fudge factor

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The (Honest) Truth About Dishonesty: How We Lie to Everyone, Especially Ourselves by Dan Ariely

accounting loophole / creative accounting, Albert Einstein, behavioural economics, Bernie Madoff, Broken windows theory, cashless society, clean water, cognitive dissonance, cognitive load, Credit Default Swap, Donald Trump, fake it until you make it, financial engineering, fudge factor, John Perry Barlow, new economy, operational security, Richard Feynman, Schrödinger's Cat, Shai Danziger, shareholder value, social contagion, Steve Jobs, Tragedy of the Commons, Walter Mischel

First, we need to recognize that dishonesty is largely driven by a person’s fudge factor and not by the SMORC. The fudge factor suggests that if we want to take a bite out of crime, we need to find a way to change the way in which we are able to rationalize our actions. When our ability to rationalize our selfish desires increases, so does our fudge factor, making us more comfortable with our own misbehavior and cheating. The other side is true as well; when our ability to rationalize our actions is reduced, our fudge factor shrinks, making us less comfortable with misbehaving and cheating. When you consider the range of undesirable behaviors in the world from this stand-point—from banking practices to backdating stock options, from defaulting on loans and mortgages to cheating on taxes—there’s a lot more to honesty and dishonesty than rational calculations.

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This is where our amazing cognitive flexibility comes into play. Thanks to this human skill, as long as we cheat by only a little bit, we can benefit from cheating and still view ourselves as marvelous human beings. This balancing act is the process of rationalization, and it is the basis of what we’ll call the “fudge factor theory.” To give you a better understanding of the fudge factor theory, think of the last time you calculated your tax return. How did you make peace with the ambiguous and unclear decisions you had to make? Would it be legitimate to write off a portion of your car repair as a business expense? If so, what amount would you feel comfortable with?

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Although most people haven’t consciously figured out (much less announced) their acceptable rate of lying like this young man, this overall approach seems to be quite accurate; each of us has a limit to how much we can cheat before it becomes absolutely “sinful.” Trying to figure out the inner workings of the fudge factor—the delicate balance between the contradictory desires to maintain a positive self-image and to benefit from cheating—is what we are going to turn our attention to next. CHAPTER 2 Fun with the Fudge Factor Here’s a little joke for you: Eight-year-old Jimmy comes home from school with a note from his teacher that says, “Jimmy stole a pencil from the student sitting next to him.” Jimmy’s father is furious.

The Irrational Bundle by Dan Ariely

accounting loophole / creative accounting, air freight, Albert Einstein, Alvin Roth, An Inconvenient Truth, assortative mating, banking crisis, Bear Stearns, behavioural economics, Bernie Madoff, Black Swan, Broken windows theory, Burning Man, business process, cashless society, Cass Sunstein, clean water, cognitive dissonance, cognitive load, compensation consultant, computer vision, Cornelius Vanderbilt, corporate governance, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, delayed gratification, Demis Hassabis, Donald Trump, end world poverty, endowment effect, Exxon Valdez, fake it until you make it, financial engineering, first-price auction, Ford Model T, Frederick Winslow Taylor, fudge factor, Garrett Hardin, George Akerlof, Gordon Gekko, greed is good, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, John Perry Barlow, Kenneth Arrow, knowledge economy, knowledge worker, lake wobegon effect, late fees, loss aversion, Murray Gell-Mann, name-letter effect, new economy, operational security, Pepsi Challenge, Peter Singer: altruism, placebo effect, price anchoring, Richard Feynman, Richard Thaler, Saturday Night Live, Schrödinger's Cat, search costs, second-price auction, Shai Danziger, shareholder value, Silicon Valley, Skinner box, Skype, social contagion, software as a service, Steve Jobs, subprime mortgage crisis, sunk-cost fallacy, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, ultimatum game, Upton Sinclair, Walter Mischel, young professional

First, we need to recognize that dishonesty is largely driven by a person’s fudge factor and not by the SMORC. The fudge factor suggests that if we want to take a bite out of crime, we need to find a way to change the way in which we are able to rationalize our actions. When our ability to rationalize our selfish desires increases, so does our fudge factor, making us more comfortable with our own misbehavior and cheating. The other side is true as well; when our ability to rationalize our actions is reduced, our fudge factor shrinks, making us less comfortable with misbehaving and cheating. When you consider the range of undesirable behaviors in the world from this standpoint—from banking practices to backdating stock options, from defaulting on loans and mortgages to cheating on taxes—there’s a lot more to honesty and dishonesty than rational calculations.

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This is where our amazing cognitive flexibility comes into play. Thanks to this human skill, as long as we cheat by only a little bit, we can benefit from cheating and still view ourselves as marvelous human beings. This balancing act is the process of rationalization, and it is the basis of what we’ll call the “fudge factor theory.” To give you a better understanding of the fudge factor theory, think of the last time you calculated your tax return. How did you make peace with the ambiguous and unclear decisions you had to make? Would it be legitimate to write off a portion of your car repair as a business expense? If so, what amount would you feel comfortable with?

…

Although most people haven’t consciously figured out (much less announced) their acceptable rate of lying like this young man, this overall approach seems to be quite accurate; each of us has a limit to how much we can cheat before it becomes absolutely “sinful.” Trying to figure out the inner workings of the fudge factor—the delicate balance between the contradictory desires to maintain a positive self-image and to benefit from cheating—is what we are going to turn our attention to next. CHAPTER 2 Fun with the Fudge Factor Here’s a little joke for you: Eight-year-old Jimmy comes home from school with a note from his teacher that says, “Jimmy stole a pencil from the student sitting next to him.” Jimmy’s father is furious.

Elliptic Tales: Curves, Counting, and Number Theory by Avner Ash, Robert Gross

Andrew Wiles, fudge factor, Georg Cantor, P = NP

This agrees with what we found by direct calculation. 204 CHAPTER 13 For each p, we call the function ζC,p (T) the local zeta-function of C. Now we can define the Hasse–Weil zeta-function of C, denoted Z(C, s), except for a certain fudge factor we will explain but not define. You simply substitute T = p−s in ζC,p (T) and then multiply all these local factors together: Z(C, s) = ζC,p (p−s ) × fudge. p good Here is a rough idea of where the fudge factor comes from. We call a prime p “good” for C if C modulo p is nonsingular, which means C(Fac p ) has no ac singular point on it, where Fp is as usual an algebraic closure of Fp . We call p “bad” if it is not good.

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For a given curve C, there are only a finite number of bad primes. The factor called “fudge” is a product of certain functions of p−s for the bad primes p. These functions are defined in a complicated way we can’t go into here. (However, when C is an elliptic curve, we will be able to tell you how to define the fudge factors.) The fudge factors are hard to define, but they are essential to flesh out our understanding of C modulo p for all primes p. In particular, they are necessary to make a certain functional equation discussed below work out correctly. Let’s continue our example with C = P1 , a projective line. To get the Hasse–Weil zeta-function of P1 , we have to substitute T = p−s and then multiply all these local factors together: Z(P1 , s) = (1 − p−s )−1 (1 − pp−s )−1 (13.1) p There are no bad primes in this example, because P1 modulo p is nonsingular for all p.

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The numerator of the Hasse–Weil zetafunction of C is the product over good primes of polynomials of degree 2g evaluated at p−s , times a fudge factor from the bad primes. The reciprocal of this numerator is called the L-function of C, and is written L(C, s). In the case of a curve, we have the formula L(C, s) = fudge × p good 1 , fp (p−s ) where fp (T) is some polynomial of degree 2g. The theory tells us that the constant term of fp is always equal to 1, and various theorems give us bounds on the absolute values of the coefficients of fp . So we can write this as L(C, s) = fudge × 1 p good 1 + c1,p p−s + c2,p p−2s + · · · + c2g,p p−2gs . (Remember that although we don’t say here what the fudge factor is, it is known and can be determined.)

Principles of Corporate Finance by Richard A. Brealey, Stewart C. Myers, Franklin Allen

3Com Palm IPO, accelerated depreciation, accounting loophole / creative accounting, Airbus A320, Alan Greenspan, AOL-Time Warner, Asian financial crisis, asset allocation, asset-backed security, banking crisis, Bear Stearns, Bernie Madoff, big-box store, Black Monday: stock market crash in 1987, Black-Scholes formula, Boeing 747, book value, break the buck, Brownian motion, business cycle, buy and hold, buy low sell high, California energy crisis, capital asset pricing model, capital controls, Carl Icahn, Carmen Reinhart, carried interest, collateralized debt obligation, compound rate of return, computerized trading, conceptual framework, corporate governance, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-border payments, cross-subsidies, currency risk, discounted cash flows, disintermediation, diversified portfolio, Dutch auction, equity premium, equity risk premium, eurozone crisis, fear index, financial engineering, financial innovation, financial intermediation, fixed income, frictionless, fudge factor, German hyperinflation, implied volatility, index fund, information asymmetry, intangible asset, interest rate swap, inventory management, Iridium satellite, James Webb Space Telescope, junk bonds, Kenneth Rogoff, Larry Ellison, law of one price, linear programming, Livingstone, I presume, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, low interest rates, market bubble, market friction, money market fund, moral hazard, Myron Scholes, new economy, Nick Leeson, Northern Rock, offshore financial centre, PalmPilot, Ponzi scheme, prediction markets, price discrimination, principal–agent problem, profit maximization, purchasing power parity, QR code, quantitative trading / quantitative finance, random walk, Real Time Gross Settlement, risk free rate, risk tolerance, risk/return, Robert Shiller, Scaled Composites, shareholder value, Sharpe ratio, short selling, short squeeze, Silicon Valley, Skype, SpaceShipOne, Steve Jobs, subprime mortgage crisis, sunk-cost fallacy, systematic bias, Tax Reform Act of 1986, The Nature of the Firm, the payments system, the rule of 72, time value of money, too big to fail, transaction costs, University of East Anglia, urban renewal, VA Linux, value at risk, Vanguard fund, vertical integration, yield curve, zero-coupon bond, zero-sum game, Zipcar

In this step only market risks are relevant. Avoid Fudge Factors in Discount Rates Think back to our example of project Z, where we reduced forecasted cash flows from $1 million to $900,000 to account for a possible failure of technology. The project’s PV was reduced from $909,100 to $818,000. You could have gotten the right answer by adding a fudge factor to the discount rate and discounting the original forecast of $1 million. But you have to think through the possible cash flows to get the fudge factor, and once you forecast the cash flows correctly, you don’t need the fudge factor. Fudge factors in discount rates are dangerous because they displace clear thinking about future cash flows.

