 67, 68, 73, 89, 250 Richardson, Katherine, 53 Rifkin, Jeremy, 83, 264–5 Rise and Fall of the Great Powers, The (Kennedy), 279 risk, 112, 113–14 Robbins, Lionel, 34 Robinson, James, 86 Robinson, Joan, 142 robots, 191–5, 237, 258, 278 Rockefeller Foundation, 135 Rockford, Illinois, 179–80 Rockström, Johan, 48, 55 Roddick, Anita, 232–4 Rogoff, Kenneth, 271, 280 Roman Catholic Church, 15, 19 Rombo, Tanzania, 190 Rome, Ancient, 13, 48, 154 Romney, Mitt, 92 Roosevelt, Franklin Delano, 37 rooted membership, 190 Rostow, Walt, 248–50, 254, 257, 267–70, 284 Ruddick, Will, 185 rule of thumb, 113–14 Ruskin, John, 42, 223 Russia, 200 rust belt, 90, 239 S S curve, 251–6 Sainsbury’s, 56 Samuelson, Paul, 17–21, 24–5, 38, 62–7, 70, 74, 84, 91, 92, 93, 262, 290–91 Sandel, Michael, 41, 120–21 Sanergy, 226 sanitation, 5, 51, 59 Santa Fe, California, 213 Santinagar, West Bengal, 178 São Paolo, Brazil, 281 Sarkozy, Nicolas, 43 Saumweder, Philipp, 226 Scharmer, Otto, 115 Scholes, Myron, 100–101 Schumacher, Ernst Friedrich, 42, 142 Schumpeter, Joseph, 21 Schwartz, Shalom, 107–9 Schwarzenegger, Arnold, 163, 167, 204 ‘Science and Complexity’ (Weaver), 136 Scotland, 57 Seaman, David, 187 Seattle, Washington, 217 second machine age, 258 Second World War (1939–45), 18, 37, 70, 170 secular stagnation, 256 self-interest, 28, 68, 96–7, 99–100, 102–3 Selfish Society, The (Gerhardt), 283 Sen, Amartya, 43 Shakespeare, William, 61–3, 67, 93 shale gas, 264, 269 Shang Dynasty, 48 shareholders, 82, 88, 189, 191, 227, 234, 273, 292 sharing economy, 264 Sheraton Hotel, Boston, 3 Siegen, Germany, 290 Silicon Valley, 231 Simon, Julian, 70 Sinclair, Upton, 255 Sismondi, Jean, 42 slavery, 33, 77, 161 Slovenia, 177 Small Is Beautiful (Schumacher), 42 smart phones, 85 Smith, Adam, 33, 57, 67, 68, 73, 78–9, 81, 96–7, 103–4, 128, 133, 160, 181, 250 social capital, 76–7, 122, 125, 172 social contract, 120, 125 social foundation, 10, 11, 44, 45, 49, 51, 58, 77, 174, 200, 254, 295–6 social media, 83, 281 Social Progress Index, 280 social pyramid, 166 society, 76–7 solar energy, 59, 75, 111, 118, 187–8, 190 circular economy, 221, 222, 223, 224, 226–7, 239 commons, 203 zero-energy buildings, 217 zero-marginal-cost revolution, 84 Solow, Robert, 135, 150, 262–3 Soros, George, 144 South Africa, 56, 177, 214, 216 South Korea, 90, 168 South Sea Bubble (1720), 145 Soviet Union (1922–91), 37, 67, 161, 279 Spain, 211, 238, 256 Spirit Level, The (Wilkinson & Pickett), 171 Sraffa, Piero, 148 St Gallen, Switzerland, 186 Stages of Economic Growth, The (Rostow), 248–50, 254 stakeholder finance, 190 Standish, Russell, 147 state, 28, 33, 69–70, 78, 82, 160, 176, 180, 182–4, 188 and commons, 85, 93, 197, 237 and market, 84–6, 200, 281 partner state, 197, 237–9 and robots, 195 stationary state, 250 Steffen, Will, 46, 48 Sterman, John, 66, 143, 152–4 Steuart, James, 33 Stiglitz, Joseph, 43, 111, 196 stocks and flows, 138–41, 143, 144, 152 sub-prime mortgages, 141 Success to the Successful, 148, 149, 151, 166 Sugarscape, 150–51 Summers, Larry, 256 Sumner, Andy, 165 Sundrop Farms, 224–6 Sunstein, Cass, 112 supply and demand, 28, 132–6, 143, 253 supply chains, 10 Sweden, 6, 255, 275, 281 swishing, 264 Switzerland, 42, 66, 80, 131, 186–7, 275 T Tableau économique (Quesnay), 16 tabula rasa, 20, 25, 63, 291 takarangi, 54 Tanzania, 121, 190, 202 tar sands, 264, 269 taxation, 78, 111, 165, 170, 176, 177, 237–8, 276–9 annual wealth tax, 200 environment, 213–14, 215 global carbon tax, 201 global financial transactions tax, 201, 235 land-value tax, 73, 149, 180 non-renewable resources, 193, 237–8, 278–9 People’s QE, 185 tax relief v. tax justice, 23, 276–7 TED (Technology, Entertainment, Design), 202, 258 Tempest, The (Shakespeare), 61, 63, 93 Texas, United States, 120 Thailand, 90, 200 Thaler, Richard, 112 Thatcher, Margaret, 67, 69, 76 Theory of Moral Sentiments (Smith), 96 Thompson, Edward Palmer, 180 3D printing, 83–4, 192, 198, 231, 264 thriving-in-balance, 54–7, 62 tiered pricing, 213–14 Tigray, Ethiopia, 226 time banking, 186 Titmuss, Richard, 118–19 Toffler, Alvin, 12, 80 Togo, 231, 292 Torekes, 236–7 Torras, Mariano, 209 Torvalds, Linus, 231 trade, 62, 68–9, 70, 89–90 trade unions, 82, 176, 189 trademarks, 195, 204 Transatlantic Trade and Investment Partnership (TTIP), 92 transport, 59 trickle-down economics, 111, 170 Triodos, 235 Turkey, 200 Tversky, Amos, 111 Twain, Mark, 178–9 U Uganda, 118, 125 Ulanowicz, Robert, 175 Ultimatum Game, 105, 117 unemployment, 36, 37, 276, 277–9 United Kingdom Big Bang (1986), 87 blood donation, 118 carbon dioxide emissions, 260 free trade, 90 global material footprints, 211 money creation, 182 MONIAC (Monetary National Income Analogue Computer), 64–5, 75, 142, 262 New Economics Foundation, 278, 283 poverty, 165, 166 prescription medicines, 123 wages, 188 United Nations, 55, 198, 204, 255, 258, 279 G77 bloc, 55 Human Development Index, 9, 279 Sustainable Development Goals, 24, 45 United States American Economic Association meeting (2015), 3 blood donation, 118 carbon dioxide emissions, 260 Congress, 36 Council of Economic Advisers, 6, 37 Earning by Learning, 120 Econ 101 course, 8, 77 Exxon Valdez oil spill (1989), 9 Federal Reserve, 87, 145, 146, 271, 282 free trade, 90 Glass–Steagall Act (1933), 87 greenhouse gas emissions, 153 global material footprint, 211 gross national product (GNP), 36–40 inequality, 170, 171 land-value tax, 73, 149, 180 political funding, 91–2, 171 poverty, 165, 166 productivity and employment, 193 rust belt, 90, 239 Transatlantic Trade and Investment Partnership (TTIP), 92 wages, 188 universal basic income, 200 University of Berkeley, 116 University of Denver, 160 urbanisation, 58–9 utility, 35, 98, 133 V values, 6, 23, 34, 35, 42, 117, 118, 121, 123–6 altruism, 100, 104 anthropocentric, 115 extrinsic, 115 fluid, 28, 102, 106–9 and networks, 110–11, 117, 118, 123, 124–6 and nudging, 112, 113, 114, 123–6 and pricing, 81, 120–23 Veblen, Thorstein, 82, 109, 111, 142 Venice, 195 verbal framing, 23 Verhulst, Pierre, 252 Victor, Peter, 270 Viner, Jacob, 34 virtuous cycles, 138, 148 visual framing, 23 Vitruvian Man, 13–14 Volkswagen, 215–16 W Wacharia, John, 186 Wall Street, 149, 234, 273 Wallich, Henry, 282 Walras, Léon, 131, 132, 133–4, 137 Ward, Barbara, 53 Warr, Benjamin, 263 water, 5, 9, 45, 46, 51, 54, 59, 79, 213–14 wave energy, 221 Ways of Seeing (Berger), 12, 281 Wealth of Nations, The (Smith), 74, 78, 96, 104 wealth ownership, 177–82 Weaver, Warren, 135–6 weightless economy, 261–2 WEIRD (Western, educated, industrialised, rich, democratic), 103–5, 110, 112, 115, 117, 282 West Bengal, India, 124, 178 West, Darrell, 171–2 wetlands, 7 whale hunting, 106 Wiedmann, Tommy, 210 Wikipedia, 82, 223 Wilkinson, Richard, 171 win–win trade, 62, 68, 89 wind energy, 75, 118, 196, 202–3, 221, 233, 239, 260, 263 Wizard of Oz, The, 241 Woelab, 231, 293 Wolf, Martin, 183, 266 women’s rights, 33, 57, 107, 160, 201 and core economy, 69, 79–81 education, 57, 124, 178, 198 and land ownership, 178 see also gender equality workers’ rights, 88, 91, 269 World 3 model, 154–5 World Bank, 6, 41, 119, 164, 168, 171, 206, 255, 258 World No Tobacco Day, 124 World Trade Organization, 6, 89 worldview, 22, 54, 115 X xenophobia, 266, 277, 286 Xenophon, 4, 32, 56–7, 160 Y Yandle, Bruce, 208 Yang, Yuan, 1–3, 289–90 yin yang, 54 Yousafzai, Malala, 124 YouTube, 192 Yunnan, China, 56 Z Zambia, 10 Zanzibar, 9 Zara, 276 Zeitvorsoge, 186–7 zero environmental impact, 217–18, 238, 241 zero-hour contracts, 88 zero-humans-required production, 192 zero-interest loans, 183 zero-marginal-cost revolution, 84, 191, 264 zero-waste manufacturing, 227 Zinn, Howard, 77 PICTURE ACKNOWLEDGEMENTS Illustrations are reproduced by kind permission of: archive.org


