tail risk

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Fault Lines: How Hidden Fractures Still Threaten the World Economy by Raghuram Rajan

"World Economic Forum" Davos, accounting loophole / creative accounting, Alan Greenspan, Andrei Shleifer, Asian financial crisis, asset-backed security, assortative mating, bank run, barriers to entry, Bear Stearns, behavioural economics, Bernie Madoff, Bretton Woods, business climate, business cycle, carbon tax, Clayton Christensen, clean water, collapse of Lehman Brothers, collateralized debt obligation, colonial rule, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency manipulation / currency intervention, currency risk, diversification, Edward Glaeser, financial innovation, fixed income, floating exchange rates, full employment, Glass-Steagall Act, global supply chain, Goldman Sachs: Vampire Squid, Greenspan put, illegal immigration, implied volatility, income inequality, index fund, interest rate swap, Joseph Schumpeter, Kaizen: continuous improvement, Kenneth Rogoff, knowledge worker, labor-force participation, Long Term Capital Management, longitudinal study, low interest rates, machine readable, market bubble, Martin Wolf, medical malpractice, microcredit, money market fund, moral hazard, new economy, Northern Rock, offshore financial centre, open economy, Phillips curve, price stability, profit motive, proprietary trading, Real Time Gross Settlement, Richard Florida, Richard Thaler, risk tolerance, Robert Shiller, Ronald Reagan, Savings and loan crisis, school vouchers, seminal paper, short selling, sovereign wealth fund, tail risk, The Great Moderation, the payments system, The Wealth of Nations by Adam Smith, too big to fail, upwardly mobile, Vanguard fund, women in the workforce, World Values Survey

This will give the trader a longer horizon, creating some uncertainty about whether any tail risk she takes could actually hit before her bonus is paid, thus giving her greater incentive to avoid it. Of course, such a compensation structure will be effective only if a trader knowingly takes tail risks, not if she is unintentionally guided into taking them. Crude limits on the positions individual traders or units are allowed to take, and mandatory diversification requirements, may also be necessary, not so much to prevent tail risk taking but to minimize the loss if it does occur. Incentives at the Top The proposals above to manage tail risks presume that top management wants to curb such risk taking.

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But this is precisely how we would expect the market to behave if it believed the banks were taking on subsidized tail risk. Thus far, as we have moved through the corporate hierarchy, from trader to risk manager to CEO to corporate board to shareholder, we have found little concern anywhere about the tail risks that were building up, especially in the aggressive banks. Many of the actors—traders, management, and shareholders—typically focused on the advantages of taking the tail risk. In insurance parlance, they would get a share of the premiums that flowed in while the going was good, and they would be protected by limited liability from having to make massive payouts if the extreme risk hit.

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Summary and Conclusion The problem of tail risk taking is particularly acute in the modern financial system, where bankers are under tremendous pressure to produce risk-adjusted performance. Few can deliver superior performance on a regular basis, but precisely for this reason, the rewards for those who can are enormous. The pressure on the second-rate to take tail risk, thus allowing them to masquerade as superstars for a while, is intense. The market should theoretically encourage good risk management and penalize excessive risk taking. But tail risks are difficult to control for two reasons.

Beyond Diversification: What Every Investor Needs to Know About Asset Allocation by Sebastien Page

Andrei Shleifer, asset allocation, backtesting, Bernie Madoff, bitcoin, Black Swan, Bob Litterman, book value, business cycle, buy and hold, Cal Newport, capital asset pricing model, commodity super cycle, coronavirus, corporate governance, COVID-19, cryptocurrency, currency risk, discounted cash flows, diversification, diversified portfolio, en.wikipedia.org, equity risk premium, Eugene Fama: efficient market hypothesis, fixed income, future of work, Future Shock, G4S, global macro, implied volatility, index fund, information asymmetry, iterative process, loss aversion, low interest rates, market friction, mental accounting, merger arbitrage, oil shock, passive investing, prediction markets, publication bias, quantitative easing, quantitative trading / quantitative finance, random walk, reserve currency, Richard Feynman, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, robo advisor, seminal paper, shareholder value, Sharpe ratio, sovereign wealth fund, stochastic process, stochastic volatility, stocks for the long run, systematic bias, systematic trading, tail risk, transaction costs, TSMC, value at risk, yield curve, zero-coupon bond, zero-sum game

We can also use forward- looking scenarios. We can combine volatility and tail risk directly into one objective function. To do so, we can use the same approach as we did for the risk regimes above, but replace the regime-specific aversion parameters with aversions to volatility and tail risk: Expected return – [risk aversion 1 × volatility (quiet) + risk aversion 2 × tail risk] Again, tail risk can be measured as CVaR, VaR, probability of loss, 2008 scenario, etc. It can be probability-weighted within the objective function. Essentially, every tail-risk measure we discussed in the risk forecasting section can be used, and beyond.

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There are several other modified versions of mean-variance optimization that account for nonnormal (non-Gaussian) higher moments, in particular fat tails.3 For example, we can replace volatility with a measure of tail risk. In Chapter 10 we discussed conditional value at risk (CVaR), a measure of expected loss during market sell-offs. If we use CVaR as our measure of tail risk, we can modify mean variance to solve for the weights that maximize4 – risk aversion × CVaR CVaR can be replaced with any tail-risk measure of choice, such as probability of a loss greater than –10%, value at risk (VaR), etc. We can also use tail-risk constraints. For example, suppose we don’t want CVaR to go below –10%. We can define the optimization problem as Expected return – risk aversion × volatility subject to CVaR <–10% In this framework, any constraint should work.

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Rowe Price, 191 Asset Allocation Committee, xii capital markets assumptions approach at, 37–38 and global equity markets forecasts, 13–14 portfolios/products managed by, 248 scenario analysis at, 157–158, 163 and tactical asset allocation, 57–58 Target Date Fund series of, 250 Taborsky, Mark, 174 Tactical asset allocation (TAA), 45–59 best valuation signal for, 52–56 forecast horizons for, 111 (See also Longer-term risk forecasting) global, 182 and macro dashboards, 67 in practice, 46–52 and relative valuation between stocks and bonds, 56–59 Tail dependence, 126 Tail risk: combining volatility and, 206–207 and managed volatility, 99, 101 in optimization problem, 206 Tail-risk estimation: fat tails, 147–157 scenario analysis, 157–167 Tail-risk hedging, 135 Tail-risk-aware analytics, 135–136 Tails: and correlation asymmetries, 123 and correlations, 124–126, 134 and kurtosis, 118 and skewness, 118 (See also Fat tails) Taleb, Nassim Nicholas, 8–9, 148, 150, 153 Target allocation portfolios, 253–261 conservative income, 253–255 diversified global portfolio, 257–259 diversified income, 255–257 Target allocation portfolios (continued): growth portfolio, 261–261 specialized portfolios, 261–262 Target volatility portfolios, 261–263 Target-date funds (TDFs), 186, 187, 190–195, 248 Target-date portfolios, 248–253 Technology Select Sector SPDR ETF, 242 Thompson, Toby, 94 Three-factor model, 22 Three-sigma days, 94–95 Thurston, David, 218–219 Time horizon(s): and bond returns, 16 and building block valuation model, 33 in CAPM, 14 and CAPM forecasts, 21 for cash return, 19 and correlation forecasting, 140–143 counterweight effect at, 41–42 differing between momentum and value investing, 180 for fixed income asset classes, 39–40 macro factors for short term tactical investments, 63–66 with managed volatility, 107 and momentum, 71–73, 75–76 and persistence of risk measures, 113–117 in tactical asset allocation, 57 and volatility, 113–114 within-horizon and end-of-horizon risk, 168–170 Time series analyses, 159 Time series forecasts, 31 Tracking error, 210 Treasury Inflation-Protected Securities (TIPS), 186–188 Treynor, Jack, 6 Turing Pharmaceuticals, 238 Turkington, David, 156, 211, 225 “215 Years of Global Multi-Asset Momentum: 1800–2014” (Geczy and Samonov), 71 Tzitzouris, Jim, 186, 187, 189–192, 233 Unstable portfolios, 207–210 Uppal, Raman, 211 US Treasuries: impact of QE on, 17 as safe-haven class, 161 stock correlations with, 132 volatility persistence for, 114 US Treasury bills, 11–12, 19 US Treasury bonds, 11 Utility, 192, 198 Utility function: approximating, 203–207 inflection points in, 201–203 Utility maximization, 199–203 Utility theory, 199 Valeant Pharmaceuticals, 238 Valuation, 25–42, 267 and bond future returns, 39–42 building block model for, 28–39 and CAPM model, 12 and equity risk premium, 14 fundamental analysis, 37–39 in market risk premium determination, 21 and momentum, 61, 70–82 relative, between stocks and bonds, 27–28 shorter-term (see Shorter-term valuation signals) of stocks, P/E ratio vs.

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

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

The same features are observed for carry trading and harvesting illiquidity premia. • The rewards for tail risks appear time varying—extra high in the aftermath of an adverse event. 19.1 INTRODUCTION The last underlying factor I focus on actually involves several interrelated sources of risk and return, which I call together “tail risks” (see cube). I already discussed the volatility selling strategy in Chapter 15, focusing on equity index options. Here I extend the analysis beyond option trading and analyze aspects of tail risks, or higher moment risks, other than volatility. Chapter 15 concluded that pure volatility risk may not be well rewarded because, while index option selling has been profitable, single-stock option selling has not.

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This unorthodox but intriguing idea is related to the “keeping up with the Joneses” utility function (see Note 9 in Chapter 5) and could explain the “Easterlin paradox” that average happiness as measured by surveys has not increased over decades-long periods when material wealth has grown many-fold. 19.6 TIME-VARYING PREMIA FOR TAIL RISK EXPOSURES Since the literature on tail risk or higher moment premia is young and limited data histories are available, it is hard to say much about the time-varying nature of these premia. Tail risks are diverse, but heightened volatility and correlation disproportionately occur in bad times (recessions, financial crises), so these factors clearly warrant high-risk premia. In principle, these premia could be constant over time but empirical evidence suggests that they are not.

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14.5 MOMENTUM IN OTHER ASSET CLASSES 14.6 NOTES Chapter 15 - Volatility selling (on equity indices) 15.1 INTRODUCTION 15.2 HISTORICAL PERFORMANCE OF VOLATILITY-TRADING STRATEGIES 15.3 TWEAKS/REFINEMENTS 15.4 THE REASONS VOLATILITY SELLING IS PROFITABLE 15.5 OTHER ASSETS 15.6 NOTES Chapter 16 - Growth factor and growth premium 16.1 INTRODUCTION TO UNDERLYING FACTORS IN CHAPTERS 16–19 16.2 INTRODUCTION TO THE GROWTH FACTOR 16.3 THEORY AND EVIDENCE ON GROWTH 16.4 ASSET MARKET RELATIONS 16.5 TIME-VARYING GROWTH PREMIUM 16.6 NOTES Chapter 17 - Inflation factor and inflation premium 17.1 INTRODUCTION 17.2 INFLATION PROCESS—HISTORY, DETERMINANTS, EXPECTATIONS 17.3 INFLATION SENSITIVITY OF MAJOR ASSET CLASSES AND THE INFLATION PREMIUM 17.4 TIME-VARYING INFLATION PREMIUM 17.5 NOTES Chapter 18 - Liquidity factor and illiquidity premium 18.1 INTRODUCTION 18.2 FACTOR HISTORY: HOW DOES LIQUIDITY ITSELF VARY OVER TIME? 18.3 HISTORICAL EVIDENCE ON AVERAGE LIQUIDITY-RELATED PREMIA 18.4 TIME-VARYING ILLIQUIDITY PREMIA 18.5 NOTE Chapter 19 - Tail risks (volatility, correlation, skewness) 19.1 INTRODUCTION 19.2 FACTOR HISTORY 19.3 HISTORICAL EVIDENCE ON AVERAGE ASSET RETURNS VS. VOLATILITY AND CORRELATION 19.4 THEORY AND EVIDENCE ON THE SKEWNESS PREMIUM 19.5 VERDICT ON WHY HIGH-VOLATILITY ASSETS FARE SO POORLY 19.6 TIME-VARYING PREMIA FOR TAIL RISK EXPOSURES 19.7 NOTES Part III - Back to broader themes Chapter 20 - Endogenous return and risk: Feedback effects on expected returns 20.1 FEEDBACK LOOPS ON THE DIRECTION OF RISKY ASSETS 20.2 FEEDBACK LOOPS ON LESS DIRECTIONAL POSITIONS 20.3 AGENDA FOR MARKET-TIMERS AND RESEARCHERS 20.4 NOTES Chapter 21 - Forward-looking measures of asset returns 21.1 POPULAR VALUE AND CARRY INDICATORS AND THEIR PITFALLS 21.2 BUILDING BLOCKS OF EXPECTED RETURNS 21.3 NOTES Chapter 22 - Interpreting carry or non-zero yield spreads 22.1 INTRODUCTION 22.2 FUTURE EXCESS RETURNS OR MARKET EXPECTATIONS?

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

anti-fragile, availability heuristic, behavioural economics, Benoit Mandelbrot, Bernie Madoff, Black Swan, Brownian motion, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, cellular automata, Claude Shannon: information theory, cognitive dissonance, complexity theory, data science, David Graeber, disintermediation, Donald Trump, Edward Thorp, equity premium, fake news, financial independence, information asymmetry, invisible hand, knowledge economy, loss aversion, mandelbrot fractal, Mark Spitznagel, mental accounting, microbiome, mirror neurons, moral hazard, Murray Gell-Mann, offshore financial centre, p-value, Paradox of Choice, Paul Samuelson, Ponzi scheme, power law, precautionary principle, price mechanism, principal–agent problem, public intellectual, Ralph Nader, random walk, rent-seeking, Richard Feynman, Richard Thaler, Ronald Coase, Ronald Reagan, Rory Sutherland, Rupert Read, Silicon Valley, Social Justice Warrior, Steven Pinker, stochastic process, survivorship bias, systematic bias, tail risk, TED Talk, The Nature of the Firm, Tragedy of the Commons, transaction costs, urban planning, Yogi Berra

“The difference between successful people and really successful people is that really successful people say no to almost everything,” he said. Likewise our wiring might be adapted to “say no” to tail risk. For there are a zillion ways to make money without taking tail risk. There are a zillion ways to solve problems (say, feed the world) without complicated technologies that entail fragility and an unknown possibility of tail blowup. Whenever I hear someone saying “we need to take (tail) risks” I know it is not coming from a surviving practitioner but from a finance academic or a banker—the latter, we saw, almost always blows up, usually with other people’s money.

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This is why I have been against the state dictating to us what we “should” be doing: only evolution knows if the “wrong” thing is really wrong, provided there is skin in the game to allow for selection. WHAT IS RELIGION ABOUT? It is therefore my opinion that religion exists to enforce tail risk management across generations, as its binary and unconditional rules are easy to teach and enforce. We have survived in spite of tail risks; our survival cannot be that random. Recall that skin in the game means that you do not pay attention to what people say, only to what they do, and to how much of their necks they are putting on the line. Let survival work its wonders.

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In my war with the Monsanto machine, the advocates of genetically modified organisms (transgenics) kept countering me with benefit analyses (which were often bogus and doctored up), not tail risk analyses for repeated exposures. Psychologists determine our “paranoia” or “risk aversion” by subjecting a person to a single experiment—then declare that humans are rationally challenged, as there is an innate tendency to “overestimate” small probabilities. They manage to believe that their subjects will never ever again take any personal tail risk! Recall from the chapter on inequality that academics in social science are … dynamically challenged. Nobody could see the grandmother-obvious inconsistency of such behavior with our ingrained daily life logic, which is remarkably more rigorous.

Chaos Kings: How Wall Street Traders Make Billions in the New Age of Crisis by Scott Patterson

"World Economic Forum" Davos, 2021 United States Capitol attack, 4chan, Alan Greenspan, Albert Einstein, asset allocation, backtesting, Bear Stearns, beat the dealer, behavioural economics, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, bitcoin, Bitcoin "FTX", Black Lives Matter, Black Monday: stock market crash in 1987, Black Swan, Black Swan Protection Protocol, Black-Scholes formula, blockchain, Bob Litterman, Boris Johnson, Brownian motion, butterfly effect, carbon footprint, carbon tax, Carl Icahn, centre right, clean tech, clean water, collapse of Lehman Brothers, Colonization of Mars, commodity super cycle, complexity theory, contact tracing, coronavirus, correlation does not imply causation, COVID-19, Credit Default Swap, cryptocurrency, Daniel Kahneman / Amos Tversky, decarbonisation, disinformation, diversification, Donald Trump, Doomsday Clock, Edward Lloyd's coffeehouse, effective altruism, Elliott wave, Elon Musk, energy transition, Eugene Fama: efficient market hypothesis, Extinction Rebellion, fear index, financial engineering, fixed income, Flash crash, Gail Bradbrook, George Floyd, global pandemic, global supply chain, Gordon Gekko, Greenspan put, Greta Thunberg, hindsight bias, index fund, interest rate derivative, Intergovernmental Panel on Climate Change (IPCC), Jeff Bezos, Jeffrey Epstein, Joan Didion, John von Neumann, junk bonds, Just-in-time delivery, lockdown, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, Mark Spitznagel, Mark Zuckerberg, market fundamentalism, mass immigration, megacity, Mikhail Gorbachev, Mohammed Bouazizi, money market fund, moral hazard, Murray Gell-Mann, Nick Bostrom, off-the-grid, panic early, Pershing Square Capital Management, Peter Singer: altruism, Ponzi scheme, power law, precautionary principle, prediction markets, proprietary trading, public intellectual, QAnon, quantitative easing, quantitative hedge fund, quantitative trading / quantitative finance, Ralph Nader, Ralph Nelson Elliott, random walk, Renaissance Technologies, rewilding, Richard Thaler, risk/return, road to serfdom, Ronald Reagan, Ronald Reagan: Tear down this wall, Rory Sutherland, Rupert Read, Sam Bankman-Fried, Silicon Valley, six sigma, smart contracts, social distancing, sovereign wealth fund, statistical arbitrage, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, systematic trading, tail risk, technoutopianism, The Chicago School, The Great Moderation, the scientific method, too big to fail, transaction costs, University of East Anglia, value at risk, Vanguard fund, We are as Gods, Whole Earth Catalog

In fact, it was a dreaded line item, with no expected return for most years, that would make their performance look worse—even if it might dramatically improve their performance in a bad year. More often than not, the prospective investors didn’t even understand what the fund did. “We do tail-risk hedging,” Spitznagel would tell them across the expanse of a dark oak conference table. “The Black Swan Protection Protocol Fund buys far out-of-the-money options that produce explosive returns in crashes, fat tails…” Tail risk? Options? Black Swans? Blank stares. It was as if they were speaking a foreign language. “I had to sit and explain this to people who run hundreds of billions of dollars,” Yarckin recalled.