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If he was right in the first place, and the true bias is 10%, then adding a 10% fudge factor to the discount rate understates PV. The fudge factor also makes long-lived projects look much worse than quick-payback projects.18 Discount Rates for International Projects In this chapter we have concentrated on domestic investments. In Chapter 27 we say more about investments made internationally. Here we simply warn against adding fudge factors to discount rates for projects in developing economies. Such fudge factors are too often seen in practice. It’s true that markets are more volatile in developing economies, but much of that risk is diversifiable for investors in the U.S., Europe, and other developed countries.

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There is a Third Law, but that is for another chapter. 2Adding a fudge factor to the cost of capital also favors quick-payback projects and penalizes longer-lived projects, which tend to have lower rates of return but higher NPVs. Adding a 5% fudge factor to the discount rate is roughly equivalent to reducing the forecast and present value of the first year’s cash flow by 5%. The impact on the present value of a cash flow 10 years in the future is much greater, because the fudge factor is compounded in the discount rate. The fudge factor is not too much of a burden for a 2- or 3-year project, but an enormous burden for a 10- or 20-year project. 3If you doubt this, try some simple experiments.

Ruby by example: concepts and code by Kevin C. Baird

Benevolent Dictator For Life (BDFL), David Heinemeier Hansson, Debian, digital map, Donald Knuth, en.wikipedia.org, Firefox, fudge factor, functional programming, general-purpose programming language, Guido van Rossum, Larry Wall, MVC pattern, Paul Graham, Perl 6, premature optimization, union organizing, web application

I knew the approximate ratio of the word processor’s 62 C ha pt er 4 word count versus the output of wc (I call this the fudge factor), and I could certainly do the math, but I wanted something that would do all of this for me automatically. Let’s take a look. The Code #!/usr/bin/env ruby # word_count.rb class String def num_matches(thing_to_match) return self.split(thing_to_match).size - 1 end # num_matches end # String BAR_LENGTH = 20 # to match these calculations with the output of some word processors FUDGE_FACTOR = 0.82 def word_count(files) Multiplying Strings output = '' total_word_count = 0 files.each do |filename| file_word_count = word_count_for_file(filename) output += "#{filename} has #{file_word_count} words.

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/usr/bin/env ruby # word_count.rb class String def num_matches(thing_to_match) return self.split(thing_to_match).size - 1 end # num_matches end # String BAR_LENGTH = 20 # to match these calculations with the output of some word processors FUDGE_FACTOR = 0.82 def word_count(files) Multiplying Strings output = '' total_word_count = 0 files.each do |filename| file_word_count = word_count_for_file(filename) output += "#{filename} has #{file_word_count} words.\n" total_word_count += file_word_count end # each file return output + '-' * BAR_LENGTH + "\n" + "Total word count = #{total_word_count}" + " (#{(total_word_count * FUDGE_FACTOR)})" end # word_count def word_count_for_file(filename) f = File.new(filename, 'r') contents = f.read() f.close() spaces = contents.num_matches(' ') breaks = contents.num_matches("\n") false_doubles = contents.num_matches(" \n") double_spaces = contents.num_matches(' ') hyphens = contents.num_matches('-') false_doubles += double_spaces + hyphens words = spaces + breaks - false_doubles + 1 return words end # word_count_for_file puts word_count(ARGV) Te xt M a ni pul at io n 63 How It Works We start out by adding a new method called num_matches to the String class ( ).

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\n" total_word_count += file_word_count end # each file return output + '-' * BAR_LENGTH + "\n" + "Total word count = #{total_word_count}" + " (#{(total_word_count * FUDGE_FACTOR)})" end # word_count def word_count_for_file(filename) f = File.new(filename, 'r') contents = f.read() f.close() spaces = contents.num_matches(' ') breaks = contents.num_matches("\n") false_doubles = contents.num_matches(" \n") double_spaces = contents.num_matches(' ') hyphens = contents.num_matches('-') false_doubles += double_spaces + hyphens words = spaces + breaks - false_doubles + 1 return words end # word_count_for_file puts word_count(ARGV) Te xt M a ni pul at io n 63 How It Works We start out by adding a new method called num_matches to the String class ( ). It simply returns the number of times the argument appears within the calling String. I also define top-level constants called BAR_LENGTH ( ), which is just for visual formatting, and FUDGE_FACTOR ( ), which I already noted is the ratio between the two different word-counting programs I was working with. We then define the word_count method ( ), which takes the files argument. You’ll notice on the last line of the script that this program takes an arbitrary number of filenames as its argument, which is different from our earlier scripts that would only deal with a single file at a time.

Relevant Search: With Examples Using Elasticsearch and Solr by Doug Turnbull, John Berryman

business logic, cognitive load, commoditize, crowdsourcing, data science, domain-specific language, Dr. Strangelove, fail fast, finite state, fudge factor, full text search, heat death of the universe, information retrieval, machine readable, natural language processing, premature optimization, recommendation engine, sentiment analysis, the long tail

You can see this in sum of from the previous explain: 3.19292, sum of: 3.19292, weight(title:alien in 223) [PerFieldSimilarity] 3.6.3. Practical caveats to the vector space model Although the vector space model provides a general framework for discussing Lucene’s scoring, it’s far from a complete picture. Numerous fudge factors have been shown to improve scoring in practice. Perhaps most fundamentally, the ways matches are combined by compound queries into a larger score isn’t always a summation. You’ve seen through the | symbol that the “max” of two fields is often taken. There’s also often a coord factor that directly punishes compound matches missing some of their components (coord multiplies the resulting dot product by <the number of matches> / <the total query terms>).

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Another important note about this dot product is that it’s often normalized by dividing the magnitude of each vector: For dot products, normalization converts the score to a 0–1. This rebalances the equation to account for features that tend to have high weights, and those that tend to have smaller weights.[3] For search, given all the fudge factors in Lucene scoring and the peculiarities of field statistics, you should never attempt to compare scores between queries without a great deal of deep customization to make them comparable. 3 Astute readers will recognize this as the cosine similarity. As stated previously, the sparse vector representation of text is known as the bag of words model.

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Taken together, Lucene’s classic similarity measures a term’s weight in a piece of text as follows: TF weighted × IDF weighted × fieldNorm Revisiting the fieldWeight calculation, you see this formula in play: 0.4414702, fieldWeight in 31, product of: 1.4142135, tf(freq=2.0), with freq of: 2.0, termFreq=2.0 3.9957323, idf(docFreq=1, maxDocs=40) 0.078125, fieldNorm(doc=31) Lucene’s next default similarity: BM25 Over the years, an alternate approach to computing a TF × IDF score has become prevalent in the information retrieval community: Okapi BM25. Because of its proven high performance on article-length text, Lucene’s BM25 similarity will be rolling out as the default similarity for Solr/Elasticsearch, even as you read this book. What is BM25? Instead of “fudge factors” as discussed previously, BM25 bases its TF × IDF “fudges” on more-robust information retrieval findings. This includes forcing the impact of TF to reach a saturation point. Instead of the impact of length (fieldNorms) always increasing, its impact is computed relative to the average document length (above-average docs weighted down, below-average boosted).

Isaac Newton by James Gleick

Albert Einstein, Astronomia nova, complexity theory, dark matter, Edmond Halley, Fellow of the Royal Society, fudge factor, Isaac Newton, Johannes Kepler, On the Revolutions of the Heavenly Spheres, Richard Feynman, Thomas Kuhn: the structure of scientific revolutions

Newton, by contrast, set himself, and science, the obligation to exclude nothing and calculate everything. As Westfall says, “So completely has modern physical science modeled itself on the Principia that we can scarcely realize how unprecedented such calculations were.” It was impossible, given the available data, and sometimes he cheated. Westfall, “Newton and the Fudge Factor,” Science 179 (February 23, 1973): 751. Also Nicholas Kollerstrom, “Newton’s Lunar Mass Error,” Journal of the British Astronomical Association 95 (1995): 151. For another example of what Whiteside calls “the delicate art of numerical cookery,” see Math VI: 508–36. 23. Principia 807. 24. Principia 806. 25.

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A History of the Royal Society, with Memoirs of the Presidents. London: 1848. Westfall, Richard S. Force in Newton’s Physics: The Science of Dynamics in the Seventeenth Century. London: Macdonald, 1971. ———. Never at Rest: A Biography of Isaac Newton. Cambridge: Cambridge University Press, 1980. ———. “Newton and the Fudge Factor,” Science 179: 751. ———. Science and Religion in Seventeenth-Century England. New Haven: Yale University Press, 1958. ———. “Short-Writing and the State of Newton’s Conscience, 1662.” Notes and Records of the Royal Society 18 (1963): 10. Whiston, William. Memoirs of the Life and Writings of Mr.

In the Age of the Smart Machine by Shoshana Zuboff

affirmative action, American ideology, blue-collar work, collective bargaining, computer age, Computer Numeric Control, conceptual framework, data acquisition, demand response, deskilling, factory automation, Ford paid five dollars a day, fudge factor, future of work, industrial robot, information retrieval, interchangeable parts, job automation, lateral thinking, linked data, Marshall McLuhan, means of production, old-boy network, optical character recognition, Panopticon Jeremy Bentham, pneumatic tube, post-industrial society, radical decentralization, RAND corporation, scientific management, Shoshana Zuboff, social web, systems thinking, tacit knowledge, The Wealth of Nations by Adam Smith, Thorstein Veblen, union organizing, vertical integration, work culture , zero-sum game

An operator who worked regularly with the calculator models de- scribed his frustration at not having access to their underlying assump- tions and algorithms, which he called "fudge factors": 278 AUTHORITY: THE SPIRITUAL DIMENSION OF POWER The models use equations, fudge factors, put in there to make sure you make quality pulp. If you don't know these fudge factors, they can work against you. I had to talk the engineers into explaining the fudge factors to me. The assumptions of the designers are never explained to us. You cannot really be controlling the process if you don't understand these things. As long as it's a black box to me, all I can do is babysit the computer.