pages: 501 words: 114,888

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives by Peter H. Diamandis, Steven Kotler

Ada Lovelace, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, blood diamonds, Burning Man, call centre, cashless society, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, crowdsourcing, cryptocurrency, Dean Kamen, delayed gratification, dematerialisation, digital twin, disruptive innovation, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, food miles, game design, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, indoor plumbing, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the telegraph, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kickstarter, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, mass immigration, megacity, meta analysis, meta-analysis, microbiome, mobile money, multiplanetary species, Narrative Science, natural language processing, Network effects, new economy, New Urbanism, Oculus Rift, out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, Satoshi Nakamoto, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, technoutopianism, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize

If solitary minds working in collectivist organizations—aka, business, culture, and society—produced converging exponential technologies—aka, the fastest innovation accelerant the world has yet seen—imagine what a hive-minded planet—aka, a kinder, gentler Borg—might be capable of creating. Put differently: How fast is our future if we’re all thinking together? And if you’ve come out the other side of all this thinking or feeling a little unsettled, there’s actually a technical term for this as well: loss aversion. One of our most potent cognitive biases, loss aversion is the evolutionarily programmed suspicion that if I take away whatever you have today, whatever I replace it with tomorrow will be a whole lot worse. This is why people stay stuck in ruts, it’s among the main reasons companies have such difficulty innovating, and why cultural change is so molasses slow. Yet, who knows, maybe our hive mind will get us past this particular blind spot, but, until then, that sense of converging exponentials meets five great migrations meets holy-shit vertigo that you might be feeling is perfectly natural.