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Few wanted to stray from the pack into a strategy that seemed experimental. If Universa could turn CalPERS into a client, perhaps the precedent would give other pension funds the thumbs-up that tail-risk strategies were now kosher. It was potentially transformative. Lagnado’s boss, Ted Eliopoulos, CalPERS’s chief investment officer, had recently seen a talk by Taleb and grown intrigued by the notion of making the fund’s portfolio more resilient to Black Swans with a tail-risk strategy. There was a common belief in the pension fund world that the strategies were too expensive and couldn’t be scaled to fit their massive portfolios. While you might make money in a crash, the bleeding during good times wasn’t worth it.

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PS - I have no interest in Asness, not even AQR, but they can’t get away w/nonsensical claims abt tail risk. @Clifford Asness Getting famous and rich for saying ‘bad shit happens sometimes’ and then screaming ‘see’ when it luckily does soon after, even though you’ve lost all the money many times, and then using that pulpit to slander and abuse people is just gross. Just my opinion. @nntaleb For the general public watching the road rage of Mr. Asness who misreplied to my last post: The claims [sic] by AQR is: tail risk is not needed by funds because there are ways to do it better. As we are finding out: the performance of AQR doesn’t show it.

The Invisible Hands: Top Hedge Fund Traders on Bubbles, Crashes, and Real Money by Steven Drobny

Albert Einstein, AOL-Time Warner, Asian financial crisis, asset allocation, asset-backed security, backtesting, banking crisis, Bear Stearns, Bernie Madoff, Black Swan, bond market vigilante , book value, Bretton Woods, BRICs, British Empire, business cycle, business process, buy and hold, capital asset pricing model, capital controls, central bank independence, collateralized debt obligation, commoditize, commodity super cycle, commodity trading advisor, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency peg, debt deflation, diversification, diversified portfolio, equity premium, equity risk premium, family office, fiat currency, fixed income, follow your passion, full employment, George Santayana, global macro, Greenspan put, Hyman Minsky, implied volatility, index fund, inflation targeting, interest rate swap, inventory management, inverted yield curve, invisible hand, junk bonds, Kickstarter, London Interbank Offered Rate, Long Term Capital Management, low interest rates, market bubble, market fundamentalism, market microstructure, Minsky moment, moral hazard, Myron Scholes, North Sea oil, open economy, peak oil, pension reform, Ponzi scheme, prediction markets, price discovery process, price stability, private sector deleveraging, profit motive, proprietary trading, purchasing power parity, quantitative easing, random walk, Reminiscences of a Stock Operator, reserve currency, risk free rate, risk tolerance, risk-adjusted returns, risk/return, savings glut, selection bias, Sharpe ratio, short selling, SoftBank, sovereign wealth fund, special drawing rights, statistical arbitrage, stochastic volatility, stocks for the long run, stocks for the long term, survivorship bias, tail risk, The Great Moderation, Thomas Bayes, time value of money, too big to fail, Tragedy of the Commons, transaction costs, two and twenty, unbiased observer, value at risk, Vanguard fund, yield curve, zero-sum game

Are there risks specific to commodity markets that do not exist in equities? Commodity markets have much larger tail risk because spot shortages and outages can occur in the face of rather inelastic demand. Heating oil or natural gas especially can exhibit this phenomenon at times. Significant changes in the demand profile of a commodity rarely occur, unless there is some step change, similar to the one in the corn market when ethanol was introduced as an energy option. On the supply side, though, tail risk is inherent, usually resulting from an outage of some kind. In equities, however, the tail tends to be different because incremental supply can be brought online via issuance.

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I would keep a very sharp eye on liquidity, so all this would depend on the size of my portfolio and my ability to keep the majority of my assets in liquid investments. The lesson of 2008 is that liquidity is all that matters when it ceases to exist. Therefore, real money managers need to reorient their portfolios to avoid large tail risks. Looking ahead at potential tail risks, I believe that a developed market sovereign debt crisis looms stemming from the inability of a major sovereign to completely fulfill its commitments. I am talking about a G3 nation. Wow, that would be a shock! In keeping with the pension discussion, what would be your base currency?

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Big drawdowns and volatility matter. Focusing on return targets misses the damage to performance caused by large drawdowns and high volatility. Portfolios should be constructed such that extreme worst-case scenarios are accounted for and dealt with in the investment process, either through the use of overlays, hedges to cut off tail risk, or less aggressive asset allocation with truly diversifying exposures. 2. Look forward, not backward. Historical asset class or fund performance is not a good indicator of the future. Real money portfolios should not be constructed to fit the recent past no matter how comfortable that may be. The macro environment matters greatly and should be considered first and foremost when constructing portfolios. 3.

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems by Irene Aldridge

algorithmic trading, asset allocation, asset-backed security, automated trading system, backtesting, Black Swan, Brownian motion, business cycle, business process, buy and hold, capital asset pricing model, centralized clearinghouse, collapse of Lehman Brothers, collateralized debt obligation, collective bargaining, computerized trading, diversification, equity premium, fault tolerance, financial engineering, financial intermediation, fixed income, global macro, high net worth, implied volatility, index arbitrage, information asymmetry, interest rate swap, inventory management, Jim Simons, law of one price, Long Term Capital Management, Louis Bachelier, machine readable, margin call, market friction, market microstructure, martingale, Myron Scholes, New Journalism, p-value, paper trading, performance metric, Performance of Mutual Funds in the Period, pneumatic tube, profit motive, proprietary trading, purchasing power parity, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, short selling, Small Order Execution System, statistical arbitrage, statistical model, stochastic process, stochastic volatility, systematic trading, tail risk, trade route, transaction costs, value at risk, yield curve, zero-sum game

While these three metrics remain popular, they do not take into account the tail risk of extreme adverse returns. Brooks and Kat (2002), Mahdavi (2004), and Sharma (2004), for example, present cases against using Sharpe ratios on non-normally distributed returns. The researchers’ primary concerns surrounding the use of the Sharpe ratio are linked to the use of derivative instruments that result in an asymmetric return distribution and fat tails. Ignoring deviations from normality may underestimate risk and overestimate performance. New performance measures have been subsequently developed to capture the tail risk inherent in the returns of most trading strategies.

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A natural extension of the Sharpe ratio is to change the measure of risk from standard deviation to a drawdown-based methodology in an effort to 56 HIGH-FREQUENCY TRADING capture the tail risk of the strategies. The Calmar ratio, Sterling ratio, and Burke ratio do precisely that. The Calmar ratio, developed by Young (1991), uses the maximum drawdown as the measure of volatility. The Sterling ratio, first described by Kestner (1996), uses the average drawdown as a proxy for volatility. Finally, the Burke ratio, developed by Burke (1994), uses the standard deviation of maximum drawdowns as a volatility metric. In addition to ignoring the tail risk, the Sharpe ratio is also frequently criticized for including positive returns in the volatility measure.

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Volatility of returns measures the dispersion of returns around the average return; it is most often computed as the standard deviation of returns. 49 50 HIGH-FREQUENCY TRADING Volatility, or standard deviation, is often taken to proxy risk. Standard deviation, however, summarizes the average deviation from the mean and does not account for the risk of extreme negative effects that can wipe out years of performance. A measure of tail risk popular among practitioners that documents the maximum severity of losses observed in historical data is maximum drawdown. Maximum drawdown records the lowest peak-to-trough return from the last global maximum to the minimum that occurred prior to the next global maximum that supersedes the last global maximum.

Safe Haven: Investing for Financial Storms by Mark Spitznagel

Albert Einstein, Antoine Gombaud: Chevalier de Méré, asset allocation, behavioural economics, bitcoin, Black Swan, blockchain, book value, Brownian motion, Buckminster Fuller, cognitive dissonance, commodity trading advisor, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, delayed gratification, diversification, diversified portfolio, Edward Thorp, fiat currency, financial engineering, Fractional reserve banking, global macro, Henri Poincaré, hindsight bias, Long Term Capital Management, Mark Spitznagel, Paul Samuelson, phenotype, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, rent-seeking, Richard Feynman, risk free rate, risk-adjusted returns, Schrödinger's Cat, Sharpe ratio, spice trade, Steve Jobs, tail risk, the scientific method, transaction costs, value at risk, yield curve, zero-sum game

., it should raise your wealth), and to do that it needs to mitigate the risks that matter, not the risks that don't. It was the birth of tail risk hedging as an investable asset class. Tail risk hedging removed the effect of the nasty Black Swan on portfolios; cost‐effective tail risk hedging obliterated all the other forms of risk mitigation. Accordingly, the idea grew on people and a new category was born. This led to a legion of imitators—those very same mutua muli persons who had previously been fooled by modern finance tools, finding a new thing to sell. Universa proved the following: not only is there no substitute to tail risk hedging, but, when it comes to tail risk hedging, simply—as per the boast in the Porsche advertisement—there is no substitute.

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Indeed the investment world is populated by analysts who, while using patently wrong mathematics, managed to look good and cosmetically sophisticated but eventually harm their clients in the long run. Why? Because, simply, it is OPM (other people's money) they are risking while the returns are theirs—again, absence of skin in the game. Steady returns (continuous ratification) comes along with hiding tail risks. Banks lost more money in two episodes, 1982 and 2008, than they made in the history of banking—but managers are still rich. They claimed that the standard models were showing low risk when they were sitting on barrels of dynamite—so we needed to destroy these models as tools of deception. This risk transfer is visible in all business activities: corporations end up obeying the financial analyst dictum to avoid tail insurance: in their eyes, a company that can withstand storms can be inferior to one that is fragile to the next slight downturn or rise in interest rates, if the latter's earning per share exceed the former's by a fraction of a penny!

Austerity: The History of a Dangerous Idea by Mark Blyth

"there is no alternative" (TINA), accounting loophole / creative accounting, Alan Greenspan, balance sheet recession, bank run, banking crisis, Bear Stearns, Black Swan, book value, Bretton Woods, business cycle, buy and hold, capital controls, Carmen Reinhart, Celtic Tiger, central bank independence, centre right, collateralized debt obligation, correlation does not imply causation, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency peg, debt deflation, deindustrialization, disintermediation, diversification, en.wikipedia.org, ending welfare as we know it, Eugene Fama: efficient market hypothesis, eurozone crisis, financial engineering, financial repression, fixed income, floating exchange rates, Fractional reserve banking, full employment, German hyperinflation, Gini coefficient, global reserve currency, Greenspan put, Growth in a Time of Debt, high-speed rail, Hyman Minsky, income inequality, information asymmetry, interest rate swap, invisible hand, Irish property bubble, Joseph Schumpeter, Kenneth Rogoff, liberal capitalism, liquidationism / Banker’s doctrine / the Treasury view, Long Term Capital Management, low interest rates, market bubble, market clearing, Martin Wolf, Minsky moment, money market fund, moral hazard, mortgage debt, mortgage tax deduction, Occupy movement, offshore financial centre, paradox of thrift, Philip Mirowski, Phillips curve, Post-Keynesian economics, price stability, quantitative easing, rent-seeking, reserve currency, road to serfdom, Robert Solow, savings glut, short selling, structural adjustment programs, tail risk, The Great Moderation, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, Tobin tax, too big to fail, Two Sigma, unorthodox policies, value at risk, Washington Consensus, zero-sum game

Rather, we piece together how the debt increase was generated by the implosion of the US financial sector and how this impacted sovereigns from the United States to the Eurozone and beyond. To explain this I stress how the interaction of the repo (sale and repurchase) markets, complex instruments, tail risks, and faulty thinking combined to give us the problem of too big to fail. It takes us from the origins of the crisis in the run on the US repo market in September 2008 to the transmission of this US-based crisis to the Eurozone, noting along the way how a banking crisis was deftly, and most politically, turned into a public-sector crisis and how much it all cost.34 Chapter 3, “Europe: Too Big to Bail: The Politics of Permanent Austerity,” analyzes how the private debt generated by the US banking sector was rechristened as the “sovereign debt crisis” of profligate European states.

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These are the bare essentials that made it possible, and they all lie firmly in the private sector. They are—and we shall unpack them in plain English as we go—the structure of collateral deals in US repo markets, the structure of mortgage-backed derivatives and their role in repo transactions, the role played by correlation and tail risk in amplifying these problems, and the damage done by a set of economic ideas that blinded actors—both bankers and regulators—to the risks building up in the system. Again, I stress that these are quintessentially private-sector phenomena. I do this so that I can ask one more question as a setup.

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Rather than reducing correlation, these complex assets amplified an already ongoing liquidity crunch that had originated in the repo market months earlier. Too big to fail was the inevitable result of highly levered institutions discovering that all the liquidity in the world really could dry up all at once. The First Blinder: Tail Risk So, why didn’t anyone see this coming? Queen Elizabeth asked the British economists assembled at the London School of Economics in 2009, who, like analysts everywhere, had failed to see the crisis coming. The answer lies in the way banks measure and manage risk, the third of our seemingly unrelated elements that together generated the crisis and that are quintessentially private-sector, not public-sector failings.

The Crisis of Crowding: Quant Copycats, Ugly Models, and the New Crash Normal by Ludwig B. Chincarini

affirmative action, Alan Greenspan, asset-backed security, automated trading system, bank run, banking crisis, Basel III, Bear Stearns, Bernie Madoff, Black-Scholes formula, Bob Litterman, business cycle, buttonwood tree, Carmen Reinhart, central bank independence, collapse of Lehman Brothers, collateralized debt obligation, collective bargaining, corporate governance, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, delta neutral, discounted cash flows, diversification, diversified portfolio, family office, financial engineering, financial innovation, financial intermediation, fixed income, Flash crash, full employment, Gini coefficient, Glass-Steagall Act, global macro, high net worth, hindsight bias, housing crisis, implied volatility, income inequality, interest rate derivative, interest rate swap, John Meriwether, Kickstarter, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, low interest rates, low skilled workers, managed futures, margin call, market design, market fundamentalism, merger arbitrage, Mexican peso crisis / tequila crisis, Mitch Kapor, money market fund, moral hazard, mortgage debt, Myron Scholes, National best bid and offer, negative equity, Northern Rock, Occupy movement, oil shock, price stability, proprietary trading, quantitative easing, quantitative hedge fund, quantitative trading / quantitative finance, Ralph Waldo Emerson, regulatory arbitrage, Renaissance Technologies, risk free rate, risk tolerance, risk-adjusted returns, Robert Shiller, Ronald Reagan, Sam Peltzman, Savings and loan crisis, Sharpe ratio, short selling, sovereign wealth fund, speech recognition, statistical arbitrage, statistical model, survivorship bias, systematic trading, tail risk, The Great Moderation, too big to fail, transaction costs, value at risk, yield curve, zero-coupon bond

On May 31, 2007, he met with Fuld and told him that Lehman was too big in the leveraged lending business and could lose a lot of money in tail risk. Tail risk is the possibility of a huge negative event. Nagioff showed Fuld the numbers, which reflected a possible $3.2 billion loss under a stress scenario computed specifically for their meeting. According to Nagioff, he told Fuld that Lehman needed to reduce its forward commitments from $36 billion to $20 billion, impose rules on the amount of leverage in the deals, and develop a framework for limiting and evaluating this business. Fuld was surprised and concerned by the tail risk in the leveraged loan positions and authorized Nagioff to present his analysis to the Executive Committee and get authorization to move forward with a plan to limit the firm’s leveraged loan exposure.

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Instead, LTCM found innovative ways to close their positions. In this case, the fund might buy a pristine 10-year swap. The two swaps (old and new) are similar but opposite, and so cancel one another’s risk exposure, becoming what are called dead swaps. According to an LTCM partner, there is still a “remaining amount of annuity risk and tail risk, but these are essentially offsetting positions.” LTCM had a $1.2 trillion book of dead swaps, which they auctioned to the investment banks. For example, suppose LTCM had a swap with UBS receiving 5% and paying floating; the other swap had Goldman Sachs paying 4.9% and receiving floating. Anyone with a high bid could purchase the position, but Goldman Sachs and UBS had the biggest incentive to buy.

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Some thought Goldman was causing the market dysfunction.28 According to Goldman, however, neither the QS nor the QE group caused the movements. Traders at these groups stopped because they saw how damaging their trades might become. Goldman’s traders had begun to understand that the quant space was interconnected and fragile, just as LTCM’s space had been 10 years earlier. When you take a lot of leverage, you need to care for the tail risk aspect. If you can’t reduce the leverage quickly, it can kill you. With leverage, you have to worry about big tail unusual events. Global Alpha was more liquid and easy to take down, but the other fund [GEO] because of liquidity crunch and the crowding, was just going to take the positions down faster; there was no depth in these markets.

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

Pennies before the bulldozer This strategy has been termed ‘picking up pennies before the bulldozer’: there is genuinely free money lying around to be had (at least temporarily) by those who are willing to ignore unpredictable tail risks in the medium or long term. Who came out better? Alana’s career has stalled. Beth has done well, lived the high life and most likely has already retired or even died by the time the tail risk shows up. And if not, of course, Beth still has friends, family, a decent reputation (how could anyone have foreseen such an unlikely event?), and finds a new job very quickly after a suitably contrite period of unemployment.

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I’ll talk more about the implications for modellers when their models fail in chapters 9 and 10. For now, the point is that the incentives of risk management are not aligned. There is profit to be had from incorrectly characterising risk, and in particular from underestimating it. Those who correctly estimate significant tail risks may not be recognised or rewarded for doing so. Before the event, tail risks are unknown anyway if they can only be estimated from past data. After the event, there are other things to worry about. All that is not to say that LTCM were naively taking their models to be reality: in fact, they had a fairly sophisticated risk management system which did not solely rely on a VaR figure calculated assuming that the future would look like the past.

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First, the assumption that the past will be a reliable guide to the future is one that has been repeatedly shown to be incorrect. More sophisticated VaR models may price in either expectations about future changes (such as an increase in volatility) or more simply add a conservative margin for error. Second, the VaR has nothing to say about the shape or magnitude of the tail risk itself. The 99th percentile is a useful boundary for what might happen on the worst of the good days, but if a bad day happens, you’re on your own. David Einhorn, manager of another hedge fund, described this as ‘like an air bag that works all the time, except when you have a car accident’. As such, using the VaR as a risk measure effectively encourages the concentration of risks into the tail above the reported quantile.

The Butterfly Defect: How Globalization Creates Systemic Risks, and What to Do About It by Ian Goldin, Mike Mariathasan

air freight, air traffic controllers' union, Andrei Shleifer, Asian financial crisis, asset-backed security, bank run, barriers to entry, Basel III, Bear Stearns, behavioural economics, Berlin Wall, biodiversity loss, Bretton Woods, BRICs, business cycle, butterfly effect, carbon tax, clean water, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, connected car, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, David Ricardo: comparative advantage, deglobalization, Deng Xiaoping, digital divide, discovery of penicillin, diversification, diversified portfolio, Douglas Engelbart, Douglas Engelbart, Edward Lorenz: Chaos theory, energy security, eurozone crisis, Eyjafjallajökull, failed state, Fairchild Semiconductor, Fellow of the Royal Society, financial deregulation, financial innovation, financial intermediation, fixed income, Gini coefficient, Glass-Steagall Act, global pandemic, global supply chain, global value chain, global village, high-speed rail, income inequality, information asymmetry, Jean Tirole, John Snow's cholera map, Kenneth Rogoff, light touch regulation, Long Term Capital Management, market bubble, mass immigration, megacity, moral hazard, Occupy movement, offshore financial centre, open economy, precautionary principle, profit maximization, purchasing power parity, race to the bottom, RAND corporation, regulatory arbitrage, reshoring, risk free rate, Robert Solow, scientific management, Silicon Valley, six sigma, social contagion, social distancing, Stuxnet, supply-chain management, systems thinking, tail risk, TED Talk, The Great Moderation, too big to fail, Toyota Production System, trade liberalization, Tragedy of the Commons, transaction costs, uranium enrichment, vertical integration

Securitization is the process in which banks repackage a number of risky assets (for example, mortgages, credit card receivables, and student loans) and sell claims to different parts of the return stream.23 Although securitization in itself might not be destabilizing, excessive securitization has a number of detrimental effects, including excessive opacity and complexity. One important reason for the excessive transfer of risk through securitization was that this process was a convenient method to reduce the amount of capital required for a certain risk. The models on which regulatory capital requirements relied had a tendency to overlook tail risks.24 This loophole was exploited by banks that took $100 worth of loans for which they had to hold $8 of capital to generate a $100 security for which they had to hold much less, if any, capital. This regulatory and ratings arbitrage made it increasingly attractive for banks to engage in securitized lending.