The Knowledge Machine: How Irrationality Created Modern Science by Michael Strevens

Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Atul Gawande, coronavirus, COVID-19, dark matter, data science, Eddington experiment, Edmond Halley, Fellow of the Royal Society, fudge factor, germ theory of disease, Great Leap Forward, Gregor Mendel, heat death of the universe, Higgs boson, Intergovernmental Panel on Climate Change (IPCC), invention of movable type, invention of the telescope, Isaac Newton, Islamic Golden Age, Johannes Kepler, Large Hadron Collider, longitudinal study, Louis Pasteur, military-industrial complex, Murray Gell-Mann, Peace of Westphalia, Richard Feynman, Stephen Hawking, Steven Pinker, systematic bias, Thales of Miletus, the scientific method, Thomas Bayes, William of Occam

The role of Kuhn’s ideas in contemporary history of science is laid out succinctly in Mario Biagioli’s short paper “Productive Illusions.” 47 science’s biggest names can be seen discarding: See, respectively, Fisher, “Has Mendel’s Work Been Rediscovered?”; Richardson et al., “There Is No Highly Conserved Embryonic Stage in the Vertebrates”; Holton, “Subelectrons, Presuppositions, and the Millikan-Ehrenhaft Dispute”; Westfall, “Newton and the Fudge Factor” (the quote is from p. 753). In each case, accusations of impropriety have spurred illuminating debates about the culpability of the scientists and the damage done to science—with some writers arguing for little culpability and less damage—but there is scant doubt that a certain amount of deliberate misrepresentation took place. 48 Eddington’s original presentation: Dyson, Eddington, and Davidson, “Determination of the Deflection of Light.” 52 Pasteur and Pouchet had sparred: This story is told in Collins and Pinch, The Golem, which also contains a brief, accessible, and rather unsympathetic account of Eddington’s maneuvers. 52 a combative and unfair disputant: A balanced biography that takes the notebooks into account is Patrice Debré’s Louis Pasteur. 53 the industry-supported group is considerably more likely: On soda: Bes-Rastrollo et al., “Financial Conflicts of Interest and Reporting Bias Regarding the Association between Sugar-Sweetened Beverages and Weight Gain.”

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The Thirty Years War. London: Jonathan Cape, 1938. Weinberg, S. Dreams of a Final Theory. New York: Pantheon, 1992. Weiner, J. The Beak of the Finch. New York: Knopf, 1994. Westfall, R. S. Never at Rest: A Biography of Isaac Newton. Cambridge: Cambridge University Press, 1983. Westfall, R. S. “Newton and the Fudge Factor.” Science 179 (1973): 751–8. Whewell, W. Astronomy and General Physics Considered with Reference to Natural Theology. Vol. 3 of The Bridgewater Treatises on the Power, Wisdom and Goodness of God as Manifested in the Creation. London: William Pickering, 1833. Whewell, W. History of the Inductive Sciences, from the Earliest to the Present Times.

Arguing With Zombies: Economics, Politics, and the Fight for a Better Future by Paul Krugman

affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, Andrei Shleifer, antiwork, Asian financial crisis, bank run, banking crisis, basic income, behavioural economics, benefit corporation, Berlin Wall, Bernie Madoff, bitcoin, blockchain, bond market vigilante , Bonfire of the Vanities, business cycle, capital asset pricing model, carbon footprint, carbon tax, Carmen Reinhart, central bank independence, centre right, Climategate, cognitive dissonance, cryptocurrency, David Ricardo: comparative advantage, different worldview, Donald Trump, Edward Glaeser, employer provided health coverage, Eugene Fama: efficient market hypothesis, fake news, Fall of the Berlin Wall, fiat currency, financial deregulation, financial innovation, financial repression, frictionless, frictionless market, fudge factor, full employment, green new deal, Growth in a Time of Debt, hiring and firing, illegal immigration, income inequality, index fund, indoor plumbing, invisible hand, it is difficult to get a man to understand something, when his salary depends on his not understanding it, job automation, John Snow's cholera map, Joseph Schumpeter, Kenneth Rogoff, knowledge worker, labor-force participation, large denomination, liquidity trap, London Whale, low interest rates, market bubble, market clearing, market fundamentalism, means of production, Modern Monetary Theory, New Urbanism, obamacare, oil shock, open borders, Paul Samuelson, plutocrats, Ponzi scheme, post-truth, price stability, public intellectual, quantitative easing, road to serfdom, Robert Gordon, Robert Shiller, Ronald Reagan, secular stagnation, Seymour Hersh, stock buybacks, The Chicago School, The Great Moderation, the map is not the territory, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, universal basic income, very high income, We are all Keynesians now, working-age population

But the New Keynesian models that have come to dominate teaching and research assume that people are perfectly rational and financial markets are perfectly efficient. To get anything like the current slump into their models, New Keynesians are forced to introduce some kind of fudge factor that for reasons unspecified temporarily depresses private spending. (I’ve done exactly that in some of my own work.) And if the analysis of where we are now rests on this fudge factor, how much confidence can we have in the models’ predictions about where we are going? The state of macro, in short, is not good. So where does the profession go from here? VII. FLAWS AND FRICTIONS Economics, as a field, got in trouble because economists were seduced by the vision of a perfect, frictionless market system.

UNIX® Network Programming, Volume 1: The Sockets Networking API, 3rd Edition by W. Richard Stevens, Bill Fenner, Andrew M. Rudoff

Dennis Ritchie, exponential backoff, failed state, fudge factor, global macro, history of Unix, information retrieval, OpenAI, OSI model, p-value, RFC: Request For Comment, Richard Stallman, UUNET, web application

The historical definition in this bullet is the Berkeley implementation, dating back to 4.2BSD, and copied by many others. • Berkeley-derived implementations add a fudge factor to the backlog: It is multiplied by 1.5 (p. 257 of TCPv1 and p. 462 of TCPv2). For example, the commonly specified backlog of 5 really allows up to 8 queued entries on these systems, as we show in Figure 4.10. The reason for adding this fudge factor appears lost to history [Joy 1994]. But if we consider the backlog as specifying the maximum number of completed connections that the kernel will queue for a socket ([Borman 1997b], as discussed shortly), then the reason for the fudge factor is to take into account incomplete connections on the queue

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This time, the variable pointed to by lenp will return with the amount of information stored in the buffer, and this variable is allocated by the caller. A pointer to the buffer is also returned to the caller. Since the size of the routing table or the number of interfaces can change between the two calls to sysctl, the value returned by the first call contains a 10% fudge factor (pp. 639 – 640 of TCPv2). Section 18.5 get_ifi_info Function (Revisited) 501 Figure 18.16 shows the first half of the get_ifi_info function. 3 struct ifi_info * 4 get_ifi_info(int family, int doaliases) 5 { 6 int flags; 7 char *buf, *next, *lim; 8 size_t len; 9 struct if_msghdr *ifm; 10 struct ifa_msghdr *ifam; 11 struct sockaddr *sa, *rti_info[RTAX_MAX]; 12 struct sockaddr_dl *sdl; 13 struct ifi_info *ifi, *ifisave, *ifihead, **ifipnext; route/get_ifi_info.c 14 buf = Net_rt_iflist(family, 0, &len); 15 16 ifihead = NULL; ifipnext = &ifihead; 17 18 19 20 21 22 lim = buf + len; for (next = buf; next < lim; next += ifm->ifm_msglen) { ifm = (struct if_msghdr *) next; if (ifm->ifm_type == RTM_IFINFO) { if (((flags = ifm->ifm_flags) & IFF_UP) == 0) continue; /* ignore if interface not up */ 23 24 25 26 27 28 sa = (struct sockaddr *) (ifm + 1); get_rtaddrs(ifm->ifm_addrs, sa, rti_info); if ( (sa = rti_info[RTAX_IFP]) !

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., xxiii free function, 508, 684 free_ifi_info function, 471, 478 source code, 480 freeaddrinfo function, 321, 327, 345 definition of, 321 FreeBSD, 20 – 24, 78, 108, 197, 260 – 262, 299, 405, 469, 473, 497, 538, 658, 666, 710, 775, 882 – 883, 891, 897, 904, 926, 934, 939 – 940 freehostent function, 347 definition of, 347 frequently asked question, see FAQ fseek function, 400 fsetpos function, 400 fstat function, 406 fstat program, 897 FTP (File Transfer Protocol), 20, 62, 201, 311 – 312, 360, 362, 366, 375, 662, 914, 947 fudge factor, 106, 500 full-duplex, 36, 415 Fuller, V., 874, 949 fully buffered standard I/O stream, 401 fully qualified domain name, see FQDN function destructor, 690 system call versus, 891 wrapper, 11 – 13 gai_strerror function, 320 – 321 definition of, 321 Ganguly, S., 285, 953 Garcia, M., 267, 952 Garfinkel, S.

The Grand Design by Stephen Hawking, Leonard Mlodinow

airport security, Albert Einstein, Albert Michelson, anthropic principle, Arthur Eddington, Buckminster Fuller, conceptual framework, cosmic microwave background, cosmological constant, dark matter, fudge factor, invention of the telescope, Isaac Newton, Johannes Kepler, John Conway, John von Neumann, Large Hadron Collider, luminiferous ether, Mercator projection, Richard Feynman, Stephen Hawking, Thales of Miletus, the scientific method, Turing machine

Elegance, for example, is not something easily measured, but it is highly prized among scientists because laws of nature are meant to economically compress a number of particular cases into one simple formula. Elegance refers to the form of a theory, but it is closely related to a lack of adjustable elements, since a theory jammed with fudge factors is not very elegant. To paraphrase Einstein, a theory should be as simple as possible, but not simpler. Ptolemy added epicycles to the circular orbits of the heavenly bodies in order that his model might accurately describe their motion. The model could have been made more accurate by adding epicycles to the epicycles, or even epicycles to those.

The Most Powerful Idea in the World: A Story of Steam, Industry, and Invention by William Rosen

Albert Einstein, All science is either physics or stamp collecting, barriers to entry, Charles Babbage, collective bargaining, computer age, Copley Medal, creative destruction, David Ricardo: comparative advantage, decarbonisation, delayed gratification, Fellow of the Royal Society, flying shuttle, Flynn Effect, fudge factor, full employment, Higgs boson, independent contractor, invisible hand, Isaac Newton, Islamic Golden Age, iterative process, James Hargreaves, James Watt: steam engine, John Harrison: Longitude, Joseph Schumpeter, Joseph-Marie Jacquard, knowledge economy, language acquisition, Lewis Mumford, moral hazard, Network effects, Panopticon Jeremy Bentham, Paul Samuelson, Peace of Westphalia, Peter Singer: altruism, QWERTY keyboard, Ralph Waldo Emerson, rent-seeking, Robert Solow, Ronald Coase, Simon Kuznets, spinning jenny, tacit knowledge, the scientific method, The Wealth of Nations by Adam Smith, Thomas Malthus, three-masted sailing ship, transaction costs, transcontinental railway, zero-sum game, éminence grise

IF THE CAST IRON used for pots and pans was the most mundane version of the element, the most sublime was steel. As with all iron alloys, carbon is steel’s critical component. In its simplest terms, wrought iron has essentially no minimum amount of carbon, just as there is no maximum carbon content for cast iron. As a result, the recipe for either has a substantial fudge factor. Not so with steel. Achieving steel’s unique combination of strengths demands a very narrow range of carbon: between 0.25 percent and a bit less than 2 percent. For centuries* this has meant figuring out how to initiate the process whereby carbon insinuates itself into iron’s crystalline structure, and how to stop it once it achieves the proper percentage.