pages: 621 words: 123,678

Financial Freedom: A Proven Path to All the Money You Will Ever Need by Grant Sabatier

"side hustle", 8-hour work day, Airbnb, anti-work, asset allocation, bitcoin, buy and hold, cryptocurrency, diversified portfolio, Donald Trump, financial independence, fixed income, follow your passion, full employment, Home mortgage interest deduction, index fund, loss aversion, Lyft, money market fund, mortgage debt, mortgage tax deduction, passive income, remote working, ride hailing / ride sharing, risk tolerance, Skype, stocks for the long run, stocks for the long term, TaskRabbit, the rule of 72, time value of money, uber lyft, Vanguard fund

I know people who are so afraid to invest that they just keep their money in a savings account making 1 percent or less, effectively losing money, since inflation rises 2 to 3 percent each year. Sure, you can lose money investing, but losing to inflation is a guaranteed loss! And if you invest intelligently, in most cases the upside is much greater than the downside over the long term. But we humans naturally fear losing more than we enjoy winning (a concept aptly known as loss aversion), which is why some people either don’t invest at all or get stuck on an emotional roller coaster—always chasing that next big gain or freaking out and making a rash decision on a decline. But investing isn’t gambling and there are ways to minimize the risks, as you’ll see in the section of this book on investing. The same happens when it comes to paying off debt. Some people can get so frustrated, scared, or embarrassed by carrying a large debt load that they don’t want to invest until they’ve paid it all down.