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Used with the permission of SIFMA (the Securities Industry and Financial Markets Association). A number of theoretical reasons have been advanced to explain why banks might issue excessive numbers of securities. For example, it has been argued that markets for securities might become fragile if investors were to demand safe assets but neglect certain tail risks.26 Such a situation closely resembles that in the period between 2003 and 2007, when large numbers of new mortgage-backed securities were issued that investors perceived as safe. It has also been shown that heterogeneous expectations and adaptive behavior can lead to a situation in which more hedging instruments can destabilize markets.27 A similar motive emerges with respect to financial innovation, which typically increases the part of portfolio variance that is due to speculation when traders do not share the same assumptions about the evolution of markets.28 All of these findings rely on models that deviate from the traditional mantra of maintaining full rationality where all agents have perfect knowledge about the economy and each other.

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At the same time that regulators were stumbling, the collapse of the U.S.-based hedge fund Long-Term Capital Management following the 1997–98 financial crisis signaled that banks deemed “too big to fail” could expect to be bailed out by national governments. Together with the widespread use of value-at-risk models (which underestimated tail risks), this expectation obscured risk managers’ incentives and effectively eliminated the downside risk for those large financial institutions that were systemically the most relevant. Implicit government guarantees had a substantial impact on banks’ funding costs. One estimate puts the yearly reduction in funding costs due to implicit guarantees at between US$70 billion and US$120 billion between 2002 and 2011 (figure 2.6).44 Implicit guarantees are effectively a transfer of wealth from taxpayers to the financial system.

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

Affordable Care Act / Obamacare, Alan Greenspan, algorithmic trading, Andrei Shleifer, asset-backed security, availability heuristic, bank run, banking crisis, behavioural economics, Black Monday: stock market crash in 1987, Black-Scholes formula, bonus culture, break the buck, Bretton Woods, call centre, Carmen Reinhart, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Graeber, diversification, diversified portfolio, Edmond Halley, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, eurozone crisis, family office, financial deregulation, financial engineering, financial innovation, fixed income, Flash crash, Google Glasses, Gordon Gekko, high net worth, housing crisis, Hyman Minsky, impact investing, implied volatility, income inequality, index fund, information asymmetry, Innovator's Dilemma, interest rate swap, Kenneth Rogoff, Kickstarter, late fees, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, low interest rates, margin call, Mark Zuckerberg, McMansion, Minsky moment, money market fund, mortgage debt, mortgage tax deduction, Myron Scholes, negative equity, Network effects, Northern Rock, obamacare, payday loans, peer-to-peer lending, Peter Thiel, principal–agent problem, profit maximization, quantitative trading / quantitative finance, railway mania, randomized controlled trial, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Savings and loan crisis, short selling, Silicon Valley, Silicon Valley startup, Skype, South Sea Bubble, sovereign wealth fund, statistical model, subprime mortgage crisis, tail risk, Thales of Miletus, the long tail, transaction costs, Tunguska event, unbanked and underbanked, underbanked, Vanguard fund, web application

Markets get bigger, people become complacent, and risks grow until they can overwhelm the system as a whole. The next and final chapter looks at how finance can do better at managing very big risks, including the ones it generates itself. 9. Tail Risk: Pricing the Probability of Mayhem As job titles go, Gordon Woo’s takes some beating. Woo is a catastrophist, and his job is to think about tail risks—the sorts of big risks that occur outside the normal distribution of events and lurk in the long tails of probability. To be more precise, his job is to think about disasters. Earthquakes, hurricanes, terrorist attacks, and pandemics are his raw materials; models that calculate the probability of catastrophes and the damage they might cause are the products he helps to turn out.

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The Most Dangerous Asset in the World PART II: A FORCE FOR GOOD 4. Social-Impact Bonds and the Shrinking of the State 5. Live Long and Prosper 6. Equity and the License to Dream 7. Peer-to-Peer Lending and the Flaws of Finance 8. The Edge: Reaching the Marginal Borrower 9. Tail Risk: Pricing the Probability of Mayhem Conclusion Acknowledgments Glossary Notes Index Preface When I was offered the job of the Economist’s banking correspondent in the early summer of 2007, my reaction was one of apprehension. Banking was not an industry that I knew anything about.

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Mungo’s, 96 Standard & Poor’s (S&P), 24, 49, 157, 184, 234 Standardization, 39–41, 45, 47 Stevens, David, 151–152 Stevens, Teresa, 151–153 Stock exchanges, 14–16 Stocker, Anil, 207, 217 Stop-loss orders, 56 Straw, Jack, 94 Structured Bioequity, xii–xiii Structured finance, 237–238 Structured investment vehicle, 37 Stub quotes, 56 Student loans, 164, 166–167, 169–171 Stumpf, John, 192 Subprime mortgage tranches, loss amounts on, 233 Subprime mortgages, x, 79, 197–198, 233 Sufi, Amir, 204 Summers, Larry, 180 Suppa, Enrico, 9 Sutherland, Martinez, 89–90, 95, 105, 112 Svenska Handelsbanken, 206–207 Swaps, credit-default, 29–30 Swaps, interest-rate, 29 Swaziland, social-impact bonds (SIBs) in Sweden, banking crisis in, 75 Syndicated loans, 41 Tail risks, 221, 237 Tanzania, financial liberalization and, 34 Testosterone and cortisol, effect of on risk appetite and aversion, 116 Thailand, insurance claims for flooding, 225 Thaler, Richard, 137 Thales of Miletus, 10 Thayer, Ignacio, 210–211 Thiel, Peter, 163 This Time is Different (Reinhart and Rogoff), 35 Titmuss, Richard, 110 TransferWise, 190–192 Trente demoiselles de Genève, 22 True Link Financial, 144 Tufano, Peter, 59, 213–214 Tulipmania, 33, 36 Tversky, Amos, 137 UBS, 60 Uganda, social-impact bonds (SIBs) in, 103 Unbanked households, 200 United States aggregate value of property, 69 consumer debt, 183, 204 corporate debt, 120 cost of diagnosed diabetes, 102 cost of entitlements, 100 credit card debt, 183 general solicitation by private firms, 153–154 government interest in alternatives to student debt, 168 government spending, 99 home-ownership rates, 28, 85, 170 household debt, 205 leverage ratio, 2007, 77 life expectancy, 125 median house price, 70 monetary charitable gifts, 109 money raised through IPOs, 120 mortgage debt, 69 nonprofits in, 105–106 prepaid cards, 203 property bubbles, 74–75 real estate cycles, 237 savings-and-loan crisis (1990s), 30 social-impact bonds (SIBs), 98 student debt, 169 Unsecured lending, 206 Upstart, 166–168, 173, 175, 182 Used-car market, use of heuristics in, 46 Vega, Joseph de la, 24 Venture capital (VC), 150–151 Veterans, SIB program for, 102 Veterans Support Organization, 102 Viatical settlements, 142 Victory Loans, 28 Vishny, Robert, 42, 44 Volcker, Paul, xv, 30 Wachovia, xiv Wadhwa, Vivek, xv Warren, Elizabeth, xiv Washington Mutual, xiv Westlake, Darren, 153–154, 158, 161–162 “What Everybody Ought to Know About This Stock and Bond Business” Merrill Lynch ad, 28 When the Money Runs Out (King), 99 Wonga, 203, 205, 208 Woo, Gordon, 221–222, 227–229, 231, 233, 238 World Bank, 169 Wren, Christopher, 16 Wyman, Oliver, 204 Yale University, income-contingent financing program of, 165 Yale University, study of loss aversion, 136 Yunus, Muhammad, 203 Zaccaria, Benedetto, 9 ZestFinance, 199, 201, 205–206 Zombanakis, Minos, 41 Zopa, 181, 187, 188, 195 Zuckerberg, Mark, 174

The Euro and the Battle of Ideas by Markus K. Brunnermeier, Harold James, Jean-Pierre Landau

"there is no alternative" (TINA), Affordable Care Act / Obamacare, Alan Greenspan, asset-backed security, bank run, banking crisis, battle of ideas, Bear Stearns, Ben Bernanke: helicopter money, Berlin Wall, Bretton Woods, Brexit referendum, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, centre right, collapse of Lehman Brothers, collective bargaining, credit crunch, Credit Default Swap, cross-border payments, currency peg, currency risk, debt deflation, Deng Xiaoping, different worldview, diversification, Donald Trump, Edward Snowden, en.wikipedia.org, Fall of the Berlin Wall, financial deregulation, financial repression, fixed income, Flash crash, floating exchange rates, full employment, Future Shock, German hyperinflation, global reserve currency, income inequality, inflation targeting, information asymmetry, Irish property bubble, Jean Tirole, Kenneth Rogoff, Les Trente Glorieuses, low interest rates, Martin Wolf, mittelstand, Money creation, money market fund, Mont Pelerin Society, moral hazard, negative equity, Neil Kinnock, new economy, Northern Rock, obamacare, offshore financial centre, open economy, paradox of thrift, pension reform, Phillips curve, Post-Keynesian economics, price stability, principal–agent problem, quantitative easing, race to the bottom, random walk, regulatory arbitrage, rent-seeking, reserve currency, risk free rate, road to serfdom, secular stagnation, short selling, Silicon Valley, South China Sea, special drawing rights, tail risk, the payments system, too big to fail, Tyler Cowen, union organizing, unorthodox policies, Washington Consensus, WikiLeaks, yield curve

The European community thus needs a discussion of the extent to which it is willing to assume tail risk for its members. A commonly acceptable cutoff needs to be identified, agreed upon, clearly communicated, and enforced in future crises. Common liability for extreme crisis events must then go hand in hand with some kind of common control, as is to some extent reflected in nascent moves toward a more credible imposition of budget discipline in the euro area. This linkage also applied in the case of the discussion of unemployment insurance, where conditionality and uniform administration would be a key to credibility. The discussion of European liability for the tail risk of states, however, is implicitly limited to the case where governments refinance through debt: either they repay or they default.

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A European bond structure in the form of ESBies avoids any joint liability but would still redirect destabilizing cross-border capital flights and reduce the diabolic loop between government debt risk and banking risk. AGREED CUT-OFF RULE WHEN SOCIETY SHOULD INSURE “TAIL RISK” Irrespective of the specifics of the ultimately agreed-upon optimal policy rule, society will in the end provide some tail insurance for extreme events that its leveraged sectors or individuals may face. How much tail risk society—or, better said, nominal claim holders—should assume is a political question and depends very much on the underlying economic philosophy of the country. One of the main points of this book is that Europe has, up until now, avoided giving an answer to this question.

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Assigning zero-risk weights to government bonds may counteract the fiscal-bank diabolic loop in times of crisis, but ex ante could well contribute to the buildup of systemic risk. Irrespective of the specifics of the ultimately agreed-upon optimal policy rule, society will in the end provide some tail insurance to its leveraged sectors. How much tail risk society or, conversely, nominal claim holders should assume is a political question and depends very much on the underlying economic philosophy of the country. One of the main points of this book is that Europe has, up until now, avoided giving a single clear answer to this question. There clearly is no agreement among member states, with followers of the German tradition very aware of the moral hazard problems, while those influenced by French thinking call for more insurance and aggressive intervention in times of crisis.

Investment: A History by Norton Reamer, Jesse Downing

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

To what degree can we rely on price action to tell us the real risk of our investments? We also need to comprehend the nature of tail risks more effectively; that is, we need to understand how portfolios and markets behave under extreme scenarios. These types of outlier events have monumental consequences on all aspects of money management and lead to corresponding extreme shocks, from liquidity crises to credit crunches to fundamental changes in the economics of the underlying investments. Our failure to really conceptualize the nature of tail risk events has resulted in some investors and institutions becoming far too risky and some others, in truth, acting too conservatively.

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In the process, one reduces the probability of massive loss (the size of the left tail), which is great for capital preservation. Of course, by the same token, one cuts down 240 Investment: A History the size of the right tail, or the likelihood of enormous gain. And thus, both the adage and Carnegie are correct—it is just a question of purpose. Do you accept the left tail risk and swing for the fences, hoping to end up on the right tail with great riches? Or do you abandon the right tail and avoid the left tail, thus maximizing your chances of sitting somewhere in the middle? Markowitz’s Model and Tobin’s Improvements Although the concept of diversification has existed for some time, it was not until Harry Markowitz that the mathematical mechanics of diversification were worked out.

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Our failure to really conceptualize the nature of tail risk events has resulted in some investors and institutions becoming far too risky and some others, in truth, acting too conservatively. While the former is clearly worse, as this sort of aggressive behavior can jeopardize the very existence of the institution, being too conservative leaves returns on the table and can result in suboptimal performance. Our failure to truly apprehend the nuances of tail risk has resulted in an even more pernicious and dominant phenomenon: participants are often too risky or too conservative at precisely the wrong times. When all is going well and it seems as if certain assets cannot possibly fall in value is precisely the moment when the greatest threats are lurking.

Market Sense and Nonsense by Jack D. Schwager

3Com Palm IPO, asset allocation, Bear Stearns, Bernie Madoff, Black Monday: stock market crash in 1987, Brownian motion, buy and hold, collateralized debt obligation, commodity trading advisor, computerized trading, conceptual framework, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, diversified portfolio, fixed income, global macro, high net worth, implied volatility, index arbitrage, index fund, Jim Simons, junk bonds, London Interbank Offered Rate, Long Term Capital Management, low interest rates, managed futures, margin call, market bubble, market fundamentalism, Market Wizards by Jack D. Schwager, merger arbitrage, negative equity, pattern recognition, performance metric, pets.com, Ponzi scheme, proprietary trading, quantitative trading / quantitative finance, random walk, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, selection bias, Sharpe ratio, short selling, statistical arbitrage, statistical model, subprime mortgage crisis, survivorship bias, tail risk, transaction costs, two-sided market, value at risk, yield curve

Investment Misconception Investment Misconception 46: The diversification benefits beyond 10 holdings are minimal (even for heterogeneous investment universes such as hedge funds). Reality: Research studies that conclude that diversification benefits beyond 10 are minimal are invariably based on what happens on average across thousands of portfolios rather than what happens in the worst case to a specific portfolio (that is, tail risk). Most investors and portfolio managers, however, are very much concerned about the worst-case risk for their portfolios, not what happens on average across all portfolios. For these investors, diversification well beyond 10 can provide substantial risk-reduction benefits. How many more beyond 10 will be case dependent, but generally speaking, 20 or more will be a better choice than 10 (as long as added investments are of equivalent quality and sufficiently diversified with other managers to reduce the average correlation of managers in the portfolio).

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If, however, the manager has consistently assumed substantial market exposure and the track record coincides with a rising market, then past returns may reflect the market more than manager skill. 4. Diversify well beyond 10 (Chapter 17). Although, on average, the benefits of diversification are often only moderate beyond 10 diversified holdings, this view misses the point that the main value of greater diversification is mitigating worst-case outcomes (“tail risk” in the industry vernacular). Substantially greater diversification is therefore still beneficial, provided that added investments are considered of equivalent quality and are not more correlated to other holdings. 5. Favor bottom-up (manager-based) rather than top-down (category-based) allocation.

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The best due diligence process in the world can’t compete with the safeguards of direct investor ownership and transparency that are inherent in the managed account structure. 25. Research studies that conclude that diversification benefits beyond 10 are modest are invariably based on what happens on average across thousands of portfolios rather than what happens in the worst case to a specific portfolio. Portfolio managers who are concerned about tail risk should diversify well beyond 10 holdings (except when added assets are considered to be inferior to existing assets). 26. Increasing the number of holdings will not necessarily enhance diversification. The key is the degree to which added assets are uncorrelated to existing assets. Adding correlated holdings could even reduce diversification. 27.

Inside the House of Money: Top Hedge Fund Traders on Profiting in a Global Market by Steven Drobny

Abraham Maslow, Alan Greenspan, Albert Einstein, asset allocation, Berlin Wall, Bonfire of the Vanities, Bretton Woods, business cycle, buy and hold, buy low sell high, capital controls, central bank independence, commoditize, commodity trading advisor, corporate governance, correlation coefficient, Credit Default Swap, currency risk, diversification, diversified portfolio, family office, financial engineering, fixed income, glass ceiling, Glass-Steagall Act, global macro, Greenspan put, high batting average, implied volatility, index fund, inflation targeting, interest rate derivative, inventory management, inverted yield curve, John Meriwether, junk bonds, land bank, Long Term Capital Management, low interest rates, managed futures, margin call, market bubble, Market Wizards by Jack D. Schwager, Maui Hawaii, Mexican peso crisis / tequila crisis, moral hazard, Myron Scholes, new economy, Nick Leeson, Nixon triggered the end of the Bretton Woods system, oil shale / tar sands, oil shock, out of africa, panic early, paper trading, Paul Samuelson, Peter Thiel, price anchoring, proprietary trading, purchasing power parity, Reminiscences of a Stock Operator, reserve currency, risk free rate, risk tolerance, risk-adjusted returns, risk/return, rolodex, Sharpe ratio, short selling, Silicon Valley, tail risk, The Wisdom of Crowds, too big to fail, transaction costs, value at risk, Vision Fund, yield curve, zero-coupon bond, zero-sum game

On average, when there 46 INSIDE THE HOUSE OF MONEY is a bad event, volatility goes up because everybody gets nervous and pays up for insurance. One thing the September 11 attacks did for me was reconfirm that tail risk should not be allowed in your portfolio because things happen that you can’t imagine. I’ll give you an example that shows how serious I am about cutting off tail risk. After the stock market bubble burst in 2000 and the Fed started cutting rates, I thought there was a chance the United States could be headed toward a Japan-like deflation situation. I bought butterfly option structures on front-end interest rates whereby I bought one call struck at 2 percent yield and sold two times as many calls struck at 1 percent yield, such that we’d make money if interest rates went anywhere from 2 percent to zero.The option structure was very cheap and our biggest payout came if rates stopped at 1 percent.