…

Except during times of dramatic depopulation, such as the Black Death of the fourteenth century, or extremely large additions to the stock of arable land, as with Europe’s discovery of the New World, growth in land per worker has been negligible for centuries, so small that its effect on growth can be eliminated in the simplest calculations. The second component, growth in capital3 per worker—that is, all the buildings, machinery, tools, and so on—explains only about 24 percent of total growth. However, since the growth in the amount of land and capital per worker together doesn’t equal the overall growth rate, a fudge factor must be used, called the residual: what’s left over. This also means that the residual, despite the ass-backward way it is calculated, amounts to at least three-quarters of the total increase in economic growth since 1800. That’s a big chunk of activity defined by subtracting everything else, a little like a ten-drawer file cabinet with seven drawers marked “Miscellaneous.”

The God Equation: The Quest for a Theory of Everything by Michio Kaku

Albert Einstein, anthropic principle, Arthur Eddington, cosmic microwave background, cosmological constant, dark matter, double helix, Eddington experiment, Edmond Halley, Ernest Rutherford, fudge factor, Higgs boson, Isaac Newton, Johannes Kepler, Large Hadron Collider, Murray Gell-Mann, Olbers’ paradox, place-making, Richard Feynman, Schrödinger's Cat, Stephen Hawking, Tacoma Narrows Bridge, uranium enrichment

(He did not realize this at the time, but this was the solution to the question asked by Richard Bentley. The universe did not collapse under gravity because the universe was expanding, overcoming the tendency to collapse.) In order to find a static universe, Einstein was forced to add a fudge factor (called the cosmological constant) into his equations. By adjusting its value by hand, he could cancel out the expansion or contraction of the universe. Later, in 1929, astronomer Edwin Hubble, by using the giant Mount Wilson Observatory telescope in California, was able to make a startling discovery.

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

airline deregulation, Alan Greenspan, Albert Einstein, bank run, barriers to entry, behavioural economics, Bretton Woods, business cycle, butterfly effect, capital controls, carbon tax, Carmen Reinhart, central bank independence, collective bargaining, congestion pricing, 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 elasticity of demand, price stability, prisoner's dilemma, profit maximization, public intellectual, quantitative easing, randomized controlled trial, rent control, rent-seeking, Richard Thaler, risk/return, 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 standards of the profession require that the modeler make only some general claims about how what he or she is doing is relevant to the real world. It is left to the reader or the user of the model to infer the specific circumstances in which the model can help us better understand reality.§ This fudge factor increases the chances of malpractice. Models lifted out of their original context can be used in settings for which they are inappropriate. At the empirical end of economics, such as labor and development economics, where almost all economists work directly with data and real-world evidence, paradoxically the problems may be even more severe.

They Have a Word for It A Lighthearted Lexicon of Untranslatable Words & Phrases-Sarabande Books (2000) by Howard Rheingold

Ayatollah Khomeini, clockwork universe, Easter island, fudge factor, Howard Rheingold, informal economy, junk bonds, Kula ring, Lao Tzu, Ronald Reagan, Rosa Parks, Silicon Valley, systems thinking, The Home Computer Revolution, the map is not the territory, the scientific method, Tragedy of the Commons

/aux.frais(French) Items you are likely to forget to include when making a budget. [noun] Here's a problem that vexes small households and sovereign nations: figuring out in advance how you are going to spend your money. No matter how thoroughly you do your research, how conscientiously you build in fudge factors, Serious Business 127 how hard you work at sticking to a prearranged budget, doesn't it seem as if you always end up outspending your target amount, especially if it is an annual budget? How does this happen? Did you remember to include the cost of replacing a cracked windshield or removing an impacted wisdom tooth?

Our Robots, Ourselves: Robotics and the Myths of Autonomy by David A. Mindell

Air France Flight 447, air gap, Apollo 11, Apollo 13, Apollo Guidance Computer, autonomous vehicles, Beryl Markham, Boeing 747, Captain Sullenberger Hudson, Charles Lindbergh, Chris Urmson, digital map, disruptive innovation, driverless car, drone strike, Easter island, en.wikipedia.org, Erik Brynjolfsson, fudge factor, Gene Kranz, human-factors engineering, index card, John Markoff, low earth orbit, Mars Rover, Neil Armstrong, ride hailing / ride sharing, Ronald Reagan, self-driving car, Silicon Valley, telepresence, telerobotics, trade route, US Airways Flight 1549, William Langewiesche, zero-sum game

I asked my colleague Jon How, one of the principals on the project, how many such thresholds there are in a system like that. His reply: “Many, many, many.” In fact the “configuration file” for the MIT vehicle contained nearly a thousand lines of text, setting hundreds of variables: sensor positions and calibrations, fudge factors to align the sensors with one another, how to deal with sun dazzle, etc. Machine learning techniques can help reduce this reliance on parameters, but they still rely on human programmers for their basic structure. How points out that core algorithms generally rely heavily on accurate models of uncertainty in the world.

Shipping Greatness by Chris Vander Mey

business logic, corporate raider, don't be evil, en.wikipedia.org, fudge factor, Google Chrome, Google Hangouts, Gordon Gekko, Jeff Bezos, Kickstarter, Lean Startup, minimum viable product, performance metric, recommendation engine, Skype, slashdot, sorting algorithm, source of truth, SQL injection, Steve Jobs, Superbowl ad, two-pizza team, web application

The testing constant is a function of the size of your test team. In the spreadsheet shown in Figure 4-1, I’ve added some calculations to ensure that tasks don’t end on the weekends. Because this model uses “ideal” developer days for estimates, it is critical to build a buffer into your dates, but not the engineering task estimates. A buffer is a “fudge factor” that accommodates unforeseen problems and general productivity losses. Some teams estimate that approximately three out of five days are productive. Anything could be happening in those two days, but it’s likely some combination of meetings, broken builds, marriage problems, and false starts.

Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It by Erica Thompson

Alan Greenspan, Bayesian statistics, behavioural economics, Big Tech, Black Swan, butterfly effect, carbon tax, coronavirus, correlation does not imply causation, COVID-19, data is the new oil, data science, decarbonisation, DeepMind, Donald Trump, Drosophila, Emanuel Derman, Financial Modelers Manifesto, fudge factor, germ theory of disease, global pandemic, hindcast, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, implied volatility, Intergovernmental Panel on Climate Change (IPCC), John von Neumann, junk bonds, Kim Stanley Robinson, lockdown, Long Term Capital Management, moral hazard, mouse model, Myron Scholes, Nate Silver, Neal Stephenson, negative emissions, paperclip maximiser, precautionary principle, RAND corporation, random walk, risk tolerance, selection bias, self-driving car, social distancing, Stanford marshmallow experiment, statistical model, systematic bias, tacit knowledge, tail risk, TED Talk, The Great Moderation, The Great Resignation, the scientific method, too big to fail, trolley problem, value at risk, volatility smile, Y2K

Even I probably wouldn’t change π (although my colleague at the London School of Economics Leonard Smith points out that I do change the value of π every time I use a digital computer). And yet what you are doing, in making a model, is exactly that: simplifying reality away from the messy truth towards something that happens to be more tractable. Why is it that it feels totally acceptable to make simplifications or add in empirically derived fudge factors along some dimensions, but to do so along others would be complete sacrilege even if it resulted in a model that could make demonstrably better predictions? Model laws are not real laws If model quantities are not real quantities, what about model laws? Perhaps we were getting close to that when we discussed π and the conservation of mass.

Frequently Asked Questions in Quantitative Finance by Paul Wilmott

Abraham Wald, Albert Einstein, asset allocation, beat the dealer, Black-Scholes formula, Brownian motion, butterfly effect, buy and hold, capital asset pricing model, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, delta neutral, discrete time, diversified portfolio, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial engineering, fixed income, fudge factor, implied volatility, incomplete markets, interest rate derivative, interest rate swap, iterative process, lateral thinking, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, market bubble, martingale, Myron Scholes, Norbert Wiener, Paul Samuelson, power law, quantitative trading / quantitative finance, random walk, regulatory arbitrage, risk free rate, risk/return, Sharpe ratio, statistical arbitrage, statistical model, stochastic process, stochastic volatility, transaction costs, urban planning, value at risk, volatility arbitrage, volatility smile, Wiener process, yield curve, zero-coupon bond

First, if we do start to move outside the Black-Scholes world then chances are it will be the diffusion coefficient that we must change from its usual to accommodate new models. Second, if we want to fudge our option prices, to massage them into line with traded prices for example, we can only do so by fiddling with this diffusion coefficient, i.e. what we now know to be the volatility. This derivation tells us that our only valid fudge factor is the volatility. Black-Scholes for Accountants The final derivation of the Black-Scholes equation requires very little complicated mathematics, and doesn’t even need assumptions about Gaussian returns, all we need is for the variance of returns to be finite. The Black-Scholes analysis requires continuous hedging, which is possible in theory but impossible, and even undesirable, in practice.

The Healing of America: A Global Quest for Better, Cheaper, and Fairer Health Care by T. R. Reid

Berlin Wall, British Empire, double helix, employer provided health coverage, fudge factor, Kenneth Arrow, medical malpractice, profit maximization, profit motive, single-payer health, South China Sea, the payments system

Colombia, with health care funded by a steeply progressive tax code, topped the chart on this scale, followed closely by western European countries and Japan. Finally, the WHO experts took all these factors, tabulated each country’s score on each measure, and arrived at its rating of “overall performance.” But this score was adjusted by one more fudge factor: a comparison of each country’s actual performance on national health care to the overall performance it should have been able to achieve, considering its level of education and the amount of money it spends on health care.With this ultimate wrinkle factored in, the report finally came up with its ranking of “overall performance” in all 191 member nations.

Quarantine by Greg Egan

cosmic microwave background, dark matter, disinformation, fudge factor, intermodal, pattern recognition, placebo effect, Schrödinger's Cat, time dilation, warehouse robotics

‘Oh, nobody’s done anything. Nothing’s changed. It just… all seems even more stupid and oppressive than usual, today. I read an article in Physical Review this morning: a whole new treatment of the measurement problem. They add a few more dimensions to space-time; throw in a few nonlinearities, asymmetries and assorted fudge factors; and—miracle of miracles!—the collapse of the wave falls out the other end.’ I know I should have dutifully silenced her half-way through the word ‘measurement’—if only for the sake of appearances—but the hypocrisy would have been too much. She says, ‘People are wasting valuable time, heading down paths that I know are blind alleys.