., 210–11 how to contribute to, 244–51 inflation and, 22, 25, 35, 39–42, 46, 114, 138, 213–14, 219, 264, 290 international, 216, 229–30, 235–36 job hacking and, 106, 156–58, 161–62, 168–69 lifestyle and, 57, 59–61, 259, 267, 278 living off them, 287–99, 312, 314 living richer life and, 312–17 long-term, 22, 213, 216, 230–32, 253–55, 260, 275–78, 286, 289 maxing out of, 211, 213, 239–51, 262 net worth and, 76–79, 82–83, 91, 108, 146, 223, 256, 268, 273, 276 and paying down debt, 84–86, 88, 92 rates of, 216–18, 259, 262, 302 real estate and, 2, 43, 119, 131, 146–47, 212–13, 237, 256, 260,262–86, 289, 300, 302 rebalancing of, 223–24, 236, 238, 261, 307 retiring and, 8–9, 21–28, 39–44, 46–51, 54–56, 60–61, 74–75, 179, 212, 215–22, 226, 229, 239, 242, 244–48, 251, 275, 287–92, 294–99 returns of, 22, 43–44, 46, 211, 213, 215, 222–23, 228, 239–40, 243, 245–46, 252, 254–55, 257–62, 264–66, 271–72, 274, 280, 285, 289–92, 294, 296, 300, 312–13 of Sabatier, 9–10, 30, 36, 95, 108, 114–18, 144, 181–83, 213–14,216–17, 220, 236, 256–57, 274–75, 285–86, 308 savings and, 95, 114–19, 143–44, 153–54, 213–17, 225, 239, 254, 258, 267–68, 273, 285, 287 selection of, 228–31, 254–55, 261–62 short-term, 213–16, 230, 260, 275, 286 side hustles and, 69–70, 95, 108, 113, 179–83, 187–88, 190, 192, 208, 216, 218, 220, 249–50, 259, 262, 264, 289–91, 298 taxes and, 46, 114, 211–15, 218, 224, 228, 232, 237, 239–55, 260, 262–68, 270–72, 275–77, 281–82, 285, 288, 291–300, 315 withdrawals from, 39–44, 46–49, 51, 54–56, 61, 66, 68–70, 239–45, 247–48, 251–54, 260, 262, 287–99 your number and, 37, 47, 49–51, 54–56, 66, 68–70, 72–74, 82–83, 91, 137, 179, 181, 210, 213, 216, 221, 259–60, 275–76, 287–89 see also under bonds; brokerage accounts; incomes; stocks, stock market iShares, 232, 234 Kelly, Brian (The Points Guy), 192 lawyers, law firms, 95, 144, 167, 193–94, 205, 224, 280, 313–14 website building for, 181–82, 194, 202 liabilities, 76–82, 91, 265 lifestyle, 28, 74, 158 expenses and, 17–18, 21, 57–63 housing and, 58–60, 62–63, 65–66 investing and, 57, 59–61, 259, 267, 278 of Sabatier, 9, 61–62 side hustles and, 111, 113, 191, 207–9 your number and, 15, 37, 59–60, 62 limited liability companies (LLCs), 179, 189–90, 309 load fees, 224 loans, 89, 151, 215 expenses and, 130–31, 147 investing and, 260, 263–64, 268–69, 271, 273, 279, 281, 285–86 net worth and, 77, 81–82 paying down, 84–85 preapproved, 281, 286 to students, 8, 55–56, 77, 81–82, 84–85, 130, 147, 313 Los Angeles, Calif., 148, 159, 271–72, 282 loss aversion, 88 Millennial Money, 11, 107, 146, 156, 164, 166, 168–69, 182 model portfolios, 229 Money Talk Cards, 305, 308 mopeds, 20, 109, 148, 182 mortgages, 52, 58, 66, 81–84, 131, 151 adjustable rate (ARMs), 268–70 fifteen–year, 269–70, 274 fixed rate (FRMs), 268–69, 274 investing and, 263–64, 266–77, 281, 283, 285–86 net worth and, 77, 81–82 preapproved, 281, 286 savings and, 146, 154 thirty-year, 269–70 mutual funds, 226, 229, 241, 243, 258 net worth, 13, 76–83, 122, 300, 312 calculation of, 76–77, 91 definition of, 82–83, 91 future-optimization framework and, 305–6, 308 investing and, 76–79, 82–83, 91, 108, 146, 223, 256, 268, 273, 276 negative, 82, 130–31 real estate and, 77–79, 83, 146 of Sabatier, 9–10, 82, 108, 114 savings and, 76, 79, 82, 146 side hustles and, 77, 108 and thinking about money before buying, 130–31, 137 your number and, 82–83, 91 New York City, 15, 150, 152, 166 housing and real estate in, 63–67, 271, 282, 315 1 percent rule, 281–82 passions, 2–3, 9, 33–35, 127 analysis of, 191–94, 209 in retirement, 297, 299 side hustles and, 11, 188, 191–96, 209 present value formula, 55–56 private mortgage insurance (PMI), 273–74 real estate: affordability of, 267, 270–75 and being prepared to walk away from deals, 285–86 buying and holding, 275, 286 case for, 264–66 criteria to follow for, 280–81, 285–86 finding properties and, 280–86 flipping of, 275–76, 286 with high rent appreciation potential, 281–82, 286 investing and, 2, 43, 119, 131, 146–47, 212–13, 237, 256, 260, 262–86, 289, 300, 302 net worth and, 77–79, 83, 146 refinancing of, 268, 270, 273 scaling in, 278–80, 286 test driving neighborhoods and, 284, 286 and thinking about money before buying, 127, 130–31, 133 see also homes, housing real estate agents, 182, 194, 283 real estate investment trusts (REITs), 237, 262 Realtors, 194, 279, 281–83, 286 recruiters, recruiting, 163, 165–66, 170, 173, 177, 192 retiring, retirement, 1, 8–12, 18–31, 34–36, 38–56, 308, 310 housing and, 45, 49, 52, 54, 60, 144 how much money actually needed for, 44–49 inflation and, 24–28, 40–42, 45–46, 94 investing and, 8–9, 21–28, 39–44, 46–51, 54–56, 60–61, 74–75, 179, 212, 215–22, 226, 229, 239, 242, 244–48, 251, 275, 287–92, 294–99 with less money at thirty than at sixty, 38–39, 47, 54 lifestyle and, 60–61, 74 living richer life and, 313, 315–16 and money for rest of your life, 42–44 and paying down debt, 84, 86 rewriting of, 28–31 of Sabatier, 8, 35, 45, 275 savings and, 8–9, 11, 20–22, 24–30, 38–40, 44–49, 51, 54–56, 60–61, 74, 94–96, 141, 144, 251 side hustles and, 43–44, 61, 69–70, 74, 179, 188, 192 time and, 19, 27, 45–47, 49n, 297–99 Trinity study and, 39–44 your number and, 36, 49–56, 68–70, 72–74 ride-sharing, 52, 109, 148 side hustles and, 183, 187, 190 risks, risk, 10, 16, 40, 49, 309 daily habits and, 89, 91–92 emotions and, 87–88 investing and, 14, 87, 106, 113–14, 211, 213, 215, 217–23, 229–30, 235, 237–38, 255–56, 260–61, 263–64, 269, 271, 279, 285, 289–91, 301, 317 side hustles and, 108, 112–13, 194, 202, 204 Robin, Vicki, 1–3, 32 robo-advisors, 212 Roth 401(k) accounts, 241, 243–45, 294, 298 Roth IRA accounts: conversion ladder for, 295, 298–99 investing in, 79, 95, 214, 218, 228, 241, 243–44, 247–49, 251, 258, 294–96, 298–99, 302 Rule of 72, 59, 75 Run the Trap, 191 S&P 500, 228, 232–38, 261 San Francisco, Calif., 64, 271, 282 savings, saving, 3, 5–11, 140–54 building wealth and, 93–94, 118 compounding and, 55, 59, 72, 94, 96, 143 daily habits and, 88–90 emotions and, 87–88 enterprise mindset and, 103, 107, 113–17 expenses and, 42–43, 74, 96–101, 120–21, 126–28, 130, 132–33, 137–38,140–44, 153–54 financial freedom levels and, 16–17 food and, 142–43, 152–54 future-optimization framework and, 301, 303, 305–6 housing and, 63, 67, 141–47, 154 inflation and, 8–9, 24–28 investing and, 95, 114–19, 143–44, 153–54, 213–17, 225, 239, 254, 258, 267–68, 273, 285, 287 job hacking and, 107, 159–60, 163, 170, 177 lifestyle and, 57–58, 60–61 living richer life and, 312–17 net worth and, 76, 79, 82, 