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Implied volatility is based on historical volatility, but who cares about historicals? They’re irrelevant.The point is, things can happen for the first time that aren’t in your distribution so they can’t be priced. If it’s never happened before, how can you hedge yourself? The only way to hedge the unknown is to cut off tail risk completely. What was your favorite trade of all time? The trade I remember the most only made a small amount of money but it was the first time I took on a large position based on my belief that I understood the market better than the market. The trade was for the price of overnight Swiss franc interest rates, one day THE FAMILY OFFICE MANAGER 47 in advance.

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The other risk is North Korea flexing their nuclear muscles.There is a chance they could use them out of desperation. One of the things Everest uses to hedge these low-probability but nonnegligible events is credit default swaps on China and Korea which, interestingly, are extremely cheap. Do you think markets underprice tail risk? Yes.We’ve seen it time and again.Things happen that nobody thought possible.The crash of 1987, the Mexican devaluation of 1994, the Asian devaluations of 1997, and September 11 all were unimaginable. Do you foresee a day when the term emerging markets ceases to exist? In other words, all markets emerge to become first world or developed countries.

Commodity Trading Advisors: Risk, Performance Analysis, and Selection by Greg N. Gregoriou, Vassilios Karavas, François-Serge Lhabitant, Fabrice Douglas Rouah

Asian financial crisis, asset allocation, backtesting, buy and hold, capital asset pricing model, collateralized debt obligation, commodity trading advisor, compound rate of return, constrained optimization, corporate governance, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, discrete time, distributed generation, diversification, diversified portfolio, dividend-yielding stocks, financial engineering, fixed income, global macro, high net worth, implied volatility, index arbitrage, index fund, interest rate swap, iterative process, linear programming, London Interbank Offered Rate, Long Term Capital Management, managed futures, market fundamentalism, merger arbitrage, Mexican peso crisis / tequila crisis, p-value, Pareto efficiency, Performance of Mutual Funds in the Period, Ponzi scheme, proprietary trading, quantitative trading / quantitative finance, random walk, risk free rate, risk-adjusted returns, risk/return, selection bias, Sharpe ratio, short selling, stochastic process, survivorship bias, systematic trading, tail risk, technology bubble, transaction costs, value at risk, zero-sum game

Note from the figure the magnitude of potential losses that this trade has incurred over the past 25 years. That said, Cootner’s original point that a profitable trade can persist in the face of knowledge of its existence seems to be borne out 36 years later. Figure 15.2 summarizes the information in Figure 15.1 differently to emphasize the “tail risk” of a July to December wheat spread strategy. If a manager took a short position in this spread, the possible outcomes incorporate losses that are several times the size of the average profit. Again, in a short position, the manager wants the price change to be negative, so the historical losses on this trade are represented by the positive numbers in Figure 15.2.

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A manager might conclude that this trade can continue to exist 14 12 10 8 6 4 2 0 ≤ –14.25c > –14.25c and ≤ –8.5c > –8.5c and ≤ -2.75c > –2.75c and ≤ 3c > 3c and ≤ 8.75c Price Change Intervals FIGURE 15.2 Histogram of the Frequency Distribution for the July Wheat–December Wheat Price Changes, 1979–2003 Source: Premia Capital Management, LLC. > 8.75c 280 PROGRAM EVALUATION, SELECTION, AND RETURNS because of the unpleasant tail risk that must be assumed when putting on this trade. Petroleum Complex Example Are there any persistent price tendencies that can be linked to structural aspects of the petroleum market? After examining the activity of commercial participants in the petroleum futures markets, it appears that their hedging activity is bunched up within certain time frames.

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As a result of the recurring frequency of down markets since the collapse of Long-Term Capital Management (LTCM) in August 1998, VaR has played a paramount role as a risk management tool and is considered a mainstream technique to estimate a CTA’s exposure to market risk. 377 378 PROGRAM EVALUATION, SELECTION, AND RETURNS With the large acceptance of VaR and, specifically, the modified VaR as a relevant risk management tool, a more suitable portfolio performance measure for CTAs can be formulated in term of the modified Sharpe ratio.1 Using the traditional Sharpe ratio to rank CTAs will underestimate the tail risk and overestimate performance. Distributions that are highly skewed will experience greater-than-average risk underestimation. The greater the distribution is from normal, the greater is the risk underestimation. In this chapter we rank 30 CTAs according to the Sharpe ratio and modified Sharpe ratio.

Stress Test: Reflections on Financial Crises by Timothy F. Geithner

Affordable Care Act / Obamacare, Alan Greenspan, asset-backed security, Atul Gawande, bank run, banking crisis, Basel III, Bear Stearns, Bernie Madoff, Bernie Sanders, Black Monday: stock market crash in 1987, break the buck, Buckminster Fuller, Carmen Reinhart, central bank independence, collateralized debt obligation, correlation does not imply causation, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency risk, David Brooks, Doomsday Book, eurozone crisis, fear index, financial engineering, financial innovation, Flash crash, Goldman Sachs: Vampire Squid, Greenspan put, housing crisis, Hyman Minsky, illegal immigration, implied volatility, Kickstarter, London Interbank Offered Rate, Long Term Capital Management, low interest rates, margin call, market fundamentalism, Martin Wolf, McMansion, Mexican peso crisis / tequila crisis, money market fund, moral hazard, mortgage debt, Nate Silver, negative equity, Northern Rock, obamacare, paradox of thrift, pets.com, price stability, profit maximization, proprietary trading, pushing on a string, quantitative easing, race to the bottom, RAND corporation, regulatory arbitrage, reserve currency, Saturday Night Live, Savings and loan crisis, savings glut, selection bias, Sheryl Sandberg, short selling, sovereign wealth fund, stock buybacks, tail risk, The Great Moderation, The Signal and the Noise by Nate Silver, Tobin tax, too big to fail, working poor

At the time, trying to force our commercial banks to raise more capital (and dilute the holdings of their existing shareholders) so that they could survive a Great Depression would have seemed arbitrary and unnecessary, like imposing a thirty-mile-an-hour speed limit on an expressway. And it would have driven more risk into nonbanks. Still, since we had no way of knowing what the future would bring, and I had vivid memories of the crises of the previous decade, I wanted us to examine the darkest possible scenarios, the seemingly implausible “tail risks.” In meeting after meeting, I argued that regulators and risk managers alike needed to set aside assumptions about the implausibility of a major shock and study the impact of that shock if it somehow happened. This provoked a fair amount of skepticism internally, and derision outside the Fed. In that apparently benign state of the world, many bank executives thought it was totally unreasonable to expect them to prepare for a deep recession, much less a depression.

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You could say our failures of foresight were primarily failures of imagination, like the failure to foresee terrorists flying planes into buildings before September 11. But severe financial crises had happened for centuries in multiple countries, in many shapes and forms, always with pretty bad outcomes. For all my talk about tail risk, negative extremes, and stress scenarios, our visions of darkness still weren’t dark enough. When models told us that only a depression-level shock could cause severe distress to banks, we should have done more to consider what would happen in the event of a depression, no matter how unlikely it seemed.

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Citi would place $312 billion of Wachovia’s assets inside a “ring fence,” partitioning them from the rest of its balance sheet, but would commit to absorb the first $42 billion in losses from those assets. The government would bear any losses above that, putting a ceiling on Citi’s catastrophic tail risk, reassuring investors that Wachovia wouldn’t drag Citi down if the assets turned out to be worse than expected. The FDIC staff concluded that the Citi proposal was unlikely to cost taxpayers anything, while the Wells offer would probably cost billions. Even as she approved the deal, Sheila continued to emphasize her reluctance to put any public money at risk, implying she had bowed to pressure from Treasury and the Fed.

In Pursuit of the Perfect Portfolio: The Stories, Voices, and Key Insights of the Pioneers Who Shaped the Way We Invest by Andrew W. Lo, Stephen R. Foerster

Alan Greenspan, Albert Einstein, AOL-Time Warner, asset allocation, backtesting, behavioural economics, Benoit Mandelbrot, Black Monday: stock market crash in 1987, Black-Scholes formula, Bretton Woods, Brownian motion, business cycle, buy and hold, capital asset pricing model, Charles Babbage, Charles Lindbergh, compound rate of return, corporate governance, COVID-19, credit crunch, currency risk, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, Donald Trump, Edward Glaeser, equity premium, equity risk premium, estate planning, Eugene Fama: efficient market hypothesis, fake news, family office, fear index, fiat currency, financial engineering, financial innovation, financial intermediation, fixed income, hiring and firing, Hyman Minsky, implied volatility, index fund, interest rate swap, Internet Archive, invention of the wheel, Isaac Newton, Jim Simons, John Bogle, John Meriwether, John von Neumann, joint-stock company, junk bonds, Kenneth Arrow, linear programming, Long Term Capital Management, loss aversion, Louis Bachelier, low interest rates, managed futures, mandelbrot fractal, margin call, market bubble, market clearing, mental accounting, money market fund, money: store of value / unit of account / medium of exchange, Myron Scholes, new economy, New Journalism, Own Your Own Home, passive investing, Paul Samuelson, Performance of Mutual Funds in the Period, prediction markets, price stability, profit maximization, quantitative trading / quantitative finance, RAND corporation, random walk, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Solow, Ronald Reagan, Savings and loan crisis, selection bias, seminal paper, shareholder value, Sharpe ratio, short selling, South Sea Bubble, stochastic process, stocks for the long run, survivorship bias, tail risk, Thales and the olive presses, Thales of Miletus, The Myth of the Rational Market, The Wisdom of Crowds, Thomas Bayes, time value of money, transaction costs, transfer pricing, tulip mania, Vanguard fund, yield curve, zero-coupon bond, zero-sum game

So, it’s the risk management issue within the firm, a governance issue, that accounts more so than using these instruments.”78 Scholes’s Perfect Portfolio Scholes has a different way of thinking about the Perfect Portfolio compared to Markowitz, Sharpe, and others.79 While they focus on the composition of the Perfect Portfolio, for Scholes the Perfect Portfolio is all about risk management. If we pay closer attention to what markets are telling us, Scholes believes, particularly to the derivatives market, we can adjust our risk exposure, avoiding the downside “tail risks” and “drawdowns,” such as those that occurred during the financial crisis, while capitalizing on the positive “tail gains” and thus better achieve our goals. In order to understand Scholes’s logic, however, we need to understand what investors really care about and how to measure compound returns and the growth of wealth.

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If investors can avoid these tails, these really bad unusual events, then their projected terminal wealth will be better protected. There are two kinds of tails, however: negative ones and positive ones. According to Scholes, for the Perfect Portfolio, investors want to not only avoid the negative tail risk but also take advantage of tail gain. Working with colleagues at Janus Henderson Investors, where he is the chief investment strategist, Scholes helps to interpret information from the options market to build distributions of expected returns on individual securities such as Microsoft along with those of asset classes, commodities, and bonds, using them to construct portfolios that maximize expected tail gain and minimize expected tail loss.

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The VIX gives us a market-based estimate of expected market volatility. To focus on the expected tails of the distribution, we could look at deeply out-of-the-money options that only pay if there is an extreme change in the market. The prices of these types of options provide valuable information about tail risk. “Using this information to construct the ideal portfolio, one can change the composition of the portfolio based on risk and how risk is changing. If one can keep the risk of their portfolio constant, you reduce a huge amount of the convexity costs that will occur because you allow your portfolio to fluctuate.… If the ideal portfolio doesn’t use information in the market to do it, it’s not an ideal portfolio.

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber

affirmative action, Albert Einstein, asset allocation, backtesting, beat the dealer, behavioural economics, Black Swan, Black-Scholes formula, Bonfire of the Vanities, book value, butterfly effect, commoditize, commodity trading advisor, computer age, computerized trading, disintermediation, diversification, double entry bookkeeping, Edward Lorenz: Chaos theory, Edward Thorp, family office, financial engineering, financial innovation, fixed income, frictionless, frictionless market, Future Shock, George Akerlof, global macro, implied volatility, index arbitrage, intangible asset, Jeff Bezos, Jim Simons, John Meriwether, junk bonds, London Interbank Offered Rate, Long Term Capital Management, loose coupling, managed futures, margin call, market bubble, market design, Mary Meeker, merger arbitrage, Mexican peso crisis / tequila crisis, moral hazard, Myron Scholes, new economy, Nick Leeson, oil shock, Paul Samuelson, Pierre-Simon Laplace, proprietary trading, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk tolerance, risk/return, Robert Shiller, Robert Solow, rolodex, Saturday Night Live, selection bias, shareholder value, short selling, Silicon Valley, statistical arbitrage, tail risk, The Market for Lemons, time value of money, too big to fail, transaction costs, tulip mania, uranium enrichment, UUNET, William Langewiesche, yield curve, zero-coupon bond, zero-sum game

One is what is called tail risk, the uncertainty of rare events, events that might even be so rare as to never have been observed. The second is risk where the probabilities of events are difficult to quantity. But unlike this primal risk, both of these end up fitting into the existing structure of probability theory. Once tail risks are recognized, they can be dealt with like any other event. They just have more zeros to the right of the decimal point. Indeed, there is an area of statistics called extreme value theory that deals with measuring the probability of tail events. Tail risk has been popularized as a topic by Nassim Taleb in Fooled by Randomness (New York: Texere, 2001) using John Stuart Mill’s example of a black swan.

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Knight distinguished the uncertainty of events that are random but where the probabilities are known, as would be the case for a game of roulette, from the uncertainty of economic or political events where the probabilities cannot 269 ccc_demon_261-270_notes.qxd 2/13/07 1:47 PM Page 270 NOTES be so mechanistically determined, such as the risk of a future war in Europe. It turns out that, as with tail risks, Knightian uncertainty can fit within the existing structure of probability. We may not be able to estimate the probability of some events with the same precision as we can for games of chance, but we can, whether through objective or subjective means, come up with a probability. Even in the case of no knowledge of the likelihood of the outcomes, analysis can still proceed with an assumption of a uniform distribution (i.e., with all the possible outcomes being assigned an equal probability of occurring).

Young Money: Inside the Hidden World of Wall Street's Post-Crash Recruits by Kevin Roose

activist fund / activist shareholder / activist investor, Basel III, Bear Stearns, Carl Icahn, cognitive dissonance, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, deal flow, discounted cash flows, Donald Trump, East Village, eat what you kill, eurozone crisis, financial engineering, fixed income, forward guidance, glass ceiling, Goldman Sachs: Vampire Squid, hedonic treadmill, information security, Jane Street, jitney, junk bonds, Kevin Roose, knowledge worker, Michael Milken, new economy, Occupy movement, off-the-grid, plutocrats, proprietary trading, Robert Shiller, selection bias, shareholder value, side project, Silicon Valley, Skype, Steve Jobs, tail risk, The Predators' Ball, too big to fail, two and twenty, urban planning, We are the 99%, work culture , young professional

The idea is that, while the theoretical expected value of the game is a small negative number (because the coin will probably land on heads within a few flips, ending the game and limiting your losses), there is a tiny possibility of a catastrophic result, in which tails comes up again and again until you owe millions of dollars. There was no right answer, but the way a person replied could shed light on what his thought process might be like as a trader; a candidate who said he’d need only a dollar to play probably wasn’t thinking through the tail-risk scenarios carefully, while a candidate who answered with too big a number was being excessively cautious. Tail risk was an important idea for someone working in finance after the crisis, since one of the biggest mistakes financial institutions had made during the inflation of the subprime mortgage bubble was ignoring the small chance that the entire interconnected mess would collapse.

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And so on and so on, each time doubling the payout for heads, and flipping again on tails. How much would I have to pay you up front to play this game? The question was a version of the Martingale, a French gambling strategy. The purpose of asking it was to test a candidate’s understanding of tail risk—the chance of low-probability, high-impact outcomes. The idea is that, while the theoretical expected value of the game is a small negative number (because the coin will probably land on heads within a few flips, ending the game and limiting your losses), there is a tiny possibility of a catastrophic result, in which tails comes up again and again until you owe millions of dollars.

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

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

Now, when people hear you want to make a low-risk portfolio out of seven stocks, even if they accept the mathematical argument about correlation, they say, “But if one company goes bad, it’s such a big part of your portfolio. It has to be safer to have hundreds of stocks, so no single one can hurt you much.” That argument could be true; that is, the smaller portfolio might have the same standard deviation but more tail risk of a large loss. It’s also possible that there’s more parameter uncertainty with the small portfolio. It doesn’t have to be true, though, and I think it isn’t, at least if you select properly. However, my main response is: “Okay. But if one company shoots up in value, it’s also a big part of your portfolio.

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Having breaks mostly when VaR was low was dangerous. It meant bad things happened often when you said VaR was low, and seldom when you said VaR was high. People lose faith quickly if you do that. The unvarnished fact was that none of us understood our risk in the center of the distribution. People worry all the time about tail risk—extreme events. But we didn’t know much about what happened on all the other days—the normal days without extreme price movements. Moreover, most of our breaks came from system or data errors. We spent more time thinking up clever approximations and defaults for missing or obviously incorrect data than about how financial prices might move.

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In practice, however, using VaR as a risk measure had a lot to recommend it. There was no good measure of bank risk, and at least VaR was available and could be verified objectively. It forced banks to confront their central risk, which is important in itself and a prerequisite to understanding tail risk. It required major improvements in systems and controls. No one had a better idea, and no one wanted to wait around for a decade or so until one arose. It would be better to have a rational risk-based system on a flawed measure and improve it later than to do nothing because you couldn’t do it perfectly.

The Fifth Risk by Michael Lewis

Albert Einstein, behavioural economics, Bernie Sanders, Biosphere 2, chief data officer, cloud computing, data science, Donald Trump, fake news, Ferguson, Missouri, low interest rates, machine readable, opioid epidemic / opioid crisis, Silicon Valley, Solyndra, Steve Bannon, tail risk, the new new thing, uranium enrichment

NORTON & COMPANY Independent Publishers Since 1923 NEW YORK | LONDON for Tom Wolfe In Memoriam Donald J. Trump @realDonaldTrump Very organized process taking place as I decide on Cabinet and many other positions. I am the only one who knows who the finalists are! 9:55 PM - 15 Nov 2016 25,572 Retweets 112,055 Likes CONTENTS PROLOGUE: LOST IN TRANSITION I. TAIL RISK II. PEOPLE RISK III. ALL THE PRESIDENT’S DATA Acknowledgments THE FIFTH RISK PROLOGUE LOST IN TRANSITION CHRIS CHRISTIE NOTICED a piece in the New York Times—that’s how it all started. The New Jersey governor had dropped out of the presidential race in February 2016 and thrown what support he had behind Donald Trump.

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As Nancy Cook later reported in Politico, Bannon visited the transition headquarters a few days after he’d given Christie the news, and made a show of tossing the work the people there had done for Donald Trump into the garbage can. Trump was going to handle the transition more or less by himself. Not even Steve Bannon thought this was a good idea. “I was fucking nervous as shit,” Bannon later told friends. “I go,” Holy fuck, this guy [Trump] doesn’t know anything. And he doesn’t give a shit.’” I TAIL RISK ON THE MORNING after the election, November 9, 2016, the people who ran the U.S. Department of Energy turned up in their offices and waited. They had cleared thirty desks and freed up thirty parking spaces. They didn’t know exactly how many people they’d host that day, but whoever won the election would surely be sending a small army into the Department of Energy, and to every other federal agency.