Duped: Double Lives, False Identities, and the Con Man I Almost Married by Abby Ellin

Bernie Madoff, bitcoin, Burning Man, business intelligence, Charles Lindbergh, cognitive dissonance, cognitive load, content marketing, dark triade / dark tetrad, Donald Trump, double helix, dumpster diving, East Village, fake news, feminist movement, forensic accounting, fudge factor, hiring and firing, Internet Archive, John Darwin disappearance case, longitudinal study, Lyft, mandatory minimum, meta-analysis, pink-collar, Ponzi scheme, post-truth, Robert Hanssen: Double agent, Ronald Reagan, Silicon Valley, Skype, Snapchat, TED Talk, telemarketer, theory of mind, Thomas Kuhn: the structure of scientific revolutions

What if they claimed to be six feet tall but were a mere five foot three in real life? People would notice that kind of discrepancy. But if they said they were five four and were really five three? That was a little more plausible. What’s an inch among lovers?3 Behavioral economist Dan Ariely, author of The (Honest) Truth About Dishonesty, said we all cheat by a “fudge factor” of roughly 15 percent.4 But some of us advance to such big lies that we’re practically drowning in the gooey concoction. The Commander certainly used fragments of the truth, combined them with untruths, and shot it all out of a cannon. He really was a doctor in private practice in Beverly Hills, and had a PhD and an MD.

Carjacked: The Culture of the Automobile and Its Effect on Our Lives by Catherine Lutz, Anne Lutz Fernandez

"Hurricane Katrina" Superdome, barriers to entry, Bear Stearns, book value, car-free, carbon footprint, collateralized debt obligation, congestion pricing, failed state, feminist movement, Ford Model T, fudge factor, Gordon Gekko, housing crisis, illegal immigration, income inequality, inventory management, Lewis Mumford, market design, market fundamentalism, mortgage tax deduction, Naomi Klein, Nate Silver, New Urbanism, oil shock, peak oil, Ralph Nader, Ralph Waldo Emerson, ride hailing / ride sharing, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, traffic fines, traumatic brain injury, Unsafe at Any Speed, urban planning, white flight, women in the workforce, working poor, Zipcar

With greater model diversity and the niche marketing of those models to a complex set of demographics that began most vigorously in the 1970s, the automobile became more than a marker of class.21 And in an environment where credit is sold so aggressively, the car today is less a reliable sign of hard work done and money earned than of hard work yet to be done and money yet to be earned. (Now the more appropriate comment to a new car buyer might be “Congratulations on your debt!”) Despite these fudging factors, class remains legible in one’s car, a fact that provides some of the sweetest pleasures to those who drive more expensive and late-model cars. Even the way some talk about how they drive sounds a lot like how they think about getting ahead. Said one man: “I have a life philosophy. If you do what the herd does, you get what the herd gets.”

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

air freight, Al Roth, Alan Greenspan, Bear Stearns, behavioural economics, Bernie Madoff, Burning Man, butterfly effect, Cass Sunstein, collateralized debt obligation, compensation consultant, 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, John Perry Barlow, lake wobegon effect, late fees, loss aversion, market bubble, Murray Gell-Mann, payday loans, Pepsi Challenge, placebo effect, price anchoring, Richard Thaler, second-price auction, Silicon Valley, Skinner box, Skype, subprime mortgage crisis, The Wealth of Nations by Adam Smith, Upton Sinclair

On the other hand, we’re selfish, and we want to benefit from cheating. On the surface, these two motivations seem contradictory, but our flexible psychology allows us to act on both of them when we cheat “just by a bit”—benefiting financially from cheating while at the same time managing not to feel bad about ourselves. I think of this as an individual “fudge factor,” or a fuzzy conscience. One way to look at the experiments described in Chapters 11 and 12 is to think about them as an examination of what happens when people wrestle with conflicting interests. When we placed participants in situations in which they were torn between wanting to behave honorably and wanting to benefit financially, they usually succumbed to temptation but only by a little bit.

Woke, Inc: Inside Corporate America's Social Justice Scam by Vivek Ramaswamy

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 2021 United States Capitol attack, activist fund / activist shareholder / activist investor, affirmative action, Airbnb, Amazon Web Services, An Inconvenient Truth, anti-bias training, Bernie Sanders, Big Tech, BIPOC, Black Lives Matter, carbon footprint, clean tech, cloud computing, contact tracing, coronavirus, corporate governance, corporate social responsibility, COVID-19, critical race theory, crony capitalism, cryptocurrency, defund the police, deplatforming, desegregation, disinformation, don't be evil, Donald Trump, en.wikipedia.org, Eugene Fama: efficient market hypothesis, fudge factor, full employment, George Floyd, glass ceiling, global pandemic, green new deal, hiring and firing, Hyperloop, impact investing, independent contractor, index fund, Jeff Bezos, lockdown, Marc Benioff, Mark Zuckerberg, microaggression, military-industrial complex, Network effects, Parler "social media", plant based meat, Ponzi scheme, profit maximization, random walk, ride hailing / ride sharing, risk-adjusted returns, Robert Bork, Robinhood: mobile stock trading app, Ronald Reagan, Salesforce, self-driving car, shareholder value, short selling, short squeeze, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, single source of truth, Snapchat, social distancing, Social Responsibility of Business Is to Increase Its Profits, source of truth, sovereign wealth fund, Susan Wojcicki, the scientific method, Tim Cook: Apple, too big to fail, trade route, transcontinental railway, traveling salesman, trickle-down economics, Vanguard fund, Virgin Galactic, WeWork, zero-sum game

Institutional Investor observed that the median annualized return between 2010 and 2019 of ESG equity funds with a track record of at least 10 years and $100 million in assets was only 11.98 percent, while the S&P 500 had returned an annualized 13.56 percent. Volatility was identical across both indices, suggesting that ESG assets underperformed not only on an absolute basis but on a risk-adjusted basis as well.10 Many of the analyses in favor of ESG outperformance are cherry-picked. Fudge factors include which companies to include versus exclude, the relevant time horizon to examine, what benchmark indices to use, and so on. Those are fundamentally subjective decisions, often made by the very people who know what conclusion they wish to reach. In sum, the existence of dueling data sets shouldn’t surprise anyone—in this case, the “data” itself is a charade.

Infinite Powers: How Calculus Reveals the Secrets of the Universe by Steven Strogatz

Albert Einstein, Asperger Syndrome, Astronomia nova, Bernie Sanders, clockwork universe, complexity theory, cosmological principle, Dava Sobel, deep learning, DeepMind, double helix, Edmond Halley, Eratosthenes, four colour theorem, fudge factor, Henri Poincaré, invention of the telescope, Isaac Newton, Islamic Golden Age, Johannes Kepler, John Harrison: Longitude, Khan Academy, Laplace demon, lone genius, music of the spheres, pattern recognition, Paul Erdős, Pierre-Simon Laplace, precision agriculture, retrograde motion, Richard Feynman, Socratic dialogue, Steve Jobs, the rule of 72, the scientific method

No one could imagine a universe so immense with stars so remote, much farther away than the planets. Today we know that is exactly the case, but back then it was inconceivable. So the Earth-centered cosmology, for all its faults, seemed like the more plausible picture. Suitably modified by the ancient Greek astronomer Ptolemy with epicycles, equants, and other fudge factors, the theory could be made to account reasonably well for planetary motion and it kept the calendar in line with seasonal cycles. The Ptolemaic system was clunky and complicated, but it worked well enough to last into the late Middle Ages. Two books published in 1543 marked a turning point, the beginning of the scientific revolution.

Your Money or Your Life: 9 Steps to Transforming Your Relationship With Money and Achieving Financial Independence: Revised and Updated for the 21st Century by Vicki Robin, Joe Dominguez, Monique Tilford

asset allocation, book value, Buckminster Fuller, buy low sell high, classic study, credit crunch, disintermediation, diversification, diversified portfolio, fiat currency, financial independence, fixed income, fudge factor, full employment, Gordon Gekko, high net worth, index card, index fund, intentional community, job satisfaction, junk bonds, Menlo Park, money market fund, Parkinson's law, passive income, passive investing, profit motive, Ralph Waldo Emerson, retail therapy, Richard Bolles, risk tolerance, Ronald Reagan, Silicon Valley, software patent, strikebreaker, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Vanguard fund, zero-coupon bond

“But must I keep track of every cent?” you may ask. Yes, every cent! Why every cent, rather than just rounding off to the nearest dollar, or using approximate figures? Because this helps to establish important lifelong habits. After all, how big is a “Finagler’s Constant”? What’s the definition of a “Fudge Factor”? How close is “close enough”? Granted, in practice many FIers settle into rounding to the dollar, but that’s as far as they slip. Human nature being what it is, if you start cheating, even “just a little bit,” that little bit tends to get bigger and soon you’ll find yourself thinking, “Well, I don’t have to write everything down, just the major expenses”; and then, “Well, I’ve done this for a month now, so I think I’ll start rounding it off to the nearest thousand.”

The Ultimate Engineer: The Remarkable Life of NASA's Visionary Leader George M. Low by Richard Jurek

additive manufacturing, affirmative action, Apollo 11, Apollo 13, Charles Lindbergh, cognitive dissonance, en.wikipedia.org, Ford Model T, fudge factor, Gene Kranz, human-factors engineering, it's over 9,000, John Conway, low earth orbit, Mars Rover, Neil Armstrong, operation paperclip, orbital mechanics / astrodynamics, private spaceflight, Ronald Reagan, Silicon Valley, Silicon Valley ideology, Stewart Brand, undersea cable, uranium enrichment, Whole Earth Catalog, Winter of Discontent, women in the workforce

I mentioned that one of the things that made Apollo feasible was Jim Webb’s original estimate of between $20 to $40 billion,” he explained. Apollo came in at around $24 billion; in his original Low committee report, he had estimated the program at just $7 billion. Webb, an old budget hand, knew the game of government budgets. He multiplied Low’s estimate by a healthy fudge factor. It worked. “With Webb’s high estimate, we never had a problem in defending Apollo costs again during the early days of the program,” he explained to Paine.16 “The agency’s initial budget request in 1970 started out at $4.5 billion for 1971. It was based on moving out with speed on the Space Task Group’s planning,” Low remembered.

Day We Found the Universe by Marcia Bartusiak

Albert Einstein, Albert Michelson, Arthur Eddington, California gold rush, Cepheid variable, Copley Medal, cosmic microwave background, cosmological constant, Eddington experiment, Edmond Halley, Edward Charles Pickering, Fellow of the Royal Society, fudge factor, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, horn antenna, invention of the telescope, Isaac Newton, Louis Pasteur, Magellanic Cloud, Occam's razor, orbital mechanics / astrodynamics, Pluto: dwarf planet, William of Occam

Stellar objects would be gravitationally drawn to one another, closer and closer over time. Ultimately, the universe would collapse under the inescapable pull of gravity. So, to avoid this cosmic calamity and match his theory with then-accepted astronomical observations, Einstein altered his famous equation, adding the term λ (the Greek letter lambda), a fudge factor that came to be called the “cosmological constant.” This new ingredient was an added energy that permeated empty space and exerted an outward “pressure” on it. This repulsive field—a kind of antigravity, actually—exactly balanced the inward gravitational attraction of all the matter in his closed universe, keeping it from moving.