146 rates of, 11, 13, 20–21, 24, 26–28, 33, 89, 94–101, 108, 114–19, 141,143, 213, 216–18, 256–58, 260, 300, 302–3, 305–6, 312–15, 317 retiring and, 8–9, 11, 20–22, 24–30, 38–40, 44–49, 51, 54–56, 60–61, 74, 94–96, 141, 144, 251 of Sabatier, 5–7, 9–11, 30, 45, 63, 95, 138, 143–44, 148, 151–53, 216–17, 256–57, 300, 302, 311–12 side hustles and, 113, 179 time and, 32–33, 94, 96–101, 118 transportation and, 141–43, 147–52, 154 your number and, 36–37, 39, 51, 54–56, 59, 68, 70–75, 94–95, 97–101, 118, 137, 141 see also health savings accounts saying no, 127, 208, 303–5, 310, 312 Charles Schwab, 232–33, 252 search engine optimization (SEO) projects, 175, 182 sequence-of-returns risk, 290–91 short sales, 283, 286 side hustles, 11, 14, 90, 153, 179–209, 300, 317 benefits of, 109–10, 185, 189 competitive analysis for, 200–203, 205, 209 enterprise mindset and, 104, 108–13, 119, 180 evaluation framework for, 190–209 in evenings, 186 figuring out what to charge for, 201–4, 209 future-optimization framework and, 301–3, 306 getting your first sale and, 204–6 hiring others for, 109, 111–13, 119, 206–7 in in-between moments, 187–89 incomes and, see under incomes investing and, 69–70, 95, 108, 113, 179–83, 187–88, 190, 192, 208, 216, 218, 220, 249–50, 259, 262, 264, 289–91, 298 job hacking and, 156, 160, 175 and knowing when to scale, 206–9 LLCs and, 179, 189–90 in mornings, 185 net worth and, 77, 108 retiring and, 43–44, 61, 69–70, 74, 179, 188, 192 of Sabatier, 9, 20, 58, 95, 104, 108–9, 175–76, 181–83, 185–86, 188, 194–95, 202–3, 205, 207–8 skills and, 109, 119, 175, 190–97, 201–2, 209 supply and demand for, 179, 182, 189, 194, 197–204, 206, 209 taxes and, 189–90, 249 time and, 108, 111, 180–87, 190, 199–200, 202–3, 207–9, 303 transportation and, 148, 187, 189, 192–93, 196, 208 on weekends, 186 and working for someone else vs. for yourself, 183–84, 207–9 your number and, 69–70, 179–81, 189, 209 your story in, 204–5 simplified employee pension individual retirement accounts (SEP IRAs), 79, 218, 228, 241, 243, 249–51 skills, 10, 51, 104, 133 analysis of, 191–94, 209 job hacking and, 14, 105, 156, 159, 164–66, 169, 174–78 learning new ones, 195–96, 209 retiring and, 34, 44 side hustles and, 109, 119, 175, 190–97, 201–2, 209 Social Security, 8, 26, 45n, 249, 269 expenses and, 53, 128, 141–42 Solo 401(k) accounts, 241, 243, 249–50 stocks, stock market, 160 buying individual, 254–57 compounding and, 22, 72 dividends paid by, 22, 25, 46, 111 emotions and, 86–87 international, 216, 229–30, 235–36 investing in, 2, 9, 17, 24–26, 34, 39–42, 46–47, 84, 86–87, 104, 114, 119, 162, 211–26, 228–38, 241–42, 244, 252–58, 260–62, 264–65, 273–79, 285, 287, 289–91, 297 past performance of, 222–23 and paying down debt, 84–86 retiring and, 39–44, 46–49 selection of, 228–29, 230–31, 255, 261 your number and, 36, 72 target date funds, 228–29, 238 taxes, 59, 64, 77, 83–84, 88, 102, 143 deductions and, 84, 128, 189–90, 240–42, 245–52, 254, 266–68, 276, 294,296–98 enterprise mindset and, 103, 114, 118 future-optimization framework and, 307–9 inflation and, 25, 45 investing and, 46, 114, 211–15, 218, 224, 228, 232, 235, 237, 239–55, 260, 262–68, 270–72, 275–77, 281–82, 285, 288, 291–99, 300, 315 job hacking and, 157–58 real hourly income rates and, 122–25, 129 retiring and, 19, 27, 45–47, 49n, 297–99 of Sabatier, 7–8 savings rates and, 95–96, 118 side hustles and, 189–90, 249 and thinking about money before buying, 120, 127–30 your number and, 52–53, 68–69 1031 exchanges, 264–65, 275 three fund investments, 235–36 time, 2, 10, 63, 153 compounding and, 22, 33, 305 daily habits and, 90–91 enterprise mindset and, 103, 105–6, 108, 111, 118–19, 300 expenses and, 32, 75, 129–30, 133–39 future-optimization framework and, 301, 303–5, 307–10 investing and, 33–34, 118, 133, 210, 212, 214–15, 224, 239, 283, 308 job hacking and, 105–6, 155–56, 160–64, 166–68, 170–73, 177–78 living richer life and, 312, 314–17 real hourly income rates and, 121–25, 129, 134–35, 139, 307 relationship between money and, 19, 32–35, 106, 111, 113, 121, 129, 133, 184, 188, 207–10, 303–4, 307–8, 310 retirement and, 19, 27, 45–47, 49n, 297–99 savings and, 32–33, 94, 96–101, 118 side hustles and, 108, 111, 180–87, 190, 199–200, 202–3, 207–9, 303 transportation and, 32–33, 148 Top Five Regrets of the Dying, The (Ware), 29–30 total stock market funds, see index funds trading, 132–33, 139 transportation, 32–35, 64, 91, 213, 297, 299, 313 expenses and, 25, 52, 54, 58–59, 61–62, 65–66, 75, 127, 140–43, 147–52, 154 housing and, 65–66, 145 job hacking and, 156–60 lifestyle and, 58–59, 61–62 real hourly income rates and, 122–25, 139 of Sabatier, 148, 151–52 savings and, 141–43, 147–52, 154 side hustles and, 148, 187, 189, 192–93, 196, 208 time and, 32–33, 148 travel-hacking and, 148–52, 154 your number and, 52, 54, 59 Trinity study, 39–44 vacations, 6, 9, 17, 28, 34, 52, 91, 105, 156, 187, 192, 278 expenses and, 130–31, 147 valuables, 52, 77–79, 83 value investing, 255 Vanguard, 212, 215, 234, 252 500 Index Fund Admiral Shares (VFIAX), 232–33 500 Index Fund Investor Shares (VFINX), 228, 232–33 Total Stock Market ETF (VTI), 222, 226, 232 Total Stock Market Index Fund (VTSAX), 228, 232–33, 257 Volkswagen (VW) campers, 8, 109, 182 Wang, Jim, 192 Ware, Bronnie, 29–30 wealth, 2–3, 16, 28, 38, 230 building of, 6, 11–12, 76, 86, 88, 93–94, 103, 118 daily habits and, 88–90 emotions and, 86, 88 job hacking and, 155, 162 net worth and, 76, 82 website building, 20, 58, 104, 175, 194–95, 201–3, 205, 207 for law firms, 181–82, 194, 202 We Need Diverse Books, 314–15 Your Money or Your Life (Robin and Dominguez), 2–3, 32 your number, 77, 307 breaking it down into smaller goals, 70–76 calculation and recalculation of, 13, 15, 44, 49–57, 66–69, 72, 75–76,82–83, 288–89, 300 definition of, 13, 82, 91 expenses and, 13, 36–38, 50–57, 59–60, 62–66, 68–70, 75, 135, 137, 276 housing and, 52, 54, 66–67 incomes and, 36–39, 68–70, 74, 82–83, 91, 169, 180, 189 investing and, 37, 47, 49–51, 54–56, 66, 68–70, 72–74, 82–83, 91, 137, 179, 181, 210, 213, 216, 221, 259–60, 275–76, 287–89 job hacking and, 155, 169, 174 lifestyle and, 15, 37, 59–60, 62 living richer life and, 312, 316 net worth and, 82–83, 91 of Sabatier, 12–13, 36 savings and, 36–37, 39, 51, 54–56, 59, 68, 70–75, 94–95, 97–101, 118, 137, 141 side hustles and, 69–70, 179–81, 189, 208 ABCDEFGHIJKLMNOPQRSTUVWXYZ ABOUT THE AUTHOR Grant Sabatier, called "The Millennial Millionaire" by CNBC, is the Founder of MillennialMoney.com, which has reached over 10 million readers.