Firefighting by Ben S. Bernanke, Timothy F. Geithner, Henry M. Paulson, Jr.

Asian financial crisis, asset-backed security, bank run, Basel III, Bear Stearns, break the buck, Build a better mousetrap, business cycle, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Doomsday Book, financial deregulation, financial engineering, financial innovation, Glass-Steagall Act, housing crisis, Hyman Minsky, income inequality, invisible hand, Kenneth Rogoff, labor-force participation, light touch regulation, London Interbank Offered Rate, Long Term Capital Management, low interest rates, margin call, money market fund, moral hazard, mortgage debt, negative equity, Northern Rock, opioid epidemic / opioid crisis, pets.com, price stability, quantitative easing, regulatory arbitrage, Robert Shiller, Savings and loan crisis, savings glut, short selling, sovereign wealth fund, special drawing rights, tail risk, The Great Moderation, too big to fail

We were all uncomfortable about this, and all three of us established new risk committees and task forces within our institutions before the crisis to try to focus attention on systemic threats. We tried to lean against the prevailing winds of overconfidence, pushing back against the notion that crises were vestiges of the past, calling for more robust risk management and humility about tail risks. But we were not sufficiently creative or forceful in acting to contain those risks, and none of us recognized how they were about to spiral out of control. For all our crisis experience, we still failed to anticipate the worst crisis of our lifetimes. When Ben was later asked what surprised him most about the crisis, he replied: “the crisis.”

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But more capital alone seemed unlikely to stop its creditors and uninsured foreign depositors from running. So the rescue also included a Fed and FDIC “ring fence” around $306 billion of Citi’s worst assets, making the company responsible for the first $37 billion in potential losses, but providing a government guarantee for 90 percent of any losses above that. The idea was to limit Citi’s tail risk by insuring it against a worst-case scenario, which would hopefully restore enough confidence to avert the worst-case scenario. We figured this approach would be much cheaper than injecting all the capital Citi needed or buying all its bad assets, unless the entire system collapsed—and in that case our problems would be much bigger than Citi.

Alpha Trader by Brent Donnelly

Abraham Wald, algorithmic trading, Asian financial crisis, Atul Gawande, autonomous vehicles, backtesting, barriers to entry, beat the dealer, behavioural economics, bitcoin, Boeing 747, buy low sell high, Checklist Manifesto, commodity trading advisor, coronavirus, correlation does not imply causation, COVID-19, crowdsourcing, cryptocurrency, currency manipulation / currency intervention, currency risk, deep learning, diversification, Edward Thorp, Elliott wave, Elon Musk, endowment effect, eurozone crisis, fail fast, financial engineering, fixed income, Flash crash, full employment, global macro, global pandemic, Gordon Gekko, hedonic treadmill, helicopter parent, high net worth, hindsight bias, implied volatility, impulse control, Inbox Zero, index fund, inflation targeting, information asymmetry, invisible hand, iterative process, junk bonds, Kaizen: continuous improvement, law of one price, loss aversion, low interest rates, margin call, market bubble, market microstructure, Market Wizards by Jack D. Schwager, McMansion, Monty Hall problem, Network effects, nowcasting, PalmPilot, paper trading, pattern recognition, Peter Thiel, prediction markets, price anchoring, price discovery process, price stability, quantitative easing, quantitative trading / quantitative finance, random walk, Reminiscences of a Stock Operator, reserve currency, risk tolerance, Robert Shiller, secular stagnation, Sharpe ratio, short selling, side project, Stanford marshmallow experiment, Stanford prison experiment, survivorship bias, tail risk, TED Talk, the scientific method, The Wisdom of Crowds, theory of mind, time dilation, too big to fail, transaction costs, value at risk, very high income, yield curve, you are the product, zero-sum game

On the other hand, this preference for longshots can sometimes lead to bad trades with good optics (like those 5% one-touches that are always so hard to resist). The longshot mentality is bolstered by financial media features that shower adulation on tail risk managers in the rare moments their highly-levered insurance bets pay off. There are no stories written about the tail risk fund that bleeds for four straight years while the VIX is pinned at 12! The takeaway here is: be aware of favorite/longshot bias. Don’t get sucked in by bad trades with good optics. Various estimates put the cross-over point around 35%/40% An example of favorite longshot bias in action You often see favorite-longshot bias over economic and central bank events.

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CNN’s Fear and Greed indicator is a nice simple snapshot of equity sentiment. Many banks publish sentiment and positioning data. In FX there is the Citi Pain Index and the HSBC Positioning Indicators. In broad macro, the Bank of America Global Fund Manager Survey gets a lot of attention and highlights crowded positions and tail risks. Retail brokers like Oanda, Dukascopy and DailyFX publish detailed positioning data. Each market has its important sentiment and positioning data, and this is generally easy to find simply by Googling. As you become expert in your market, you will learn the best sentiment and positioning indicators to follow.

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The universe of trades is so large in every asset class that there is no excuse for putting on trades that have unlimited downside. You should be confident about your ability to stop out of any trade or you should keep it small enough it’s not going to kill you if it goes pear-shaped. If a trade you have on has a low probability of a huge tail risk, cover it and find something better to trade. Understand path dependence Path dependence is an important concept for every professional trader to understand. It comes into play in different ways. Path dependence means future steps of a process depend on its history. A series of coin flips is not path dependent.

Finance and the Good Society by Robert J. Shiller

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

William Goetzmann and some of his colleagues in the Yale nance group have calculated the optimal strategy for a manager of an investment fund who wishes to deceive investors by producing good returns for a number of years, and then to take the investment fees and run in that rare year when the fund does very badly for its investors.16 Such a nefarious strategy generates “tail risk,” risk in the tails of the probability distribution of investment returns, or, in other words, “black swan events” that are so rare that investors may not see them coming, even though they are huge when they do occur. In the meantime, the investment fund can pro t from the appearance of good and safe returns.

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Smith (1761): 191, 193. 17. “Death of a Drug Lord,” CNN, December 5, 1993. 18. Griffiths (2003). References Acemoglu, Daron, and Pierre Yared. 2010. “Political Limits to Globalization.” American Economic Review 100(2):83–88. Acharya, Viral, Thomas Cooley, Matthew Richardson, and Ingo Walter. 2010. “Manufacturing Tail Risk: A Perspective on the Financial Crisis of 2007–9.” Foundations and Trends in Finance 4:247–325. Acharya, Viral, Matthew Richardson, Stijn van Nieuwerburgh, and Lawrene J. White. 2011. Guaranteed to Fail: Fannie Mae, Freddie Mac, and the Debacle of Mortgage Finance. Princeton, NJ: Princeton University Press.

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See also New York Stock Exchange stock options: as incentives, 21, 22, 23, 24, 48–49; pricing, 132; trading, 78–80 stocks: dilution, 49; dividends, 171, 185; employee ownership, 215–16; history, 46–48, 144; as incentives, 48–49; initial public offerings, 45, 47; inside information, 23, 29–30; issuing, 45, 46, 47, 48–49; prices, 20–21, 133, 171–72, 185–86 Stokey, Nancy, 29–30, 77 storytelling, 180, 181 structured investment vehicles (SIVs), 43 subprime crisis, xv–xvi, 50, 51, 52, 53, 62, 157, 220 sumptuary laws and taxes, 191, 192 swaps, 75 Sweden, mutual fund managers, 28 Swensen, David, 31 Switzerland, homeownership, 213 symmetry, beauty and, 131–32, 133 tail risk, 35 Tarbell, Ida M., 164 tariffs, xvii, 92 Tauzin, Billy, 88 taxes: cheating on, 101; consumption, 192, 253n14 (Chapter 27); estate, 192–93, 253n15 (Chapter 27); fiscal policy, 114–16, 117, 133; gift, 204–5; progressive, 116, 192, 193–94, 217–18, 235; sumptuary, 191, 192. See also income taxes technology.

The Ascent of Money: A Financial History of the World by Niall Ferguson

Admiral Zheng, Alan Greenspan, An Inconvenient Truth, Andrei Shleifer, Asian financial crisis, asset allocation, asset-backed security, Atahualpa, bank run, banking crisis, banks create money, Bear Stearns, Black Monday: stock market crash in 1987, Black Swan, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, BRICs, British Empire, business cycle, capital asset pricing model, capital controls, Carmen Reinhart, Cass Sunstein, central bank independence, classic study, collateralized debt obligation, colonial exploitation, commoditize, Corn Laws, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, Daniel Kahneman / Amos Tversky, deglobalization, diversification, diversified portfolio, double entry bookkeeping, Edmond Halley, Edward Glaeser, Edward Lloyd's coffeehouse, equity risk premium, financial engineering, financial innovation, financial intermediation, fixed income, floating exchange rates, Fractional reserve banking, Francisco Pizarro, full employment, Future Shock, German hyperinflation, Greenspan put, Herman Kahn, Hernando de Soto, high net worth, hindsight bias, Home mortgage interest deduction, Hyman Minsky, income inequality, information asymmetry, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, iterative process, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", John Meriwether, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kenneth Rogoff, knowledge economy, labour mobility, Landlord’s Game, liberal capitalism, London Interbank Offered Rate, Long Term Capital Management, low interest rates, market bubble, market fundamentalism, means of production, Mikhail Gorbachev, Modern Monetary Theory, Money creation, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, mortgage debt, mortgage tax deduction, Myron Scholes, Naomi Klein, National Debt Clock, negative equity, Nelson Mandela, Nick Bostrom, Nick Leeson, Northern Rock, Parag Khanna, pension reform, price anchoring, price stability, principal–agent problem, probability theory / Blaise Pascal / Pierre de Fermat, profit motive, quantitative hedge fund, RAND corporation, random walk, rent control, rent-seeking, reserve currency, Richard Thaler, risk free rate, Robert Shiller, rolling blackouts, Ronald Reagan, Savings and loan crisis, savings glut, seigniorage, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, spice trade, stocks for the long run, structural adjustment programs, subprime mortgage crisis, tail risk, technology bubble, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus, Thorstein Veblen, tontine, too big to fail, transaction costs, two and twenty, undersea cable, value at risk, W. E. B. Du Bois, Washington Consensus, Yom Kippur War

A credit default swap, meanwhile, offers protection against a company’s defaulting on its bonds. Perhaps the most intriguing kind of derivative, however, are the weather derivatives like natural catastrophe bonds, which allow insurance companies and others to offset the effects of extreme temperatures or natural disasters by selling the so-called tail risk to hedge funds like Fermat Capital. In effect, the buyer of a ‘cat bond’ is selling insurance; if the disaster specified in the bond happens, the buyer has to pay out an agreed sum or forfeit his principal. In return, the seller pays an attractive rate of interest. In 2006 the total notional value of weather-risk derivatives was around $45 billion.

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For there is no question that the heuristic biases of individuals play a critical role in generating volatility in financial markets. This brings us to the second reason for the inherent instability of the financial system: human behaviour. As we have seen, all financial institutions are at the mercy of our innate inclination to veer from euphoria to despondency; our recurrent inability to protect ourselves against ‘tail risk’; our perennial failure to learn from history. In a famous article, Daniel Kahneman and Amos Tversky demonstrated with a series of experiments the tendency that people have to miscalculate probabilities when confronted with simple financial choices. First, they gave their sample group 1,000 Israeli pounds each.

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Stanford 320 State Farm insurance company 181-2 state-owned enterprises see privatization; sovereign wealth funds State Savings and Loan 255 statistics 188-9 sterling see pound sterling Stevenson, George 60 Stewart, Jimmy 247-8 Stiglitz, Joseph 310-13 stockbrokers 153-4 Stockholm 48-9 stock markets and exchanges: benefits of 341 bubbles 121-4 Chile 218 closure of 300 compared with bond markets 124-5 compared with property market 261-3 crashes 121-2 as discipline on companies 120 foreign stock exchanges 293 forward/futures markets 132 fraud 121-2 history of 3 indices 164-5 and inflation 123 insurance companies and 196-8 international comparisons 125 mechanical selling 165 and pensions see pension funds speculators 122 stock exchanges 3 and supply of credit 132 total capitalization of the world’s 4 volatility and risks 6 war and 125 and First World War 297 stocks see shares Stowe House 236-40 Strong, Benjamin 161 ‘structural adjustment’ 309 structured investment vehicles (SIVs) 5 Styal 94 subprime lending 8-9 and black and Latino borrowers 266-7 responsibility for 266-8 sugar 285 Sunbelt 255 Sun Insurance Office 187 swaps 4 Sweden 48-9 Swift, Jonathan 157 Swiss National Bank 57 Switzerland 57 Sword Blade Company 157 Syria 2 tail risk 227 Taiwan 339 Tanzania 276 tariffs: protectionist 303 rising 287 taxes: bond markets and 68 British 210-11 collection 76 in debtor countries 309 excise 72 Florentine 45 land 230 and mortgage payments 252 and property law reform 275 savings discouraged by 211 Taylor, Gene 181 Teamsters Union 255 technological innovation: evolutionary 350 history of 8 and inflation 116 transferability 287 weaponry 285 technology companies 124 Temasek 337n.

Unknown Market Wizards by Jack D. Schwager

3D printing, algorithmic trading, automated trading system, backtesting, barriers to entry, Black Monday: stock market crash in 1987, Brexit referendum, buy and hold, commodity trading advisor, computerized trading, COVID-19, cryptocurrency, diversification, Donald Trump, eurozone crisis, family office, financial deregulation, fixed income, forward guidance, index fund, Jim Simons, litecoin, Long Term Capital Management, margin call, market bubble, Market Wizards by Jack D. Schwager, Nick Leeson, performance metric, placebo effect, proprietary trading, quantitative easing, Reminiscences of a Stock Operator, risk tolerance, risk-adjusted returns, Sharpe ratio, short squeeze, side project, systematic trading, tail risk, transaction costs

Once there has been enough price movement to avoid getting stopped out artificially, I will put my stop in. It is essential to have that protection on because once you have a position, there is always the possibility of news coming out adverse to your position, and you may not be able to get out quickly enough. Having a stop in eliminates that tail risk. When did you start using stops religiously? After I had my worst daily loss, a 24% hit. When was that, and what happened? The trade occurred in June 2013, and it was a comedy of errors. The ECB had been touting the possibility of negative interest rates for some time. It was my belief that if and when they went to negative interest rates, it would be very bearish for the euro.

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And I was determined not to miss out this time, so I foolishly decided to allocate 120% of capital to them. The new systems did very well for the first four months of the year, gaining over 25%. My cumulative profits even hit a new high in May 2015. However, the rest of the year was a disaster. That is when I discovered the tail risk inherent in mean reversion. First, there was a hit on the short side when I was shorting Chinese ADRs, and they just kept on going up. Then I took another hit after Hillary Clinton came out with a tweet about regulating drug prices, and the biotech sector fell apart. My mean-reversion system kept on buying these stocks, and they kept on going down.

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., an equity curve moving below its moving average) in each strategy, even if it reduces profits in a backtest. This rule can significantly limit losses if a system stops working, as can and will happen. The more strategies you run, the easier it is emotionally to turn one off. In this sense, this rule reinforces the importance of rule #1. The tail-risk in a mean-reversion strategy is more likely to come from a cluster of medium-sized losing trades rather than from the potential for a huge loss in an individual trade. Allow for the possibility that the serial correlation of losses is probably understated in any backtest. It is possible to succeed quickly, continue to do well for 15 years, and then have a near-career-ending drawdown.

The Long Good Buy: Analysing Cycles in Markets by Peter Oppenheimer

Alan Greenspan, asset allocation, banking crisis, banks create money, barriers to entry, behavioural economics, benefit corporation, Berlin Wall, Big bang: deregulation of the City of London, Black Monday: stock market crash in 1987, book value, Bretton Woods, business cycle, buy and hold, Cass Sunstein, central bank independence, collective bargaining, computer age, credit crunch, data science, debt deflation, decarbonisation, diversification, dividend-yielding stocks, equity premium, equity risk premium, Fall of the Berlin Wall, financial engineering, financial innovation, fixed income, Flash crash, foreign exchange controls, forward guidance, Francis Fukuyama: the end of history, general purpose technology, gentrification, geopolitical risk, George Akerlof, Glass-Steagall Act, household responsibility system, housing crisis, index fund, invention of the printing press, inverted yield curve, Isaac Newton, James Watt: steam engine, Japanese asset price bubble, joint-stock company, Joseph Schumpeter, Kickstarter, Kondratiev cycle, liberal capitalism, light touch regulation, liquidity trap, Live Aid, low interest rates, market bubble, Mikhail Gorbachev, mortgage debt, negative equity, Network effects, new economy, Nikolai Kondratiev, Nixon shock, Nixon triggered the end of the Bretton Woods system, oil shock, open economy, Phillips curve, price stability, private sector deleveraging, Productivity paradox, quantitative easing, railway mania, random walk, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Solow, Ronald Reagan, Savings and loan crisis, savings glut, secular stagnation, Shenzhen special economic zone , Simon Kuznets, South Sea Bubble, special economic zone, stocks for the long run, tail risk, Tax Reform Act of 1986, technology bubble, The Great Moderation, too big to fail, total factor productivity, trade route, tulip mania, yield curve

It is a phase when earnings are still rising (modestly) but prices fall sharply, on average by over 40%, with valuations contracting by a similar amount. In the hope phase, investors start to anticipate the end of recession or crisis as the rate of deterioration in data slows (things are still bad but are not deteriorating), and this visibility caps the potential downside risk. Investors respond to the lower tail risk by increasingly accepting lower future expected returns (and higher valuations); the equity risk premium declines and valuations rise as the ‘fear of missing out’ often drives investor sentiment. Although volatility is still high, it tends to fall towards the end of the hope phase as activity data start to stabilise, even at a low rate.

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US monetary policy and the global financial cycle. NBER Working Paper No. 21722. Miranda-Agrippino, S., and Rey, H. (2015b). World asset markets and the global financial cycle. CEPR Discussion Papers 10936. Mueller-Glissmann, C., Rizzi, A., Wright, I., and Oppenheimer, P. (2018). The balanced bear – Part 2: Chasing your tail risk and balancing the bear. London, UK: Goldman Sachs Global Investment Research. Mukunda, G. (2018). The social and political costs of the financial crisis, 10 years later. The Harvard Business Review [online]. Available at https://hbr.org/2018/09/the-social-and-political-costs-of-the-financial-crisis-10-years-later Musson, A.