The Invention of Science: A New History of the Scientific Revolution by David Wootton

agricultural Revolution, Albert Einstein, book value, British Empire, classic study, clockwork universe, Commentariolus, commoditize, conceptual framework, Dava Sobel, double entry bookkeeping, double helix, en.wikipedia.org, Ernest Rutherford, Fellow of the Royal Society, fudge factor, germ theory of disease, Google X / Alphabet X, Hans Lippershey, interchangeable parts, invention of gunpowder, invention of the steam engine, invention of the telescope, Isaac Newton, Jacques de Vaucanson, James Watt: steam engine, Johannes Kepler, John Harrison: Longitude, knowledge economy, Large Hadron Collider, lateral thinking, lone genius, Mercator projection, On the Revolutions of the Heavenly Spheres, Philip Mirowski, placebo effect, QWERTY keyboard, Republic of Letters, social intelligence, spice trade, spinning jenny, Suez canal 1869, tacit knowledge, technological determinism, the scientific method, Thomas Kuhn: the structure of scientific revolutions

‘The Accuracy of Tycho Brahe’s Instruments’. Journal for the History of Astronomy 9 (1978): 42–53. Westfall, Richard S. ‘The Development of Newton’s Theory of Color’. Isis (1962): 339–58. ———. Never at Rest: A Biography of Isaac Newton. Cambridge: Cambridge University Press, 1980. ———. ‘Newton and the Fudge Factor’. Science 179 (1973): 751–8. ———. ‘Science and Technology during the Scientific Revolution: An Empirical Approach’. In Renaissance and Revolution. Humanists, Scholars, Craftsmen and Natural Philosophers in Early Modern Europe. Ed. JV Field and FA James. Cambridge: Cambridge University Press, 1997: 63–72. ———.

…

Galileo’s second letter on sunspots (1612), in Galilei & Scheiner, On Sunspots (2008), 107–70. 48. ‘Préface sur le traité du vuide’, in Pascal, Oeuvres complètes (1964), Vol. 2, 772–85. 49. Dear, Discipline and Experience (1995), 15, 180; for an example published by Riccioli in 1651, 78. 50. Palmerino, ‘Experiments, Mathematics, Physical Causes’ (2010); and Westfall, ‘Newton and the Fudge Factor’ (1973). 51. The legal issues and their history were recently summarized in the House of Lords judgement on Regina v. Pendleton, 13 Dec. 2001. 52. Locke, An Essay (1690), 333. 53. Hobbes, Humane Nature (1650), 38–9; quoted in Hacking, The Emergence of Probability (2006), 48 54. Wotton, Reflections upon Ancient and Modern Learning (1694), 301. 55.

Fool Me Twice: Fighting the Assault on Science in America by Shawn Lawrence Otto

affirmative action, Albert Einstein, An Inconvenient Truth, anthropic principle, Apollo 11, Berlin Wall, biodiversity loss, Brownian motion, carbon footprint, carbon tax, Cepheid variable, clean water, Climategate, Climatic Research Unit, cognitive dissonance, Columbine, commoditize, cosmological constant, crowdsourcing, cuban missile crisis, Dean Kamen, desegregation, different worldview, disinformation, double helix, Dr. Strangelove, energy security, Exxon Valdez, fudge factor, Garrett Hardin, ghettoisation, global pandemic, Great Leap Forward, Gregor Mendel, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, informal economy, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Large Hadron Collider, Louis Pasteur, luminiferous ether, military-industrial complex, mutually assured destruction, Neil Armstrong, ocean acidification, Richard Feynman, Ronald Reagan, Saturday Night Live, shareholder value, sharing economy, smart grid, stem cell, synthetic biology, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Tragedy of the Commons, transaction costs, University of East Anglia, War on Poverty, white flight, Winter of Discontent, working poor, yellow journalism, zero-sum game

When he turned to astronomers for verification of his theory, he found that almost all of them held the notion that the universe existed in a steady state and there was no motion on a grand scale. So in deference to their observational experience, Einstein adjusted his general theory calculations with a mathematical “fudge factor”—the cosmological constant—that made the universe seem to be steady. Lemaître had independently been working off the same mathematical principles that Einstein had originally laid out, and in 1927 he wrote a dissenting paper in which he argued that the universe must be expanding, and that if it was, the redshifted light from stars was the result of this expansion.

Tesla: Man Out of Time by Margaret Cheney

Charles Lindbergh, Cornelius Vanderbilt, dematerialisation, fudge factor, industrial research laboratory, invention of radio, luminiferous ether, Menlo Park, scientific management, VTOL

The new physics boiled with debates over waves versus particles and about Einstein’s special theory of relativity, which Tesla—with strong cosmic theories of his own—rejected outright. When Einstein’s general theory of relativity was published in 1916, even its creator had been unable to accept fully the dynamic universe that it implied. So disturbed was Einstein by this that he built into his calculations a “fudge factor” that preserved the possibility that the universe might after all prove to be stable and unchanging. To Tesla this was just added proof that the relativists didn’t know what they were talking about. He himself was working on a theory of the universe to be disclosed in good time, and he had long ago propounded (but not published) his own dynamic theory of gravity.

To Explain the World: The Discovery of Modern Science by Steven Weinberg

Albert Einstein, Alfred Russel Wallace, Astronomia nova, Brownian motion, Commentariolus, cosmological constant, dark matter, Dava Sobel, double helix, Edmond Halley, Eratosthenes, Ernest Rutherford, fudge factor, invention of movable type, Isaac Newton, James Watt: steam engine, Johannes Kepler, music of the spheres, On the Revolutions of the Heavenly Spheres, Pierre-Simon Laplace, probability theory / Blaise Pascal / Pierre de Fermat, retrograde motion, Thomas Kuhn: the structure of scientific revolutions

Buchwald and M. Feingold, Newton and the Origin of Civilization (Princeton University Press, Princeton, N.J., 2014). 14. See S. Chandrasekhar, Newton’s Principia for the Common Reader (Clarendon, Oxford, 1995), pp. 472–76; Westfall, Never at Rest, pp. 736–39. 15. R. S. Westfall, “Newton and the Fudge Factor,” Science 179, 751 (1973). 16. See G. E. Smith, “How Newton’s Principia Changed Physics,” in Interpreting Newton: Critical Essays, ed. A. Janiak and E. Schliesser (Cambridge University Press, Cambridge, 2012), pp. 360–95. 17. Voltaire, Philosophical Letters, trans. E. Dilworth (Bobbs-Merrill Educational Publishing, Indianapolis, Ind., 1961), p. 61. 18.

The Rights of the People by David K. Shipler

affirmative action, airport security, computer age, disinformation, facts on the ground, fudge factor, if you build it, they will come, illegal immigration, mandatory minimum, Mikhail Gorbachev, national security letter, Nelson Mandela, Oklahoma City bombing, Panopticon Jeremy Bentham, RFID, risk tolerance, Ronald Reagan, Skype, Thomas L Friedman, union organizing, working poor, zero-sum game

Souter’s key point was not that the Atwater arrest was justifiable—indeed, he and the majority found it full of “gratuitous humiliations imposed by a police officer who was (at best) exercising extremely poor judgment.” But the justices did not think that one policeman’s overreaction should induce the Court to ban all such misdemeanor arrests and thus “mint a new rule of constitutional law.” The fudge factor in the text of the Fourth Amendment is the word “unreasonable,” which presents judges with latitude for indulging their predilections for or against police power. Courts have held that to be reasonable, an arrest must balance two competing factors: its intrusion on personal privacy versus its weight in promoting government interests, as O’Connor noted in her Atwater dissent.

The Age of Spiritual Machines: When Computers Exceed Human Intelligence by Ray Kurzweil

Ada Lovelace, Alan Greenspan, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Alvin Toffler, Any sufficiently advanced technology is indistinguishable from magic, backpropagation, Buckminster Fuller, call centre, cellular automata, Charles Babbage, classic study, combinatorial explosion, complexity theory, computer age, computer vision, Computing Machinery and Intelligence, cosmological constant, cosmological principle, Danny Hillis, double helix, Douglas Hofstadter, Everything should be made as simple as possible, financial engineering, first square of the chessboard / second half of the chessboard, flying shuttle, fudge factor, functional programming, George Gilder, Gödel, Escher, Bach, Hans Moravec, I think there is a world market for maybe five computers, information retrieval, invention of movable type, Isaac Newton, iterative process, Jacquard loom, John Gilmore, John Markoff, John von Neumann, Lao Tzu, Law of Accelerating Returns, mandelbrot fractal, Marshall McLuhan, Menlo Park, natural language processing, Norbert Wiener, optical character recognition, ought to be enough for anybody, pattern recognition, phenotype, punch-card reader, quantum entanglement, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Robert Metcalfe, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, social intelligence, speech recognition, Steven Pinker, Stewart Brand, stochastic process, Stuart Kauffman, technological singularity, Ted Kaczynski, telepresence, the medium is the message, The Soul of a New Machine, There's no reason for any individual to have a computer in his home - Ken Olsen, traveling salesman, Turing machine, Turing test, Whole Earth Review, world market for maybe five computers, Y2K

One theory is that the Universe will continue its expansion forever. Alternatively, if there’s enough stuff, then the force of the Universe’s own gravity will stop the expansion, resulting in a final “big crunch.” Unless, of course, there’s an antigravity force. Or if the “cosmological constant,” Einstein’s “fudge factor,” is big enough. I’ve had to rewrite this paragraph three times over the past several months because the physicists can’t make up their minds. The latest speculation apparently favors indefinite expansion. Personally, I prefer the idea of the Universe closing in again on itself as more aesthetically pleasing.