pages: 147 words: 45,890

Aftershock: The Next Economy and America's Future by Robert B. Reich

Berlin Wall, business cycle, declining real wages, delayed gratification, Doha Development Round, endowment effect, full employment, George Akerlof, Home mortgage interest deduction, Hyman Minsky, illegal immigration, income inequality, invisible hand, job automation, labor-force participation, Long Term Capital Management, loss aversion, mortgage debt, new economy, offshore financial centre, Ralph Nader, Ronald Reagan, school vouchers, sovereign wealth fund, Thorstein Veblen, too big to fail, World Values Survey

Millar Publishing, 1790), pp. 261–63. 9 Almost 10 percent fewer people were killed: See National Highway Traffic Safety Administration Fatality Analysis Reporting System Encyclopedia (http://www-fars.nhtsa.dot.gov/Main/index.aspx). 10 deaths and serious injuries dropped: See U.S. Bureau of Labor Statistics, economic news release: “Workplace Injury and Illness Summary,” October 29, 2009. 4. THE PAIN OF ECONOMIC LOSS 1 Princeton psychologist Daniel Kahneman: See D. Kahneman, J. L. Knetch, and R. H. Thaler, “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias,” Journal of Economic Perspectives, 5, no. 1 (Winter 1991): 193–206. 2 Societies whose living standards drop: Ibid. 3 Behavioral economist Christopher Ruhm: See C. J. Ruhm, Are Recessions Good for Your Health?, National Bureau of Economic Research, March 2006. 4 The stock market crash of 1929: See Leonardo Tondo and Ross J. Baldessarini, Suicides: Causes and Clinical Management, Medscape Medical News (http://cme.medscape.com/viewarticle/413195_2). 5 “the crisis quality of a serious illness”: Robert S.


pages: 807 words: 154,435

Radical Uncertainty: Decision-Making for an Unknowable Future by Mervyn King, John Kay

"Robert Solow", Airbus A320, Albert Einstein, Albert Michelson, algorithmic trading, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, autonomous vehicles, availability heuristic, banking crisis, Barry Marshall: ulcers, battle of ideas, Benoit Mandelbrot, bitcoin, Black Swan, Bonfire of the Vanities, Brownian motion, business cycle, business process, capital asset pricing model, central bank independence, collapse of Lehman Brothers, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, Donald Trump, easy for humans, difficult for computers, Edmond Halley, Edward Lloyd's coffeehouse, Edward Thorp, Elon Musk, Ethereum, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, fear of failure, feminist movement, financial deregulation, George Akerlof, germ theory of disease, Hans Rosling, Ignaz Semmelweis: hand washing, income per capita, incomplete markets, inflation targeting, information asymmetry, invention of the wheel, invisible hand, Jeff Bezos, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, John von Neumann, Kenneth Arrow, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, market bubble, market fundamentalism, Moneyball by Michael Lewis explains big data, Nash equilibrium, Nate Silver, new economy, Nick Leeson, Northern Rock, oil shock, Paul Samuelson, peak oil, Peter Thiel, Philip Mirowski, Pierre-Simon Laplace, popular electronics, price mechanism, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, railway mania, RAND corporation, rent-seeking, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Coase, sealed-bid auction, shareholder value, Silicon Valley, Simon Kuznets, Socratic dialogue, South Sea Bubble, spectrum auction, Steve Ballmer, Steve Jobs, Steve Wozniak, Tacoma Narrows Bridge, Thales and the olive presses, Thales of Miletus, The Chicago School, the map is not the territory, The Market for Lemons, The Nature of the Firm, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Thomas Malthus, Toyota Production System, transaction costs, ultimatum game, urban planning, value at risk, World Values Survey, Yom Kippur War, zero-sum game

Many more economists studied what became known as ‘behavioural economics’, which offers a list of widely observed ‘biases’ in people’s behaviour. These studies claim that we suffer from optimism and overconfidence, and we overestimate the likelihood of favourable outcomes. We are guilty of anchoring: attaching too much weight to the limited information we hold when we start to analyse a problem. We are victims of loss aversion: treating losses with a concern not given to equivalent gains. And so on. While Allais, Ellsberg and Simon regarded their observations as a rebuttal of the view of decision-making under uncertainty put forward by Friedman and Savage, the approach pioneered by Kahneman and Tversky adopted a markedly different stance. The subject of their critique is the decision-maker, not the model of decision-making.