How Markets Fail: The Logic of Economic Calamities by John Cassidy

Abraham Wald, Alan Greenspan, Albert Einstein, An Inconvenient Truth, Andrei Shleifer, anti-communist, AOL-Time Warner, asset allocation, asset-backed security, availability heuristic, bank run, banking crisis, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Black Monday: stock market crash in 1987, Black-Scholes formula, Blythe Masters, book value, Bretton Woods, British Empire, business cycle, capital asset pricing model, carbon tax, Carl Icahn, centralized clearinghouse, collateralized debt obligation, Columbine, conceptual framework, Corn Laws, corporate raider, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, Daniel Kahneman / Amos Tversky, debt deflation, different worldview, diversification, Elliott wave, Eugene Fama: efficient market hypothesis, financial deregulation, financial engineering, financial innovation, Financial Instability Hypothesis, financial intermediation, full employment, Garrett Hardin, George Akerlof, Glass-Steagall Act, global supply chain, Gunnar Myrdal, Haight Ashbury, hiring and firing, Hyman Minsky, income per capita, incomplete markets, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kickstarter, laissez-faire capitalism, Landlord’s Game, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, low interest rates, mandelbrot fractal, margin call, market bubble, market clearing, mental accounting, Mikhail Gorbachev, military-industrial complex, Minsky moment, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Myron Scholes, Naomi Klein, negative equity, Network effects, Nick Leeson, Nixon triggered the end of the Bretton Woods system, Northern Rock, paradox of thrift, Pareto efficiency, Paul Samuelson, Phillips curve, Ponzi scheme, precautionary principle, price discrimination, price stability, principal–agent problem, profit maximization, proprietary trading, quantitative trading / quantitative finance, race to the bottom, Ralph Nader, RAND corporation, random walk, Renaissance Technologies, rent control, Richard Thaler, risk tolerance, risk-adjusted returns, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, Savings and loan crisis, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical model, subprime mortgage crisis, tail risk, Tax Reform Act of 1986, technology bubble, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, too big to fail, Tragedy of the Commons, transaction costs, Two Sigma, unorthodox policies, value at risk, Vanguard fund, Vilfredo Pareto, wealth creators, zero-sum game

Turning to other factors that had made the financial system more vulnerable, Rajan brought up incentive-based compensation. Almost all senior financiers now receive bonuses that are tied to the investment returns their businesses generate. Since these returns are correlated with risks, Rajan pointed out, there are “perverse incentives” for managers and firms to take on more risks, especially so-called tail risks—events that occur with a very low probability but that can have disastrous consequences. The tendency for investors and traders to ape each other’s strategies, a phenomenon known as herding, was another potentially destabilizing factor, Rajan said, because it led people to buy assets even if they considered them overvalued.

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Almost all statistical models are basically extrapolative; they take past data and project forward from it. Under some circumstances, this can work; under others, it can prove disastrous. During a period such as 2002–2006, when the markets were unusually tranquil, virtually any model would have understated the “tail risk” of a big move in one direction or another. There simply wasn’t enough variation in the data to generate anything but relatively benign forecasts. VAR models also tend to exaggerate the benefits of diversification. Typically, a big bank such as Citigroup or Wells Fargo has a wide variety of assets on its books: consumer loans, corporate loans, Treasury bonds, high-grade corporate bonds, junk bonds, mortgage bonds, stocks, currencies, commodities, and all manner of derivatives.

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This type of reward structure can mitigate incentive problems, but it doesn’t eliminate them. Clever traders will try to game the system by taking risks that aren’t reflected in the benchmark they are judged against. Take the practice of writing credit default swaps. In exchange for receiving a positive return most of the time, the providers of credit protection bear the hidden “tail risk” of a low probability of a very bad outcome. “These strategies have the appearance of producing very high alphas [high return for low risk], so managers have an incentive to load up on them,” says Raghuram Rajan, the economist whose 2005 warnings I detailed in the introduction. “Every once in a while, however, they will blow up.”

Refuge: Transforming a Broken Refugee System by Alexander Betts, Paul Collier

Alvin Roth, anti-communist, centre right, charter city, corporate social responsibility, Donald Trump, failed state, Filter Bubble, global supply chain, informal economy, it's over 9,000, Kibera, mass immigration, megacity, middle-income trap, mobile money, Mohammed Bouazizi, mutually assured destruction, open borders, Peace of Westphalia, peer-to-peer, race to the bottom, randomized controlled trial, rising living standards, risk/return, school choice, special economic zone, structural adjustment programs, tail risk, trade route, urban planning, zero-sum game

As ISIS built a brutal mini-state in northern Iraq, it set its sights upon an invasion of Syria. CRYSTALLIZING MASS VIOLENCE Many societies are fragile, but only in some of them do the risks crystallize into the mass violence that gives rise to displacement. As with other forms of organized violence, what drives the numbers are the tail risks: the outliers. This can make it misleading to talk about ‘trends’. Totals are dominated by a few low-probability events that nevertheless happened. It is tempting to discern the unavoidable march of history in such numbers, but the world is not like that.8 Refuge is what statisticians call a ‘fat tails’ phenomenon: a very low likelihood event but with catastrophic consequences that create a thick tail to a distribution curve.9 The lists of fragile states typically include between forty and sixty countries around the world but only three of them account for half of all the world’s current displacement.

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Maddalena Agnoli, Lisa Chauvet, Paul Collier, Anke Hoeffler, and Sultan Mehmood, ‘Democracy’s Achilles Heel: Structural Causes of Flawed Elections and Their Consequences for Citizen Trust’, unpublished paper, CSAE. 7. See Paul Collier, ‘The Institutional and Psychological Foundations of Natural Resource Policies’, Journal of Development Studies (forthcoming). 8. See P. Cirillo and N. N. Taleb, ‘On the Statistical Properties and Tail Risk of Violent Conflicts’, Physica A: Statistical Mechanics and its Applications, 452 (2016): 29–45. 9. See, for example, Ian Bremmer and Preston Keat, The Fat Tail: The Power of Political Knowledge in an Uncertain World (New York, 2010: Oxford University Press). 10. By ‘honeypot’ country, we mean a high-income economy, defined by the World Bank as one with a GNP/capita above $12,475 in 2015. 11.

Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

Ada Lovelace, AI winter, Alignment Problem, AlphaGo, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, artificial general intelligence, autonomous vehicles, backpropagation, Bernie Sanders, Big Tech, Boston Dynamics, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, cognitive dissonance, computer age, computer vision, Computing Machinery and Intelligence, dark matter, deep learning, DeepMind, Demis Hassabis, Douglas Hofstadter, driverless car, Elon Musk, en.wikipedia.org, folksonomy, Geoffrey Hinton, Gödel, Escher, Bach, I think there is a world market for maybe five computers, ImageNet competition, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, license plate recognition, machine translation, Mark Zuckerberg, natural language processing, Nick Bostrom, Norbert Wiener, ought to be enough for anybody, paperclip maximiser, pattern recognition, performance metric, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rodney Brooks, self-driving car, sentiment analysis, Silicon Valley, Singularitarianism, Skype, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, tacit knowledge, tail risk, TED Talk, the long tail, theory of mind, There's no reason for any individual to have a computer in his home - Ken Olsen, trolley problem, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, world market for maybe five computers

We tend to anthropomorphize AI systems: we impute human qualities to them and end up overestimating the extent to which these systems can actually be fully trusted. The economist Sendhil Mullainathan, in writing about the dangers of AI, cited the long-tail phenomenon (which I described in chapter 6) in his notion of “tail risk”: We should be afraid. Not of intelligent machines. But of machines making decisions that they do not have the intelligence to make. I am far more afraid of machine stupidity than of machine intelligence. Machine stupidity creates a tail risk. Machines can make many many good decisions and then one day fail spectacularly on a tail event that did not appear in their training data. This is the difference between specific and general intelligence.20 Or as the AI researcher Pedro Domingos so memorably put it, “People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.”21 I worry about AI’s lack of reliability.

Beyond the 4% Rule: The Science of Retirement Portfolios That Last a Lifetime by Abraham Okusanya

asset allocation, diversification, diversified portfolio, high net worth, longitudinal study, low interest rates, market design, mental accounting, Paul Samuelson, quantitative easing, risk tolerance, risk-adjusted returns, Robert Shiller, seminal paper, tail risk, The 4% rule, transaction costs, William Bengen

Success rate of less than 60% could be red, between 61% and 80% is amber and between 80% and 99% is green. Monte Carlo simulations have their own weaknesses. The chief one is that returns in any one year are entirely independent of previous years. The implication is that Monte Carlo analysis tends to overstate tail risk, compared to the actual historical worst case. This is because Monte Carlo simulations don’t account for mean reversion, which is a key characteristic of most asset classes. As financial adviser and researcher Derek Tharp PhD notes: ‘Whether the prior year was flat, saw a slight increase, or a raging bull market, Monte Carlo analysis assumes that the odds of a bear market decline the following year are exactly the same.

The Acquirer's Multiple: How the Billionaire Contrarians of Deep Value Beat the Market by Tobias E. Carlisle

activist fund / activist shareholder / activist investor, book value, business cycle, Carl Icahn, cognitive dissonance, corporate governance, corporate raider, Jeff Bezos, Mark Spitznagel, Market Wizards by Jack D. Schwager, Paul Graham, Peter Thiel, Richard Thaler, shareholder value, stock buybacks, tail risk, Tim Cook: Apple

We’ll look at the details of actual stock picks by billionaire deep-value investors: •Warren Buffett •Carl Icahn •Daniel Loeb •David Einhorn We’ll see the strategies of Buffett and his teacher, Benjamin Graham, and other contrarians, including: •billionaire trader Paul Tudor-Jones •venture capitalist billionaire Peter Thiele •global macroinvestor billionaire Michael Steinhardt •billionaire tail-risk hedger Mark Spitznagel I wrote this book so you can read it in a couple of hours. It’s written for my kids, family, and friends, for people who are smart but not stock-market people. That means it’s written in plain English. Where I need to define a stock-market term, I’ve tried to do it as simply as possible.

The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma by Mustafa Suleyman

"World Economic Forum" Davos, 23andMe, 3D printing, active measures, Ada Lovelace, additive manufacturing, agricultural Revolution, AI winter, air gap, Airbnb, Alan Greenspan, algorithmic bias, Alignment Problem, AlphaGo, Alvin Toffler, Amazon Web Services, Anthropocene, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, ASML, autonomous vehicles, backpropagation, barriers to entry, basic income, benefit corporation, Big Tech, biodiversity loss, bioinformatics, Bletchley Park, Blitzscaling, Boston Dynamics, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, ChatGPT, choice architecture, circular economy, classic study, clean tech, cloud computing, commoditize, computer vision, coronavirus, corporate governance, correlation does not imply causation, COVID-19, creative destruction, CRISPR, critical race theory, crowdsourcing, cryptocurrency, cuban missile crisis, data science, decarbonisation, deep learning, deepfake, DeepMind, deindustrialization, dematerialisation, Demis Hassabis, disinformation, drone strike, drop ship, dual-use technology, Easter island, Edward Snowden, effective altruism, energy transition, epigenetics, Erik Brynjolfsson, Ernest Rutherford, Extinction Rebellion, facts on the ground, failed state, Fairchild Semiconductor, fear of failure, flying shuttle, Ford Model T, future of work, general purpose technology, Geoffrey Hinton, global pandemic, GPT-3, GPT-4, hallucination problem, hive mind, hype cycle, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, Internet of things, invention of the wheel, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kickstarter, lab leak, large language model, Law of Accelerating Returns, Lewis Mumford, license plate recognition, lockdown, machine readable, Marc Andreessen, meta-analysis, microcredit, move 37, Mustafa Suleyman, mutually assured destruction, new economy, Nick Bostrom, Nikolai Kondratiev, off grid, OpenAI, paperclip maximiser, personalized medicine, Peter Thiel, planetary scale, plutocrats, precautionary principle, profit motive, prompt engineering, QAnon, quantum entanglement, ransomware, Ray Kurzweil, Recombinant DNA, Richard Feynman, Robert Gordon, Ronald Reagan, Sam Altman, Sand Hill Road, satellite internet, Silicon Valley, smart cities, South China Sea, space junk, SpaceX Starlink, stealth mode startup, stem cell, Stephen Fry, Steven Levy, strong AI, synthetic biology, tacit knowledge, tail risk, techlash, techno-determinism, technoutopianism, Ted Kaczynski, the long tail, The Rise and Fall of American Growth, Thomas Malthus, TikTok, TSMC, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, warehouse robotics, William MacAskill, working-age population, world market for maybe five computers, zero day

They will offer extraordinary new medical advances and clean energy breakthroughs, creating not just new businesses but new industries and quality of life improvements in almost every imaginable area. And yet alongside these benefits, AI, synthetic biology, and other advanced forms of technology produce tail risks on a deeply concerning scale. They could present an existential threat to nation-states—risks so profound they might disrupt or even overturn the current geopolitical order. They open pathways to immense AI-empowered cyberattacks, automated wars that could devastate countries, engineered pandemics, and a world subject to unexplainable and yet seemingly omnipotent forces.

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It barely seems real on first encounter. In all those many discussions about AI and regulation, I’ve been struck by how hard it is, compared with a host of existing or looming challenges, to convey exactly why the risks in this book need to be taken seriously, why they aren’t just nearly irrelevant tail risks or the province of science fiction. One challenge in even beginning to have this conversation is that technology, in the popular imagination, has become associated with a narrow band of often superfluous applications. “Technology” now mostly means social media platforms and wearable gadgets to measure our steps and heart rate.

Capital Allocators: How the World’s Elite Money Managers Lead and Invest by Ted Seides

Albert Einstein, asset allocation, behavioural economics, business cycle, coronavirus, COVID-19, crowdsourcing, data science, deliberate practice, diversification, Everything should be made as simple as possible, fake news, family office, fixed income, high net worth, hindsight bias, impact investing, implied volatility, impulse control, index fund, Kaizen: continuous improvement, Lean Startup, loss aversion, Paradox of Choice, passive investing, Ralph Waldo Emerson, risk tolerance, Sharpe ratio, sovereign wealth fund, tail risk, The Wisdom of Crowds, Toyota Production System, zero-sum game

Timing peaks perfectly is impossible, but some allocators act when they sense markets are fraught with risk. These actions start with an increase in cash balances, where the only cost is opportunity cost. Allocators then tweak the position sizing or composition of the manager roster, favoring those with lower risk profiles or adding a manager specializing in tail risk protection. Additionally, CIOs create direct programs to hedge downside tails through put options, futures, or swaps on equity or fixed income indexes. 3. Co-investments CIOs take baby steps towards direct investing through co-investments with managers in their portfolio. The rationale for incorporating co-investments varies across allocators.

Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined by Lasse Heje Pedersen

activist fund / activist shareholder / activist investor, Alan Greenspan, algorithmic trading, Andrei Shleifer, asset allocation, backtesting, bank run, banking crisis, barriers to entry, Bear Stearns, behavioural economics, Black-Scholes formula, book value, Brownian motion, business cycle, buy and hold, buy low sell high, buy the rumour, sell the news, capital asset pricing model, commodity trading advisor, conceptual framework, corporate governance, credit crunch, Credit Default Swap, currency peg, currency risk, David Ricardo: comparative advantage, declining real wages, discounted cash flows, diversification, diversified portfolio, Emanuel Derman, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, financial engineering, fixed income, Flash crash, floating exchange rates, frictionless, frictionless market, global macro, Gordon Gekko, implied volatility, index arbitrage, index fund, interest rate swap, junk bonds, late capitalism, law of one price, Long Term Capital Management, low interest rates, managed futures, margin call, market clearing, market design, market friction, Market Wizards by Jack D. Schwager, merger arbitrage, money market fund, mortgage debt, Myron Scholes, New Journalism, paper trading, passive investing, Phillips curve, price discovery process, price stability, proprietary trading, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, random walk, Reminiscences of a Stock Operator, Renaissance Technologies, Richard Thaler, risk free rate, risk-adjusted returns, risk/return, Robert Shiller, selection bias, shareholder value, Sharpe ratio, short selling, short squeeze, SoftBank, sovereign wealth fund, statistical arbitrage, statistical model, stocks for the long run, stocks for the long term, survivorship bias, systematic trading, tail risk, technology bubble, time dilation, time value of money, total factor productivity, transaction costs, two and twenty, value at risk, Vanguard fund, yield curve, zero-coupon bond

Fourth, the use of leverage means that a hedge fund cannot always “ride out” a drawdown; it must be ready to react before creditors pull their financing or investors pull their capital. Portfolio construction should rely on continuously updated measures of risk and should ensure that the risk taken is at an appropriate level given the opportunities. The risk management overlay must simultaneously ensure that the risk never exceeds certain limits, manage the downside tail risk, and limit the risk of large drawdowns. 4.1. PORTFOLIO CONSTRUCTION Active investors differ a great deal in their portfolio construction, with some relying on rules and intuition while others use computer algorithms to perform a formal portfolio optimization. However, there are some general principles that most successful hedge funds adhere to: • The first principle of portfolio construction is diversification.

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To compute the volatility of a large portfolio, hedge funds need to account for correlations across assets, which can be accomplished by simulating the overall portfolio or by using a statistical model such as a factor model. Another measure of risk is value-at-risk (VaR), which attempts to capture tail risk (non-normality). The VaR measures the maximum loss with a certain confidence, as seen in figure 4.1 below. For example, the VaR is the most that you can lose with a 95% or 99% confidence. For instance, a hedge fund has a one-day 95% VaR of $10 million if A simple way to estimate VaR is to line up past returns, sort them by magnitude, and find a return that has 5% worse days and 95% better days.

The Little Book of Hedge Funds by Anthony Scaramucci

Alan Greenspan, Andrei Shleifer, asset allocation, Bear Stearns, Bernie Madoff, business process, carried interest, corporate raider, Credit Default Swap, diversification, diversified portfolio, Donald Trump, Eugene Fama: efficient market hypothesis, fear of failure, financial engineering, fixed income, follow your passion, global macro, Gordon Gekko, high net worth, index fund, it's over 9,000, John Bogle, John Meriwether, Long Term Capital Management, mail merge, managed futures, margin call, mass immigration, merger arbitrage, Michael Milken, money market fund, Myron Scholes, NetJets, Ponzi scheme, profit motive, proprietary trading, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk-adjusted returns, risk/return, Ronald Reagan, Saturday Night Live, Sharpe ratio, short selling, short squeeze, Silicon Valley, tail risk, Thales and the olive presses, Thales of Miletus, the new new thing, too big to fail, transaction costs, two and twenty, uptick rule, Vanguard fund, Y2K, Yogi Berra, zero-sum game

Why are hedge funds interesting to institutional investors? Because in a world where returns on traditional investments are low and pension funds have large unfunded liabilities, the search for the holy grail of alpha can diversify risk and provide superior returns. However, we also know that when risk is off rather than on—when tail risk implies high risk aversion—all risky assets become perfectly correlated and there is nowhere to hide, even among hedge funds. So, again, finding better managers becomes key. Finally, what is the future of the hedge fund industry? Most likely a shake-up: thousands of smaller and under-performing funds have disappeared in the past few years while the more successful players are consolidating and becoming bigger.