Big Bang by Simon Singh

Albert Einstein, Albert Michelson, All science is either physics or stamp collecting, Andrew Wiles, anthropic principle, Arthur Eddington, Astronomia nova, Bletchley Park, Boeing 747, Brownian motion, carbon-based life, Cepheid variable, Chance favours the prepared mind, Charles Babbage, Commentariolus, Copley Medal, cosmic abundance, cosmic microwave background, cosmological constant, cosmological principle, dark matter, Dava Sobel, Defenestration of Prague, discovery of penicillin, Dmitri Mendeleev, Eddington experiment, Edmond Halley, Edward Charles Pickering, Eratosthenes, Ernest Rutherford, Erwin Freundlich, Fellow of the Royal Society, Ford Model T, fudge factor, Hans Lippershey, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, heat death of the universe, Henri Poincaré, horn antenna, if you see hoof prints, think horses—not zebras, Index librorum prohibitorum, information security, invention of the telescope, Isaac Newton, Johannes Kepler, John von Neumann, Karl Jansky, Kickstarter, Louis Daguerre, Louis Pasteur, luminiferous ether, Magellanic Cloud, Murray Gell-Mann, music of the spheres, Olbers’ paradox, On the Revolutions of the Heavenly Spheres, Paul Erdős, retrograde motion, Richard Feynman, scientific mainstream, Simon Singh, Stephen Hawking, Strategic Defense Initiative, the scientific method, Thomas Kuhn: the structure of scientific revolutions, time dilation, unbiased observer, Wilhelm Olbers, William of Occam

Later he would call the cosmological constant the greatest blunder of his entire life. As he wrote in a letter to Lemaître: ‘Since I have introduced this term I had always a bad conscience…I am unable to believe that such an ugly thing should be realised in nature.’ Although Einstein was keen to abandon his cosmic fudge factor, cosmologists who still believed in an eternal, static universe were convinced that the cosmological constant was an essential and valid part of general relativity. Even some Big Bang cosmologists had become quite fond of it and were reluctant to lose it. By retaining the cosmological constant and varying its value, they could tweak their theoretical models of the Big Bang and modify the universe’s expansion.

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, behavioural economics, Berlin Wall, Boeing 747, Bonfire of the Vanities, book value, bread and circuses, British Empire, Broken windows theory, business cycle, California gold rush, Cass Sunstein, citation needed, classic study, clean water, cognitive dissonance, colonial rule, Columbine, computer age, Computing Machinery and Intelligence, conceptual framework, confounding variable, 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, Dr. Strangelove, 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, Garrett Hardin, George Santayana, ghettoisation, Gini coefficient, global village, Golden arches theory, Great Leap Forward, Henri Poincaré, Herbert Marcuse, Herman Kahn, high-speed rail, 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, Mikhail Gorbachev, mirror neurons, moral panic, mutually assured destruction, Nelson Mandela, nuclear taboo, Oklahoma City bombing, open economy, Peace of Westphalia, Peter Singer: altruism, power law, 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, Skinner box, Skype, Slavoj Žižek, South China Sea, Stanford marshmallow experiment, Stanford prison experiment, statistical model, stem cell, Steven Levy, Steven Pinker, sunk-cost fallacy, technological determinism, The Bell Curve by Richard Herrnstein and Charles Murray, the long tail, The Wealth of Nations by Adam Smith, theory of mind, Timothy McVeigh, Tragedy of the Commons, transatlantic slave trade, trolley problem, Turing machine, twin studies, ultimatum game, uranium enrichment, Vilfredo Pareto, Walter Mischel, WarGames: Global Thermonuclear War, WikiLeaks, women in the workforce, zero-sum game

A team of statisticians led by Michael Spagat and Neil Johnson found these estimates incredible and discovered that a disproportionate number of the surveyed families lived on major streets and intersections—just the places where bombings and shootings are most likely.69 An improved study conducted by the World Health Organization came up with a figure that was a quarter of the Lancet number, and even that required inflating an original estimate by a fudge factor of 35 percent to compensate for lying, moves, and memory lapses. Their unadjusted figure, around 110,000, is far closer to the battle-death body counts.70 Another team of epidemiologists extrapolated from retrospective surveys of war deaths in thirteen countries to challenge the entire conclusion that battle deaths have declined since the middle of the 20th century.71 Spagat, Mack, and their collaborators have examined them and shown that the estimates are all over the map and are useless for tracking war deaths over time.72 What about the report of 5.4 million deaths (90 percent of them from disease and hunger) in the civil war in the Democratic Republic of the Congo?

…

Myth of reversal in civilian war deaths: Human Security Centre, 2005, p. 75; Goldstein, 2011; Roberts, 2010; White, in press. 67. Civilian deaths in the Civil War: Faust, 2008. 68. Lancet study: Burnham et al., 2006. 69. Bias in epidemiological studies: Human Security Report Project, 2009; Johnson et al., 2008; Spagat, Mack, Cooper, & Kreutz, 2009. 70. Fudge factor: Bohannon, 2008. 71. Retrospective surveys of war deaths: Obermeyer, Murray, & Gakidou, 2008. 72. The trouble with surveys: Spagat et al., 2009. 73. Claim of 5.4 million deaths in DRC: Coghlan et al., 2008. 74. Problems with DRC estimate: Human Security Report Project, 2009. 75. Famine and disease decline during war: Human Security Report Project, 2009. 76.

Aerotropolis by John D. Kasarda, Greg Lindsay

3D printing, air freight, airline deregulation, airport security, Akira Okazaki, Alvin Toffler, An Inconvenient Truth, Asian financial crisis, back-to-the-land, barriers to entry, Bear Stearns, Berlin Wall, big-box store, blood diamond, Boeing 747, book value, borderless world, Boris Johnson, British Empire, business cycle, call centre, carbon footprint, Cesare Marchetti: Marchetti’s constant, Charles Lindbergh, Clayton Christensen, clean tech, cognitive dissonance, commoditize, company town, conceptual framework, credit crunch, David Brooks, David Ricardo: comparative advantage, Deng Xiaoping, deskilling, digital map, disruptive innovation, Dr. Strangelove, Dutch auction, Easter island, edge city, Edward Glaeser, Eyjafjallajökull, failed state, financial engineering, flag carrier, flying shuttle, food miles, Ford Model T, Ford paid five dollars a day, Frank Gehry, fudge factor, fulfillment center, full employment, future of work, Future Shock, General Motors Futurama, gentleman farmer, gentrification, Geoffrey West, Santa Fe Institute, George Gilder, global supply chain, global village, gravity well, Great Leap Forward, Haber-Bosch Process, Hernando de Soto, high-speed rail, hive mind, if you build it, they will come, illegal immigration, inflight wifi, intangible asset, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), intermodal, invention of the telephone, inventory management, invisible hand, Jane Jacobs, Jeff Bezos, Jevons paradox, Joan Didion, Kangaroo Route, Kickstarter, Kiva Systems, knowledge worker, kremlinology, land bank, Lewis Mumford, low cost airline, Marchetti’s constant, Marshall McLuhan, Masdar, mass immigration, McMansion, megacity, megaproject, Menlo Park, microcredit, military-industrial complex, Network effects, New Economic Geography, new economy, New Urbanism, oil shale / tar sands, oil shock, One Laptop per Child (OLPC), peak oil, Pearl River Delta, Peter Calthorpe, Peter Thiel, pets.com, pink-collar, planned obsolescence, pre–internet, RFID, Richard Florida, Ronald Coase, Ronald Reagan, Rubik’s Cube, savings glut, Seaside, Florida, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, SimCity, Skype, smart cities, smart grid, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, spinning jenny, starchitect, stem cell, Steve Jobs, Suez canal 1869, sunk-cost fallacy, supply-chain management, sustainable-tourism, tech worker, telepresence, the built environment, The Chicago School, The Death and Life of Great American Cities, the long tail, The Nature of the Firm, thinkpad, Thomas L Friedman, Thomas Malthus, Tony Hsieh, trade route, transcontinental railway, transit-oriented development, traveling salesman, trickle-down economics, upwardly mobile, urban planning, urban renewal, urban sprawl, vertical integration, Virgin Galactic, walkable city, warehouse robotics, white flight, white picket fence, Yogi Berra, zero-sum game

Heathrow sees more traffic than Britain has citizens. The world’s busiest hub, Atlanta’s Hartsfield-Jackson, has a daytime population larger than Orlando’s and an annual one that would rank it as the twelfth most populous nation on earth. (It’s also the state of Georgia’s largest employer.) All of these figures have a sky-high fudge factor, failing to account for fliers counted twice or more. The media research firm Arbitron made a better measurement a few years ago. It estimated ninety-two million Americans—nearly one in three—had flown at least once in the past twelve months. A clear and bright line separates those of us who fly and those of us who don’t.

Derivatives Markets by David Goldenberg

Black-Scholes formula, Brownian motion, capital asset pricing model, commodity trading advisor, compound rate of return, conceptual framework, correlation coefficient, Credit Default Swap, discounted cash flows, discrete time, diversification, diversified portfolio, en.wikipedia.org, financial engineering, financial innovation, fudge factor, implied volatility, incomplete markets, interest rate derivative, interest rate swap, law of one price, locking in a profit, London Interbank Offered Rate, Louis Bachelier, margin call, market microstructure, martingale, Myron Scholes, Norbert Wiener, Paul Samuelson, price mechanism, random walk, reserve currency, risk free rate, risk/return, riskless arbitrage, Sharpe ratio, short selling, stochastic process, stochastic volatility, time value of money, transaction costs, volatility smile, Wiener process, yield curve, zero-coupon bond, zero-sum game

In order to hedge the option in the Binomial model, we have to have a hedge ratio different from 1, except for Case 1. Further, it generally has to be less than 1.0 in order to hedge the option. When we replicated the option for European Put-Call Parity, we also had a European put option that we used as the ‘fudge’ factor. Here, we only have the stock and the bond. So we have to do better than we did in proving European Put-Call Parity. How can we do better, given that we lost the put option? The answer is that we have been given something we didn’t have for proving European Put-Call Parity. We now get to choose the hedge ratio and make it different from 1.0.

Den of Thieves by James B. Stewart

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", Bear Stearns, Black Monday: stock market crash in 1987, book value, Carl Icahn, corporate raider, creative destruction, deal flow, discounted cash flows, diversified portfolio, fixed income, fudge factor, George Gilder, index arbitrage, Internet Archive, Irwin Jacobs, junk bonds, margin call, Michael Milken, money market fund, Oscar Wyatt, Ponzi scheme, rolodex, Ronald Reagan, Savings and loan crisis, shareholder value, South Sea Bubble, Tax Reform Act of 1986, The Predators' Ball, walking around money, zero-coupon bond

Boesky and many arbitrageurs had always viewed the net capital requirements with thinly veiled contempt. His colleagues Conway and especially Mooradian, who had nearly lost his career after being disci- plined for net capital violations, took the law much more seriously and tried to keep Boesky in compliance. They even went so far as to build in what they termed a "fudge factor" that overstated Boesky's actual leverage in order to try to keep him in bounds. In 1985, however, with the pace of merger deals quickening, and the resulting increase in arbitrage opportunities, it was getting harder and harder to keep Boesky in compliance. Finally, that summer, Conway wrote Boesky an angry memo: "You have continued to show very small regard for our net capital position or the debt covenants under our loan agreements. . . .