In a radically uncertain world we do not know whether such actions are or are not optimal – the life insurance salesman might on this occasion be proposing an irresistible offer, or one of our colleagues might be desperate to feed his gambling habit or her drug addiction. Uncertainty is radical everywhere. And the irrational ‘biases’ identified by behavioural economists as being ‘in our nature’ are not, in any ordinary meaning of the term, irrational. They are traits that are advantageous outside the ‘small worlds’ of the casino and the psychology laboratory. And they have evolutionary origins. Loss aversion Evolution has fitted humans to deal with the many kinds of radical uncertainty encountered in large worlds. Different attitudes to uncertainty influence the chances of survival of individuals and groups. In some environments, such as business and sport, to play safe is to relinquish the possibility of success. It may even be an advantage to overestimate one’s chances of success. In other environments, it may make sense to avoid risks.


pages: 226 words: 59,080

Economics Rules: The Rights and Wrongs of the Dismal Science by Dani Rodrik

airline deregulation, Albert Einstein, bank run, barriers to entry, Bretton Woods, business cycle, butterfly effect, capital controls, Carmen Reinhart, central bank independence, collective bargaining, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, distributed generation, Donald Davies, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, Fellow of the Royal Society, financial deregulation, financial innovation, floating exchange rates, fudge factor, full employment, George Akerlof, Gini coefficient, Growth in a Time of Debt, income inequality, inflation targeting, informal economy, information asymmetry, invisible hand, Jean Tirole, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, labor-force participation, liquidity trap, loss aversion, low skilled workers, market design, market fundamentalism, minimum wage unemployment, oil shock, open economy, Pareto efficiency, Paul Samuelson, price stability, prisoner's dilemma, profit maximization, quantitative easing, randomized controlled trial, rent control, rent-seeking, Richard Thaler, risk/return, Robert Shiller, Robert Shiller, school vouchers, South Sea Bubble, spectrum auction, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, trade liberalization, trade route, ultimatum game, University of East Anglia, unorthodox policies, Vilfredo Pareto, Washington Consensus, white flight

The postulate always had its critics from within economics, such as Herbert Simon, who argued for a limited form of rationality (called “bounded rationality”), and Richard Nelson, who proposed that firms move by trial and error rather than by optimization—not to mention Adam Smith himself, who may have been the first behavioral economist.11 But it was the work of psychologist Daniel Kahneman and his coauthors that had the greatest impact on mainstream economics.12 This contribution was recognized by a Nobel memorial prize in economics given to Kahneman in 2002, the first time that the prize was awarded to a noneconomist.# Kahneman and his colleagues’ experiments cataloged a long list of behavioral regularities that violated rationality, as the concept is used in economics. People value an object more when giving it up than they do when acquiring it (loss aversion), overgeneralize from small amounts of data (overconfidence), discount evidence that contradicts their beliefs (confirmation bias), yield to short-term temptations that they realize are bad for them (weak self-control), value fairness and reciprocity (bounded selfishness), and so on. These types of behavior have important implications in many areas of economics. For example, the efficient-markets hypothesis in finance (see Chapter 5) relies on investors having unbiased expectations.


pages: 179 words: 59,704

Meet the Frugalwoods: Achieving Financial Independence Through Simple Living by Elizabeth Willard Thames

"side hustle", Airbnb, asset allocation, barriers to entry, basic income, buy and hold, carbon footprint, delayed gratification, dumpster diving, East Village, financial independence, hedonic treadmill, IKEA effect, index fund, indoor plumbing, loss aversion, McMansion, mortgage debt, passive income, payday loans, risk tolerance, Stanford marshmallow experiment, universal basic income, working poor

Plus, all of our savings were stacked one on top of the other, which is how you create an extremely frugal lifestyle. We weren’t saving just $470 on seltzer per year, we were saving $470 plus the $3,456 on yoga plus $1,008 on haircuts . . . and on and on and on until we were saving thousands upon thousands of dollars every single year. Forever. There’s a theory in behavioral economics related to loss aversion positing that once we acclimate to a certain level of luxury or ownership in our lives—be it seltzer or expensive yoga classes—we find it nearly impossible to then live without this luxury. Giving these things up feels like deprivation because we’ve acclimated ourselves to their presence in our lives. Knowing this, and knowing that we wanted to sustain a lower cost of living forever, Nate and I put a lot of time and effort into devising our frugal workarounds.


pages: 187 words: 62,861

The Penguin and the Leviathan: How Cooperation Triumphs Over Self-Interest by Yochai Benkler

business process, California gold rush, citizen journalism, Daniel Kahneman / Amos Tversky, East Village, Everything should be made as simple as possible, experimental economics, experimental subject, framing effect, informal economy, invisible hand, jimmy wales, job satisfaction, Joseph Schumpeter, Kenneth Arrow, knowledge economy, laissez-faire capitalism, loss aversion, Murray Gell-Mann, Nicholas Carr, peer-to-peer, prediction markets, Richard Stallman, Scientific racism, Silicon Valley, Steven Pinker, telemarketer, Toyota Production System, twin studies, ultimatum game, Washington Consensus, zero-sum game, Zipcar

Even economists have grudgingly admitted this; behavioral economics describes it as the framing effect. Amos Tversky and Daniel Kahneman, the fathers of behavioral economics, explain that people will make different decisions depending on how a situation is presented. For example, when making a bet, people will risk different amounts depending on whether the bet is described as risking a loss or aiming for a gain (behavioral economists have found that people display what is often called “loss aversion”: they will reject bets framed as potential losses, but accept that same bet when it is framed as potential gains). Countless experiments have demonstrated equally powerful framing effects in a wide range of contexts. While “framing” is popularly known today through these kinds of “irrationalities,” the situation and its impact on what we want and what we can or should do is a long-standing component of social psychology.