MONEY Master the Game: 7 Simple Steps to Financial Freedom by Tony Robbins

"World Economic Forum" Davos, 3D printing, active measures, activist fund / activist shareholder / activist investor, addicted to oil, affirmative action, Affordable Care Act / Obamacare, Albert Einstein, asset allocation, backtesting, Bear Stearns, behavioural economics, bitcoin, Black Monday: stock market crash in 1987, buy and hold, Carl Icahn, clean water, cloud computing, corporate governance, corporate raider, correlation does not imply causation, Credit Default Swap, currency risk, Dean Kamen, declining real wages, diversification, diversified portfolio, Donald Trump, estate planning, fear of failure, fiat currency, financial independence, fixed income, forensic accounting, high net worth, index fund, Internet of things, invention of the wheel, it is difficult to get a man to understand something, when his salary depends on his not understanding it, Jeff Bezos, John Bogle, junk bonds, Kenneth Rogoff, lake wobegon effect, Lao Tzu, London Interbank Offered Rate, low interest rates, Marc Benioff, market bubble, Michael Milken, money market fund, mortgage debt, Neil Armstrong, new economy, obamacare, offshore financial centre, oil shock, optical character recognition, Own Your Own Home, passive investing, profit motive, Ralph Waldo Emerson, random walk, Ray Kurzweil, Richard Thaler, risk free rate, risk tolerance, riskless arbitrage, Robert Shiller, Salesforce, San Francisco homelessness, self-driving car, shareholder value, Silicon Valley, Skype, Snapchat, sovereign wealth fund, stem cell, Steve Jobs, subscription business, survivorship bias, tail risk, TED Talk, telerobotics, The 4% rule, The future is already here, the rule of 72, thinkpad, tontine, transaction costs, Upton Sinclair, Vanguard fund, World Values Survey, X Prize, Yogi Berra, young professional, zero-sum game

TR: Wow. KB: But my theory is, I have always said to our investors, “If it moves two hundred basis points, it’s going to move fifteen hundred.” TR: Right. KB: It’s either going to sit still and do nothing, or it’s going to blow apart. TR: This all plays into your idea of “tail risk.” Tell me what tail risk is; not many investors focus on it. KB: If you look at what I’m doing, I’m spending three or four basis points a year on Japan. That’s four-hundredths of 1%, okay? If I’m right about the binary nature of the potential outcome of the situation there, these bonds are going to trade at 20% yields or higher.

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What happens too often is people start with a diversified plan, but as market conditions change, they try to time the markets so they are getting either more upside opportunities or better protection in unfavorable conditions. But that’s a very dangerous thing to do because it’s impossible to predict every scenario. What a well-diversified portfolio does is help you capture those tail risks [risks that can bring great rewards], and if you stick to that plan, you can create a tremendous amount of wealth over the long term. TR: What are some of the biggest opportunities for investors today and the largest challenges that they need to prepare for? ME: I think that we will look back at the time that we’re living in right now and say, “That was a great time to have invested.”

The Joys of Compounding: The Passionate Pursuit of Lifelong Learning, Revised and Updated by Gautam Baid

Abraham Maslow, activist fund / activist shareholder / activist investor, Airbnb, Alan Greenspan, Albert Einstein, Alvin Toffler, Andrei Shleifer, asset allocation, Atul Gawande, availability heuristic, backtesting, barriers to entry, beat the dealer, Benoit Mandelbrot, Bernie Madoff, bitcoin, Black Swan, book value, business process, buy and hold, Cal Newport, Cass Sunstein, Checklist Manifesto, Clayton Christensen, cognitive dissonance, collapse of Lehman Brothers, commoditize, corporate governance, correlation does not imply causation, creative destruction, cryptocurrency, Daniel Kahneman / Amos Tversky, deep learning, delayed gratification, deliberate practice, discounted cash flows, disintermediation, disruptive innovation, Dissolution of the Soviet Union, diversification, diversified portfolio, dividend-yielding stocks, do what you love, Dunning–Kruger effect, Edward Thorp, Elon Musk, equity risk premium, Everything should be made as simple as possible, fear index, financial independence, financial innovation, fixed income, follow your passion, framing effect, George Santayana, Hans Rosling, hedonic treadmill, Henry Singleton, hindsight bias, Hyman Minsky, index fund, intangible asset, invention of the wheel, invisible hand, Isaac Newton, it is difficult to get a man to understand something, when his salary depends on his not understanding it, Jeff Bezos, John Bogle, Joseph Schumpeter, junk bonds, Kaizen: continuous improvement, Kickstarter, knowledge economy, Lao Tzu, Long Term Capital Management, loss aversion, Louis Pasteur, low interest rates, Mahatma Gandhi, mandelbrot fractal, margin call, Mark Zuckerberg, Market Wizards by Jack D. Schwager, Masayoshi Son, mental accounting, Milgram experiment, moral hazard, Nate Silver, Network effects, Nicholas Carr, offshore financial centre, oil shock, passive income, passive investing, pattern recognition, Peter Thiel, Ponzi scheme, power law, price anchoring, quantitative trading / quantitative finance, Ralph Waldo Emerson, Ray Kurzweil, Reminiscences of a Stock Operator, reserve currency, Richard Feynman, Richard Thaler, risk free rate, risk-adjusted returns, Robert Shiller, Savings and loan crisis, search costs, shareholder value, six sigma, software as a service, software is eating the world, South Sea Bubble, special economic zone, Stanford marshmallow experiment, Steve Jobs, Steven Levy, Steven Pinker, stocks for the long run, subscription business, sunk-cost fallacy, systems thinking, tail risk, Teledyne, the market place, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, time value of money, transaction costs, tulip mania, Upton Sinclair, Walter Mischel, wealth creators, Yogi Berra, zero-sum game

In one of her past interviews, Alice Schroeder discussed Warren Buffett’s use of “disqualifying features” as one of his checklist items: Typically, and this is not well understood, his way of thinking is that there are disqualifying features to an investment. So he rifles through and as soon as you hit one of those it’s done. Doesn’t like the CEO, forget it. Too much tail risk, forget it. Low-margin business, forget it. Many people would try to see whether a balance of other factors made up for these things. He doesn’t analyze from A to Z; it’s a time-waster [emphasis added].1 Charlie Munger has often been credited with popularizing the use of checklists in investing.

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We all contemplate and understand the things that happen within three standard deviations, but everything important in financial history takes place outside those three standard deviations. Still, many smart people do not consider these kinds of rare events to be even remotely plausible. In addition, complex mathematical models that can purportedly manage fat-tail risks create the illusion of control. Consequently, these people express this overconfidence in their beliefs by betting the entire house on their preferred bet and piling up tons of leverage. Ultimately, this blind reliance on only the documented past leads to ruin. Failure often comes from a failure to imagine failure.

The Captured Economy: How the Powerful Enrich Themselves, Slow Down Growth, and Increase Inequality by Brink Lindsey

Airbnb, Asian financial crisis, bank run, barriers to entry, Bernie Sanders, Build a better mousetrap, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, Carmen Reinhart, Cass Sunstein, collective bargaining, creative destruction, Credit Default Swap, crony capitalism, Daniel Kahneman / Amos Tversky, David Brooks, diversified portfolio, Donald Trump, Edward Glaeser, endogenous growth, experimental economics, experimental subject, facts on the ground, financial engineering, financial innovation, financial intermediation, financial repression, hiring and firing, Home mortgage interest deduction, housing crisis, income inequality, informal economy, information asymmetry, intangible asset, inventory management, invisible hand, Jones Act, Joseph Schumpeter, Kenneth Rogoff, Kevin Kelly, knowledge worker, labor-force participation, Long Term Capital Management, low skilled workers, Lyft, Mark Zuckerberg, market fundamentalism, mass immigration, mass incarceration, medical malpractice, Menlo Park, moral hazard, mortgage debt, Network effects, patent troll, plutocrats, principal–agent problem, regulatory arbitrage, rent control, rent-seeking, ride hailing / ride sharing, Robert Metcalfe, Robert Solow, Ronald Reagan, Savings and loan crisis, Silicon Valley, Silicon Valley ideology, smart cities, software patent, subscription business, tail risk, tech bro, too big to fail, total factor productivity, trade liberalization, tragedy of the anticommons, Tragedy of the Commons, transaction costs, tulip mania, Tyler Cowen, Uber and Lyft, uber lyft, Washington Consensus, white picket fence, winner-take-all economy, women in the workforce

Specifically, in judging the trade-off between risk and reward when choosing how much debt to take on, financial firms may look only at their own individual situation and not take account of the destabilizing effects of aggregate leverage in the financial system.21 Given the fact that banks borrow from each other and also considering the risk of contagion during bad times, levels of leverage that might be fine for a single institution become problematic if more widespread. This market failure may be exacerbated by compensation practices in the financial sector, in which return on equity is a major factor in determining executives’ compensation. Executives therefore have a personal incentive to lever as much as possible, especially if the tail risks lie years down the road well after fat bonuses have already been paid. Instead of correcting market failures that lead to excessive risk-taking, regulatory policy actually makes matters worse. Specifically, the government’s efforts to reduce the harm caused when financial firms fail ends up subsidizing the heavy reliance on debt that makes firm failure more likely.

Extreme Money: Masters of the Universe and the Cult of Risk by Satyajit Das

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", "there is no alternative" (TINA), "World Economic Forum" Davos, affirmative action, Alan Greenspan, Albert Einstein, algorithmic trading, Andy Kessler, AOL-Time Warner, Asian financial crisis, asset allocation, asset-backed security, bank run, banking crisis, banks create money, Basel III, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, bonus culture, book value, Bretton Woods, BRICs, British Empire, business cycle, buy the rumour, sell the news, capital asset pricing model, carbon credits, Carl Icahn, Carmen Reinhart, carried interest, Celtic Tiger, clean water, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, Daniel Kahneman / Amos Tversky, deal flow, debt deflation, Deng Xiaoping, deskilling, discrete time, diversification, diversified portfolio, Doomsday Clock, Dr. Strangelove, Dutch auction, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, eurozone crisis, Everybody Ought to Be Rich, Fall of the Berlin Wall, financial engineering, financial independence, financial innovation, financial thriller, fixed income, foreign exchange controls, full employment, Glass-Steagall Act, global reserve currency, Goldman Sachs: Vampire Squid, Goodhart's law, Gordon Gekko, greed is good, Greenspan put, happiness index / gross national happiness, haute cuisine, Herman Kahn, high net worth, Hyman Minsky, index fund, information asymmetry, interest rate swap, invention of the wheel, invisible hand, Isaac Newton, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", job automation, Johann Wolfgang von Goethe, John Bogle, John Meriwether, joint-stock company, Jones Act, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, laissez-faire capitalism, load shedding, locking in a profit, Long Term Capital Management, Louis Bachelier, low interest rates, margin call, market bubble, market fundamentalism, Market Wizards by Jack D. Schwager, Marshall McLuhan, Martin Wolf, mega-rich, merger arbitrage, Michael Milken, Mikhail Gorbachev, Milgram experiment, military-industrial complex, Minsky moment, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, mutually assured destruction, Myron Scholes, Naomi Klein, National Debt Clock, negative equity, NetJets, Network effects, new economy, Nick Leeson, Nixon shock, Northern Rock, nuclear winter, oil shock, Own Your Own Home, Paul Samuelson, pets.com, Philip Mirowski, Phillips curve, planned obsolescence, plutocrats, Ponzi scheme, price anchoring, price stability, profit maximization, proprietary trading, public intellectual, quantitative easing, quantitative trading / quantitative finance, Ralph Nader, RAND corporation, random walk, Ray Kurzweil, regulatory arbitrage, Reminiscences of a Stock Operator, rent control, rent-seeking, reserve currency, Richard Feynman, Richard Thaler, Right to Buy, risk free rate, risk-adjusted returns, risk/return, road to serfdom, Robert Shiller, Rod Stewart played at Stephen Schwarzman birthday party, rolodex, Ronald Reagan, Ronald Reagan: Tear down this wall, Satyajit Das, savings glut, shareholder value, Sharpe ratio, short selling, short squeeze, Silicon Valley, six sigma, Slavoj Žižek, South Sea Bubble, special economic zone, statistical model, Stephen Hawking, Steve Jobs, stock buybacks, survivorship bias, tail risk, Teledyne, The Chicago School, The Great Moderation, the market place, the medium is the message, The Myth of the Rational Market, The Nature of the Firm, the new new thing, The Predators' Ball, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, trickle-down economics, Turing test, two and twenty, Upton Sinclair, value at risk, Yogi Berra, zero-coupon bond, zero-sum game

Sharpe ratios are ex post (based on actual risk) rather than ex ante (expected risk). Actual returns should be compared to expected risk at the time the position was taken. Insufficient attention is paid to the asymmetry of hedge fund returns, which do not follow the familiar bell-shaped normal distribution. Risk models grossly underestimate tail risk, exposure to large price moves. Traders arb internal risk metrics to inflate risk-adjusted returns to increase bonuses. Real hedge fund risks—correlation, liquidity, complexity, and model risk—are not measured properly. If the portfolio of long and short positions is perfectly balanced and prices move identically, then the gains and losses should cancel out, reducing risk but earning zero return.

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See also mortgages shorting (2005/2006), 256 subsidies, 334, 348 Suma Oriental, 82 Sumitomo, 227 Summers, Lawrence, 116, 129, 214, 300, 304, 315 Sunday Times, 364 super jumbo loans, 182 Super Return annual industry conference, 162 super senior tranches, 175 supply of assets, 267 survivorship bias, 243 suspension of deep-water drilling, 362 Suze Orman Show, The, 93 Suze Orman’s Financial Freedom, 93 swaps correlation, 255 credit default swaps (CDS), 232, 237 dispersion, 255 Fiat, 222-223 first-to-default (FtD), 220-221 gamma, 255 total return swap (TRS), 209 Swensen, David, 124 Swift, Jonathon, 130 Sydney Airport, 159 synchronous lateral excitation, 273 synthetic securitization, 173, 176 systematic risk, 118 T TAC (target amortization class) bonds, 178 TAF (term auction facility), 340 tail risk, 246 Tainter, Joseph, 349 takeovers (risk arb), 242 Taleb, Nicholas Nassim, 126, 246 Talking Heads, The, 46 taming risk, 120-122 Tang dynasty, 351 tansu savings, 39 Tao Jones Averages, The, 96 TARDIS (Time And Relative Dimension(s) In Space) trades, 217-218 target redemption forwards, 217 Tavakoli, Janet, 177 taxes avoidance, 48-49 cuts, 348 Dubai International Financial Centre (DIFC), 82-83 favorable regimes, 41 leveraged buyouts (LBOs), 138 VAT (value added tax), 262 tchotchkes, 162 Teenage Cancer Trust, 262 Teledyn, 60 television, financial news, 91-99 Templars, 32 temporary suspension of deep-water drilling, 362 Terra Firma Capital Partners, 154, 157, 162, 165 terrorism, 44 Texas Instruments (TI), 122 Texas International, 146 Texas Pacific Group, 154 Textron, 60 Thain, John, 291, 319, 330 Thaler, Richard, 126 Thatcher, Margaret, 66, 81, 158 the Government National Mortgage Association (GNMA or Ginnie Mae), 179 theoretical profits, 231 theories, bubbles, 277-278 Theory of the Leisure Class, The, 41 This American Life, 185 Thompson, Todd, 93 Thoreau, Henry David, 359 Thornton, John, 76 Thorp, Edward, 121 thought leaders, 90 thundering herd, the, 66 TICKETs (tradable interest bearing convertible to equity trust securities), 160 Tierney, John, 98 Tiger Fund, 243 Time, 45, 129 Time Warner, 58 Tobias, Seth, 322 TOBs (tender option bonds), 222 toggle loans, 154 toilets, Japanese, 38 Tokyo as a financial center, 78 tools, six sigma, 60 Torii, Mayumi, 43 Toscanini, Arturo, 157 total return swap (TRS), 209 Tourre, Fabrice, 199 toxic currency structures, 218-219 toxic waste, 172 Toynbee, Arnold, 354 Toys R Us, 155 TPG, 156 trade protectionism, 334, 349 trading, 23-24 alleys, 92 banks, 73 proprietary, 352 securities, 66 stabilization of global trade, 349 traditional banking models, 68 tranches, 169 AAA, 203 equity, 192 innovation of, 178 super senior, 175 synthetic CDOs, 174 Z, 170, 178 transfers risk, central banks, 281-282 systems, money, 22 Transformers, 278 Travelers, merger of with Citicorp, 75 Treynor, Jack, 117 trickle-down economics, 42-43 Triffin dilemma, 31 Triffin, Robert, 31 Trollope, Anthony, 173 Troubled Asset Relief Program (TARP), 340 troy ounce bars, 25.

Financial Market Meltdown: Everything You Need to Know to Understand and Survive the Global Credit Crisis by Kevin Mellyn

Alan Greenspan, asset-backed security, bank run, banking crisis, Bernie Madoff, bond market vigilante , bonus culture, Bretton Woods, business cycle, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, deal flow, disintermediation, diversification, fiat currency, financial deregulation, financial engineering, financial innovation, financial intermediation, fixed income, foreign exchange controls, Francis Fukuyama: the end of history, George Santayana, global reserve currency, Greenspan put, Home mortgage interest deduction, inverted yield curve, Isaac Newton, joint-stock company, junk bonds, Kickstarter, liquidity trap, London Interbank Offered Rate, long peace, low interest rates, margin call, market clearing, mass immigration, Money creation, money market fund, moral hazard, mortgage tax deduction, Nixon triggered the end of the Bretton Woods system, Northern Rock, offshore financial centre, paradox of thrift, pattern recognition, pension reform, pets.com, Phillips curve, plutocrats, Ponzi scheme, profit maximization, proprietary trading, pushing on a string, reserve currency, risk tolerance, risk-adjusted returns, road to serfdom, Ronald Reagan, shareholder value, Silicon Valley, South Sea Bubble, statistical model, Suez canal 1869, systems thinking, tail risk, The Great Moderation, the long tail, the new new thing, the payments system, too big to fail, value at risk, very high income, War on Poverty, We are all Keynesians now, Y2K, yield curve

See also Balance sheet lending Leverage, 4–5, 27–28, 66, 152, 160 liberalism, 125, 180, 182 Liberty and markets, 125, 179–182 LIBOR (London Interbank Offered Rate), 146, 150 ‘‘Lifeboat’’ method of bank rescue, 121 Liquidity, 30, 110, 113 Liquidity Trap, 113 Lombard Rate, 34 Lombard Street, book by Walter Bagehot, 102 Lombard Street, London, 34, 135 ‘‘long tail’’ risks, 69. See also ‘‘black swans’’ Long Term Credit Bank (LTCB), Japan, 170 195 196 Index Mackay, Charles, Great Popular Delusions and the Madness of Crowds, 136 Madoff, Bernard, 23, 175 Main Street, 1, 91, 104, 144, 176, 187 Manias, xviii–xx, 27, 109, 136–138 Manufacturers Hanover Trust Company, 148, 158 margin lending, 110 market capitalization, 47, 51, 70, 126, 159, 183 markets 19–22, 24–28, 40–41, 60, 72, 107, 111, 117–119, 124, 126–127, 150, 165–169, 175–176; 179–189; defined, xi–xx; functions, 18–28; history of, 75, 79–89, 135–145; how to play, 50–56; irrational, 52–53, 156–57; real estate market downturn and ‘‘Billy Bob’’ banking crisis, 131–32; secondary, 44 MBS (Mortgage Backed Securities), 57 Medici, 79 Meyer, Martin, Bankers, The, 143 MMA (Money Market Account), 130 models, uses in finance, 21, 25, 27, 63–65, 69–70, 99–100, 138, 152, 166, 171, 177, 182; faith in, 4, 58, 66, 68, 71–72, 74 MOF (Ministry of Finance, Japan), 167 money, creation of, 13; defined, x, xi, 117; history of, xv–xvi, 33–34, 77–80; function of, xii–xv; money supply, types of xv, xvii–xviii, 4, 8–9, 83, 92, 148, 155; value of, 4.