The Signal and the Noise: Why So Many Predictions Fail-But Some Don't by Nate Silver

airport security, Alan Greenspan, Alvin Toffler, An Inconvenient Truth, availability heuristic, Bayesian statistics, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, big-box store, Black Monday: stock market crash in 1987, Black Swan, Boeing 747, book value, Broken windows theory, business cycle, buy and hold, Carmen Reinhart, Charles Babbage, classic study, Claude Shannon: information theory, Climategate, Climatic Research Unit, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, computer age, correlation does not imply causation, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, Daniel Kahneman / Amos Tversky, disinformation, diversification, Donald Trump, Edmond Halley, Edward Lorenz: Chaos theory, en.wikipedia.org, equity premium, Eugene Fama: efficient market hypothesis, everywhere but in the productivity statistics, fear of failure, Fellow of the Royal Society, Ford Model T, Freestyle chess, fudge factor, Future Shock, George Akerlof, global pandemic, Goodhart's law, haute cuisine, Henri Poincaré, high batting average, housing crisis, income per capita, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of the printing press, invisible hand, Isaac Newton, James Watt: steam engine, Japanese asset price bubble, John Bogle, John Nash: game theory, John von Neumann, Kenneth Rogoff, knowledge economy, Laplace demon, locking in a profit, Loma Prieta earthquake, market bubble, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, Monroe Doctrine, mortgage debt, Nate Silver, negative equity, new economy, Norbert Wiener, Oklahoma City bombing, PageRank, pattern recognition, pets.com, Phillips curve, Pierre-Simon Laplace, Plato's cave, power law, prediction markets, Productivity paradox, proprietary trading, public intellectual, random walk, Richard Thaler, Robert Shiller, Robert Solow, Rodney Brooks, Ronald Reagan, Saturday Night Live, savings glut, security theater, short selling, SimCity, Skype, statistical model, Steven Pinker, The Great Moderation, The Market for Lemons, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, Timothy McVeigh, too big to fail, transaction costs, transfer pricing, University of East Anglia, Watson beat the top human players on Jeopardy!, Wayback Machine, wikimedia commons

* Meditation helps people achieve this, in part, by encouraging focus on posture and breathing—things that are within our control but which we normally take for granted. * Some of it also represents market making: certain investment firms, like a well-stocked 7-Eleven, hold a lot of inventory and can be counted on to be open for business when no one else is, hoping to make a few pennies at a time for their trouble. * One could imagine that a small fudge factor might be allowed if our probability estimates were close but not exactly the same, since there is some inconvenience associated with betting. * I met Santorum for my New York Times story on the Iowa vote count dispute after the initial tally had shown Romney ahead. Santorum remembered my bet and jokingly asserted that the bet was my motivation for tracking him down.

Across Realtime by Vernor Vinge

fudge factor, gravity well, Isaac Newton, job automation, Magellanic Cloud, means of production, technological singularity, Vernor Vinge, VTOL

Now, at fifty megayears, the day was a little over twenty-five hours long. Rather than change the definition of -he second or the hour, the Korolevs had decreed (just another of their decrees) that the standard day should consist of twenty-four hours plus whatever time it took to complete one rotation. Yel‚n called the extra time the Fudge Factor. Everyone else ailed it the Witching Hour. Wil walked through the Witching Hour, looking for some sign of Marta Korolev. He was still on the Robinson estate, that.vas obvious: as advanced travelers, the Robinsons had plenty of robots. Rescue-day ash had been meticulously cleaned from he stone seats, the fountains, the trees, even the ground.

The Stuff of Thought: Language as a Window Into Human Nature by Steven Pinker

airport security, Albert Einstein, Bob Geldof, classic study, colonial rule, conceptual framework, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Brooks, Douglas Hofstadter, en.wikipedia.org, experimental subject, Ford Model T, fudge factor, George Santayana, language acquisition, Laplace demon, loss aversion, luminiferous ether, Norman Mailer, Philippa Foot, Plato's cave, Richard Feynman, Ronald Reagan, Sapir-Whorf hypothesis, science of happiness, social contagion, social intelligence, speech recognition, stem cell, Steven Pinker, Thomas Bayes, Thorstein Veblen, traffic fines, trolley problem, urban renewal, Yogi Berra

Depending on small differences in how catchy the word is, and on how well-connected, trusted, or charismatic its first adopters are, it may or may not reach the tipping point that would lead it to become entrenched in the community and perpetuated down the generations. 54 This is a way to make sense of the Frequency and Diversity components of the FUDGE factors that Metcalfe suggests are the secrets to a word’s success. So a look at the spread of words and names upends the conventional wisdom of where culture comes from and how it changes. In the twentieth century, a culture came to be thought of as a superorganism that pursues goals, finds meaning, responds to stimuli, and can be the victim of manipulation or the beneficiary of intervention.

Behave: The Biology of Humans at Our Best and Worst by Robert M. Sapolsky

autism spectrum disorder, autonomous vehicles, behavioural economics, Bernie Madoff, biofilm, blood diamond, British Empire, Broken windows theory, Brownian motion, car-free, classic study, clean water, cognitive dissonance, cognitive load, corporate personhood, corporate social responsibility, Daniel Kahneman / Amos Tversky, delayed gratification, desegregation, different worldview, domesticated silver fox, double helix, Drosophila, Edward Snowden, en.wikipedia.org, epigenetics, Flynn Effect, framing effect, fudge factor, George Santayana, global pandemic, Golden arches theory, Great Leap Forward, hiring and firing, illegal immigration, impulse control, income inequality, intentional community, John von Neumann, Loma Prieta earthquake, long peace, longitudinal study, loss aversion, Mahatma Gandhi, meta-analysis, microaggression, mirror neurons, Mohammed Bouazizi, Monkeys Reject Unequal Pay, mouse model, mutually assured destruction, Nelson Mandela, Network effects, nocebo, out of africa, Peter Singer: altruism, phenotype, Philippa Foot, placebo effect, publication bias, RAND corporation, risk tolerance, Rosa Parks, selective serotonin reuptake inhibitor (SSRI), self-driving car, Silicon Valley, Skinner box, social contagion, social distancing, social intelligence, Stanford marshmallow experiment, Stanford prison experiment, stem cell, Steven Pinker, strikebreaker, theory of mind, Tragedy of the Commons, transatlantic slave trade, traveling salesman, trickle-down economics, trolley problem, twin studies, ultimatum game, Walter Mischel, wikimedia commons, zero-sum game, zoonotic diseases

When deaths are expressed as a percentage of total population, World War II is the only twentieth-century event cracking the top ten, behind An Lushan, the Mongol conquests, the Mideast slave trade, the fall of the Ming dynasty, the fall of Rome, the deaths caused by Tamerlane, the annihilation of Native Americans by Europeans, and the Atlantic slave trade. Critics have questioned this—“Hey, stop using fudge factors to somehow make World War II’s 55 million dead less than the fall of Rome’s 8 million.” After all, 9/11’s murders would not have evoked only half as much terror if America had 600 million instead of 300 million citizens. But Pinker’s analysis is appropriate, and analyzing rates of events is how you discover that today’s London is much safer than was Dickens’s or that some hunter-gatherer groups have homicide rates that match Detroit’s.

Networks, Crowds, and Markets: Reasoning About a Highly Connected World by David Easley, Jon Kleinberg

Albert Einstein, AltaVista, AOL-Time Warner, Apollo 13, classic study, clean water, conceptual framework, Daniel Kahneman / Amos Tversky, Douglas Hofstadter, Dutch auction, Erdős number, experimental subject, first-price auction, fudge factor, Garrett Hardin, George Akerlof, Gerard Salton, Gerard Salton, Gödel, Escher, Bach, incomplete markets, information asymmetry, information retrieval, John Nash: game theory, Kenneth Arrow, longitudinal study, market clearing, market microstructure, moral hazard, Nash equilibrium, Network effects, Pareto efficiency, Paul Erdős, planetary scale, power law, prediction markets, price anchoring, price mechanism, prisoner's dilemma, random walk, recommendation engine, Richard Thaler, Ronald Coase, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, seminal paper, Simon Singh, slashdot, social contagion, social web, Steve Jobs, Steve Jurvetson, stochastic process, Ted Nelson, the long tail, The Market for Lemons, the strength of weak ties, The Wisdom of Crowds, trade route, Tragedy of the Commons, transaction costs, two and twenty, ultimatum game, Vannevar Bush, Vickrey auction, Vilfredo Pareto, Yogi Berra, zero-sum game

And indeed, it suffers from exactly this problem — advertisers can sometimes occupy high slots without generating much money for the search engine. The role of ad quality. When Google developed its system for advertising, it addressed this problem as follows. For each ad submitted by an advertiser j, they determine an estimated quality factor qj. This is intended as a “fudge factor” on the clickthrough rate: if advertiser j appears in slot i, then the clickthrough rate is estimated to be not ri but the product qjri. The introduction of ad quality is simply a generalization of the model we’ve been studying all along: in particular, if we assume that all factors qi are equal to 1, then we get back the model that we’ve been using thus far in the chapter.

The Prize: The Epic Quest for Oil, Money & Power by Daniel Yergin

anti-communist, Ascot racecourse, Ayatollah Khomeini, bank run, Berlin Wall, book value, British Empire, Carl Icahn, colonial exploitation, Columbine, continuation of politics by other means, cuban missile crisis, disinformation, do-ocracy, energy security, European colonialism, Exxon Valdez, financial independence, fudge factor, geopolitical risk, guns versus butter model, Ida Tarbell, informal economy, It's morning again in America, joint-stock company, junk bonds, land reform, liberal capitalism, managed futures, megacity, Michael Milken, Mikhail Gorbachev, Monroe Doctrine, new economy, North Sea oil, oil rush, oil shale / tar sands, oil shock, old-boy network, postnationalism / post nation state, price stability, RAND corporation, rent-seeking, Ronald Reagan, shareholder value, stock buybacks, Suez canal 1869, Suez crisis 1956, Thomas Malthus, tontine, vertical integration, Yom Kippur War

For instance, depending on the accounting formula that was chosen, 25 percent of the Kuwait Oil Company could be worth anywhere from sixty million to one billion dollars. Finally, in that case, the two sides came together by inventing a new accounting concept, "updated book value," which included inflation and large fudge factors. And in October 1972 a "participation agreement" was finally reached between the Gulf states and the companies. It provided for an immediate 25 percent participation share, rising to 51 percent by 1983. But, despite all the OPEC endorsements, the application of the agreement was less popular in the rest of OPEC than Yamani hoped.