pages: 256 words: 60,620

Think Twice: Harnessing the Power of Counterintuition by Michael J. Mauboussin

affirmative action, asset allocation, Atul Gawande, availability heuristic, Benoit Mandelbrot, Bernie Madoff, Black Swan, butter production in bangladesh, Cass Sunstein, choice architecture, Clayton Christensen, cognitive dissonance, collateralized debt obligation, Daniel Kahneman / Amos Tversky, deliberate practice, disruptive innovation, Edward Thorp, experimental economics, financial innovation, framing effect, fundamental attribution error, Geoffrey West, Santa Fe Institute, George Akerlof, hindsight bias, hiring and firing, information asymmetry, libertarian paternalism, Long Term Capital Management, loose coupling, loss aversion, mandelbrot fractal, Menlo Park, meta analysis, meta-analysis, money market fund, Murray Gell-Mann, Netflix Prize, pattern recognition, Philip Mirowski, placebo effect, Ponzi scheme, prediction markets, presumed consent, Richard Thaler, Robert Shiller, Robert Shiller, statistical model, Steven Pinker, The Wisdom of Crowds, ultimatum game

Likewise, skillful people who have suffered a period of poor outcomes are often a good bet, since luck evens out over time.11 Picking the Main Mistakes We Professionals Make The primary audience for this book is investors and businesspeople, although the concepts are relevant for other professionals as well. This book is neither a survey of common mistakes nor an exposition of one big theme. For instance, most books focus either on the components of prospect theory (loss aversion, overconfidence, framing effects, anchoring, and the confirmation bias) or they dwell on one important idea.12 Rather, I have tried to select the concepts that I have found most useful, based on my experience in the investment industry and through my study of psychology and science. Each of the following chapters discusses a common decision mistake, illustrates why that mistake is consequential, and offers some thoughts on how to manage the problem.


pages: 252 words: 70,424

The Self-Made Billionaire Effect: How Extreme Producers Create Massive Value by John Sviokla, Mitch Cohen

business cycle, Cass Sunstein, Colonization of Mars, corporate raider, Daniel Kahneman / Amos Tversky, Elon Musk, Frederick Winslow Taylor, game design, global supply chain, James Dyson, Jeff Bezos, John Harrison: Longitude, Jony Ive, loss aversion, Mark Zuckerberg, market design, old-boy network, paper trading, RAND corporation, randomized controlled trial, Richard Thaler, risk tolerance, self-driving car, Silicon Valley, smart meter, Steve Ballmer, Steve Jobs, Steve Wozniak, Tony Hsieh, Toyota Production System, young professional

The Nobel Prize winner Daniel Kahneman and his research partner Amos Tversky first proposed the subjective nature of risk in a 1979 paper in which they describe a series of experiments they conducted to come up with their famous Prospect Theory, a model for human decision making. At its core, Prospect Theory argues that individual perceptions of risk can be influenced by how an opportunity is framed, the context in which it is presented, personal experience, and other factors. Among other ideas, Prospect Theory first introduced the world to the concept of loss aversion, the now-accepted notion that people are more afraid of losing what they have than they are eager to gain something new.5 For most people, the subjective nature of risk causes them to overestimate the risk of failure and underestimate the risk of missing out on a gain. Producers, in contrast, have the ability to turn that tendency on its head. People like Yan Cheung are willing to risk failure.


pages: 280 words: 75,820

Rapt: Attention and the Focused Life by Winifred Gallagher

Albert Einstein, Atul Gawande, Build a better mousetrap, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, epigenetics, Frank Gehry, fundamental attribution error, Isaac Newton, knowledge worker, longitudinal study, loss aversion, Mahatma Gandhi, McMansion, music of the spheres, Nelson Mandela, Ralph Waldo Emerson, Richard Feynman, Rodney Brooks, Ronald Reagan, Silicon Valley, social intelligence, Walter Mischel, zero-sum game

“That’s why following every detail of your financial situation is a problem, unless you get pleasure from it,” says Kahneman. “If you focus too much on each issue separately, considering each loss and gain in isolation, you make mistakes.” If you’re pondering a choice that involves risk, you might focus too much on the threat of possible loss, thereby obscuring an even likelier potential benefit. Where this common scenario is concerned, research shows that we aren’t so much risk-averse as loss-averse, in that we’re generally much more sensitive to what we might have to give up than to what we might gain. Let’s say that you’re invited to toss a coin. The terms are that if it’s tails, you lose twenty dollars; heads, you win a certain amount. If you’re then asked how much your winnings would have to be to make you take the chance, you’re likely to suggest between forty and fifty dollars. In other words, because we put more weight on the loss than the reward, before taking a 50/50 gamble, most people want to know that they’d win at least twice as much as they’d forfeit.


pages: 277 words: 79,360

The Happiness Curve: Why Life Gets Better After 50 by Jonathan Rauch

endowment effect, experimental subject, Google bus, happiness index / gross national happiness, hedonic treadmill, income per capita, job satisfaction, longitudinal study, loss aversion, Richard Thaler, science of happiness, Silicon Valley, Skype, Steve Jobs, Steve Wozniak, upwardly mobile, World Values Survey, zero-sum game

Quotations are from page 143 and various locations in chapter 5. Also foundational is the work of Martin E. P. Seligman, whose 2002 book Authentic Happiness: Using the New Positive Psychology to Realize Your Potential for Lasting Fulfillment (Atria Books) provides much insight, as well as the useful happiness formula which I adapted. The 1990 experiment by Kahneman, Knetsch, and Thaler on endowment bias is reported in “Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias,” published in the Journal of Economic Perspectives 5:1 (1991). Tali Sharot and various collaborators have published extensively on optimism bias. Sharot lays out her findings concisely and readably in her ebook The Science of Optimism. Other Sharot work I consulted includes “The Optimism Bias” in Current Biology 21:23 (2011); “Neural Mechanisms Mediating Optimism Bias,” coauthored with Alison Riccardi, Candace Raio, and Elizabeth Phelps, in Nature 450 (2007); “Selectively Altering Belief Formation in the Human Brain,” coauthored with Ryota Kanai, David Marston, Christoph W.


pages: 309 words: 81,975