The Rise of Carry: The Dangerous Consequences of Volatility Suppression and the New Financial Order of Decaying Growth and Recurring Crisis by Tim Lee, Jamie Lee, Kevin Coldiron

active measures, Alan Greenspan, Asian financial crisis, asset-backed security, backtesting, bank run, Bear Stearns, Bernie Madoff, Bretton Woods, business cycle, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, collapse of Lehman Brothers, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, currency risk, debt deflation, disinformation, distributed ledger, diversification, financial engineering, financial intermediation, Flash crash, global reserve currency, implied volatility, income inequality, inflation targeting, junk bonds, labor-force participation, Long Term Capital Management, low interest rates, Lyft, margin call, market bubble, Money creation, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, negative equity, Network effects, Ponzi scheme, proprietary trading, public intellectual, purchasing power parity, quantitative easing, random walk, rent-seeking, reserve currency, rising living standards, risk free rate, risk/return, sharing economy, short selling, short squeeze, sovereign wealth fund, stock buybacks, tail risk, TikTok, Uber and Lyft, uber lyft, yield curve

In this case the con- 38 THE RISE OF CARRY tingent liabilities involved in the accumulation of risk will probably not be fully accounted for in macroeconomic debt statistics. In this example, there is an income transfer from those buying insurance to the insurer. The insurance can be considered an asset for the buyer of the insurance and a (contingent) liability for the writer. But certainly in the case of a tail risk event, no macro financial statistics will be able directly to capture the potential consequences. In other words, a carry bubble can occur without an obvious credit bubble—obvious in the sense of being clearly visible in macroeconomic statistics—and this becomes more the case as financial market innovation creates ever-greater opportunities for carry trades and therefore for the concentration of risk.

The Alpha Masters: Unlocking the Genius of the World's Top Hedge Funds by Maneet Ahuja, Myron Scholes, Mohamed El-Erian

"World Economic Forum" Davos, activist fund / activist shareholder / activist investor, Alan Greenspan, Asian financial crisis, asset allocation, asset-backed security, backtesting, Bear Stearns, Bernie Madoff, book value, Bretton Woods, business process, call centre, Carl Icahn, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, en.wikipedia.org, family office, financial engineering, fixed income, global macro, high net worth, high-speed rail, impact investing, interest rate derivative, Isaac Newton, Jim Simons, junk bonds, Long Term Capital Management, managed futures, Marc Andreessen, Mark Zuckerberg, merger arbitrage, Michael Milken, Myron Scholes, NetJets, oil shock, pattern recognition, Pershing Square Capital Management, Ponzi scheme, proprietary trading, quantitative easing, quantitative trading / quantitative finance, Renaissance Technologies, risk-adjusted returns, risk/return, rolodex, Savings and loan crisis, short selling, Silicon Valley, South Sea Bubble, statistical model, Steve Jobs, stock buybacks, systematic bias, systematic trading, tail risk, two and twenty, zero-sum game

Many observers noted that Loeb’s “poison pen” quieted during the past four years and in its absence, the investment world’s focus shifted to how Third Point has spent 95 percent of its time since its founding investing in classic special situations globally in long/short equities, corporate credit, mortgage bonds, and tail risk trades. Loeb’s rigorous investment process, honed over almost 18 years and taught intensively to his analysts, produces bottom-up investment ideas that have generated 21.5 percent net annualized returns for his investors since inception and multiplied a dollar invested on day one 26-fold. As much as Loeb’s investors love him for his returns, the public loves him for his rabble-rousing.

Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe by Greg Ip

Affordable Care Act / Obamacare, Air France Flight 447, air freight, airport security, Alan Greenspan, Asian financial crisis, asset-backed security, bank run, banking crisis, Bear Stearns, behavioural economics, Boeing 747, book value, break the buck, Bretton Woods, business cycle, capital controls, central bank independence, cloud computing, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency peg, Daniel Kahneman / Amos Tversky, diversified portfolio, double helix, endowment effect, Exxon Valdez, Eyjafjallajökull, financial deregulation, financial innovation, Financial Instability Hypothesis, floating exchange rates, foreign exchange controls, full employment, global supply chain, hindsight bias, Hyman Minsky, Joseph Schumpeter, junk bonds, Kenneth Rogoff, lateral thinking, Lewis Mumford, London Whale, Long Term Capital Management, market bubble, Michael Milken, money market fund, moral hazard, Myron Scholes, Network effects, new economy, offshore financial centre, paradox of thrift, pets.com, Ponzi scheme, proprietary trading, quantitative easing, Ralph Nader, Richard Thaler, risk tolerance, Ronald Reagan, Sam Peltzman, savings glut, scientific management, subprime mortgage crisis, tail risk, technology bubble, TED Talk, The Great Moderation, too big to fail, transaction costs, union organizing, Unsafe at Any Speed, value at risk, William Langewiesche, zero-sum game

Securities dealers have “a very entrepreneurial culture—a drive to make money—and therefore a focus on personal achievement and a willingness to push the limits.” When Clark dug into the business, he got scared at how little top executives, both at TD and its competitors, understood about how securities dealers made money. It was, he said, a business built on taking tail risk: something highly unlikely and highly destructive. “I started to go through these products and said, ‘These products have inherent in them huge risk.’ Are derivatives good? Can hedging be good? Of course,” says Clark, “but if behind all that someone tells you this only works if the world doesn’t change significantly, I don’t like that risk.”

The Big Short: Inside the Doomsday Machine by Michael Lewis

Alan Greenspan, An Inconvenient Truth, Asperger Syndrome, asset-backed security, Bear Stearns, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, diversified portfolio, facts on the ground, financial engineering, financial innovation, fixed income, forensic accounting, Gordon Gekko, high net worth, housing crisis, illegal immigration, income inequality, index fund, interest rate swap, John Meriwether, junk bonds, London Interbank Offered Rate, Long Term Capital Management, low interest rates, medical residency, Michael Milken, money market fund, moral hazard, mortgage debt, pets.com, Ponzi scheme, Potemkin village, proprietary trading, quantitative trading / quantitative finance, Quicken Loans, risk free rate, Robert Bork, short selling, Silicon Valley, tail risk, the new new thing, too big to fail, value at risk, Vanguard fund, zero-sum game

When these got, it's simple, it's very painful, so I'm not being glib. When these guys stress loss the scenario on putting on this position, they did not envision...that we could have this degree of default, right. It is fair to say that our risk management division did not stress those losses as well.* It's just simple as that. Those are big fat tail risks that caught us hard, right. That's what happened. TANONA: Okay. Fair enough. I guess the other thing I would question. I am surprised that your trading VaR stayed stable in the quarter given this level of loss, and given that I would suspect that these were trading assets. So can you help me understand why your VaR didn't increase in the quarter dramatically?

Lying for Money: How Fraud Makes the World Go Round by Daniel Davies

Alan Greenspan, bank run, banking crisis, Bernie Madoff, bitcoin, Black Swan, Bretton Woods, business cycle, business process, collapse of Lehman Brothers, compound rate of return, cryptocurrency, fake it until you make it, financial deregulation, fixed income, Frederick Winslow Taylor, Gordon Gekko, high net worth, illegal immigration, index arbitrage, junk bonds, Michael Milken, multilevel marketing, Nick Leeson, offshore financial centre, Peter Thiel, Ponzi scheme, price mechanism, principal–agent problem, railway mania, Ronald Coase, Ronald Reagan, Savings and loan crisis, scientific management, short selling, social web, South Sea Bubble, tacit knowledge, tail risk, The Great Moderation, the payments system, The Wealth of Nations by Adam Smith, time value of money, vertical integration, web of trust

Why was it cheaper that way? Because rigorous fraud controls are expensive relative to the amount of profit that you’re making on the deal. And now we arrive at the final ‘why’? Why is there always an incentive to economise on checks, audits and fraud prevention? Because fraud is an unusual condition; it’s a ‘tail risk’. In an advanced, high-trust economy, a business can trade for years without ever seeing a big systematic fraud like Tino De Angelis. And normal businesspeople are, like all human beings, usually quite bad at judging the significance of small probabilities and rare events. It’s all too easy a heuristic to deal with the small risk of a catastrophic fraud loss by assuming that because it’s close to zero, it’s reasonable to act as if it was actually zero.

Python for Finance by Yuxing Yan

asset-backed security, book value, business cycle, business intelligence, capital asset pricing model, constrained optimization, correlation coefficient, data science, distributed generation, diversified portfolio, financial engineering, functional programming, implied volatility, market microstructure, P = NP, p-value, quantitative trading / quantitative finance, risk free rate, Sharpe ratio, tail risk, time value of money, value at risk, volatility smile, zero-sum game

Next, we estimate the four moments for S&P500 based on its daily returns as follows: from scipy import stats from matplotlib.finance import quotes_historical_yahoo import numpy as np ticker='^GSPC' begdate=(1926,1,1) enddate=(2013,12,31) p = quotes_historical_yahoo(ticker, begdate, enddate,asobject=True, adjusted=True) ret = (p.aclose[1:] - p.aclose[:-1])/p.aclose[1:] print( 'S&P500 n =',len(ret)) print( 'S&P500 mean =',round(np.mean(ret),8)) print( 'S&P500 std =',round(np.std(ret),8)) print( 'S&P500 skewness=',round(stats.skew(ret),8)) print( 'S&P500 kurtosis=',round(stats.kurtosis(ret),8)) [ 351 ] Volatility Measures and GARCH The output for the five values mentioned in the previous code, including the number of observations, is given as follows: This result is very close to the result in the paper titled Study of Fat-tail Risk by Cook Pine Capital, which can be downloaded from http://www.cookpinecapital.com/ pdf/Study%20of%20Fat-tail%20Risk.pdf. Using the same argument, we conclude that the S&P500 daily returns are skewed to the left, that is, a negative skewness, and have fat tails (kurtosis is 38.22 instead of zero).

Ludicrous: The Unvarnished Story of Tesla Motors by Edward Niedermeyer

autonomous vehicles, barriers to entry, Bear Stearns, bitcoin, business climate, call centre, carbon footprint, Clayton Christensen, clean tech, Colonization of Mars, computer vision, crowdsourcing, disruptive innovation, Donald Trump, driverless car, Elon Musk, en.wikipedia.org, facts on the ground, fake it until you make it, family office, financial engineering, Ford Model T, gigafactory, global supply chain, Google Earth, housing crisis, hype cycle, Hyperloop, junk bonds, Kaizen: continuous improvement, Kanban, Kickstarter, Lyft, Marc Andreessen, Menlo Park, minimum viable product, new economy, off grid, off-the-grid, OpenAI, Paul Graham, peak oil, performance metric, Ponzi scheme, ride hailing / ride sharing, risk tolerance, Sand Hill Road, self-driving car, short selling, short squeeze, side project, Silicon Valley, Silicon Valley startup, Skype, smart cities, Solyndra, stealth mode startup, Steve Jobs, Steve Jurvetson, tail risk, technoutopianism, Tesla Model S, too big to fail, Toyota Production System, Uber and Lyft, uber lyft, union organizing, vertical integration, WeWork, work culture , Zipcar

These situations, called “edge cases,” can arise from a single actor or a complex interaction of actors and circumstances, and their sheer randomness makes them an extremely difficult challenge for autonomous car development. Not only are they randomly distributed, meaning you can drive for thousands of miles without ever seeing one, but they are also intrinsically random events, meaning it’s incredibly difficult to design an artificial intelligence system to handle them. This “long-tail risk” means that the closer an autonomous-drive system gets to being “perfect,” the harder it becomes to anticipate and address the remaining edge cases. In 2016, when Tesla first started selling a Full Self Driving option, autonomous-drive technology was at the peak of its hype. After the Josh Brown incident and the fatal crash of an Uber autonomous test vehicle into a pedestrian in March of 2018, popular perceptions of autonomous cars turned negative and developers began to take the edge case problem a lot more seriously.

Superforecasting: The Art and Science of Prediction by Philip Tetlock, Dan Gardner

Affordable Care Act / Obamacare, Any sufficiently advanced technology is indistinguishable from magic, availability heuristic, behavioural economics, Black Swan, butterfly effect, buy and hold, cloud computing, cognitive load, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, desegregation, drone strike, Edward Lorenz: Chaos theory, forward guidance, Freestyle chess, fundamental attribution error, germ theory of disease, hindsight bias, How many piano tuners are there in Chicago?, index fund, Jane Jacobs, Jeff Bezos, Kenneth Arrow, Laplace demon, longitudinal study, Mikhail Gorbachev, Mohammed Bouazizi, Nash equilibrium, Nate Silver, Nelson Mandela, obamacare, operational security, pattern recognition, performance metric, Pierre-Simon Laplace, place-making, placebo effect, precautionary principle, prediction markets, quantitative easing, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, Robert Shiller, Ronald Reagan, Saturday Night Live, scientific worldview, Silicon Valley, Skype, statistical model, stem cell, Steve Ballmer, Steve Jobs, Steven Pinker, tacit knowledge, tail risk, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Watson beat the top human players on Jeopardy!

He still would have seen the forecast as improbable, but it would now be thousands of times more probable than before.14 The impact would be analogous to your learning that your personal chances of winning the Powerball lottery on any ticket purchase have risen from one in five million to one in five hundred. Wouldn’t you rush to buy tickets? A policy maker in 1914 who knew the true fat-tail risks of a megacasualty war might well have tried a lot harder to avert the looming catastrophe. Or, look at it this way. If height had a fat-tailed distribution, it would still be very unusual to walk down the street and encounter a twelve-foot man—followed by a fifteen-foot man—but such events could conceivably occur in one’s lifetime.

Fool's Gold: How the Bold Dream of a Small Tribe at J.P. Morgan Was Corrupted by Wall Street Greed and Unleashed a Catastrophe by Gillian Tett

"World Economic Forum" Davos, accounting loophole / creative accounting, Alan Greenspan, asset-backed security, bank run, banking crisis, Bear Stearns, Black-Scholes formula, Blythe Masters, book value, break the buck, Bretton Woods, business climate, business cycle, buy and hold, collateralized debt obligation, commoditize, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, easy for humans, difficult for computers, financial engineering, financial innovation, fixed income, Glass-Steagall Act, housing crisis, interest rate derivative, interest rate swap, inverted yield curve, junk bonds, Kickstarter, locking in a profit, Long Term Capital Management, low interest rates, McMansion, Michael Milken, money market fund, mortgage debt, North Sea oil, Northern Rock, Plato's cave, proprietary trading, Renaissance Technologies, risk free rate, risk tolerance, Robert Shiller, Satyajit Das, Savings and loan crisis, short selling, sovereign wealth fund, statistical model, tail risk, The Great Moderation, too big to fail, value at risk, yield curve

If the bank’s own models for judging the risk of, say, a CDO were wrong, then the Basel II system would not work and the dangers in the market might be considerable. Corrigan had spent enough time looking at various banks’ models to know that they were far from foolproof. Geithner’s repeated warning that banks needed to pay more attention to the “tail risk” of fat tails indicated that he too was uneasy about the modeling. However, vague notions about invisible risk were not enough to force the G8 to act. When Geithner had launched his campaign to clean up trading backlogs, he had been armed with alarming data. Similarly, when the Germans had launched their appeals for hedge fund regulation, they at least had a concrete disaster story to point to in LTCM.

Capital Ideas Evolving by Peter L. Bernstein

Albert Einstein, algorithmic trading, Andrei Shleifer, asset allocation, behavioural economics, Black Monday: stock market crash in 1987, Bob Litterman, book value, business cycle, buy and hold, buy low sell high, capital asset pricing model, commodity trading advisor, computerized trading, creative destruction, currency risk, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, diversification, diversified portfolio, endowment effect, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, financial engineering, financial innovation, fixed income, high net worth, hiring and firing, index fund, invisible hand, Isaac Newton, John Meriwether, John von Neumann, Joseph Schumpeter, Kenneth Arrow, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, mental accounting, money market fund, Myron Scholes, paper trading, passive investing, Paul Samuelson, Performance of Mutual Funds in the Period, price anchoring, price stability, random walk, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, seminal paper, Sharpe ratio, short selling, short squeeze, Silicon Valley, South Sea Bubble, statistical model, survivorship bias, systematic trading, tail risk, technology bubble, The Wealth of Nations by Adam Smith, transaction costs, yield curve, Yogi Berra, zero-sum game

bern_c02.qxd 24 3/23/07 8:53 AM THE Page 24 B E H AV I O R A L AT TAC K Second, calculating hedge fund risk is a controversial procedure. Volatility measures employed as risk measurements in conventional investing are not appropriate in a long/short environment. Among other things, hedge fund returns are subject to fat tails or tail risk—higherthan-normal probabilities of extreme negative returns. Hedge funds are short-sellers, and short-sellers take the risk of infinite losses (stocks can fall only to zero but can rise to infinity). They can be caught in what is known as a “short squeeze,” in which they are unable to make delivery of the stock they have sold because they are unable to borrow it anywhere.

The Glass Half-Empty: Debunking the Myth of Progress in the Twenty-First Century by Rodrigo Aguilera

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, activist fund / activist shareholder / activist investor, Alan Greenspan, Anthropocene, availability heuristic, barriers to entry, basic income, benefit corporation, Berlin Wall, Bernie Madoff, Bernie Sanders, bitcoin, Boris Johnson, Branko Milanovic, Bretton Woods, Brexit referendum, Capital in the Twenty-First Century by Thomas Piketty, capitalist realism, carbon footprint, Carmen Reinhart, centre right, clean water, cognitive bias, collapse of Lehman Brothers, Colonization of Mars, computer age, Corn Laws, corporate governance, corporate raider, creative destruction, cryptocurrency, cuban missile crisis, David Graeber, David Ricardo: comparative advantage, death from overwork, decarbonisation, deindustrialization, Deng Xiaoping, Doha Development Round, don't be evil, Donald Trump, Doomsday Clock, Dunning–Kruger effect, Elon Musk, European colonialism, fake news, Fall of the Berlin Wall, first-past-the-post, Francis Fukuyama: the end of history, fundamental attribution error, gig economy, Gini coefficient, Glass-Steagall Act, Great Leap Forward, green new deal, Hans Rosling, housing crisis, income inequality, income per capita, index fund, intangible asset, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jean Tirole, Jeff Bezos, Jeremy Corbyn, Jevons paradox, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, joint-stock company, Joseph Schumpeter, karōshi / gwarosa / guolaosi, Kenneth Rogoff, Kickstarter, lake wobegon effect, land value tax, Landlord’s Game, late capitalism, liberal capitalism, long peace, loss aversion, low interest rates, Mark Zuckerberg, market fundamentalism, means of production, meta-analysis, military-industrial complex, Mont Pelerin Society, moral hazard, moral panic, neoliberal agenda, Network effects, North Sea oil, Northern Rock, offshore financial centre, opioid epidemic / opioid crisis, Overton Window, Pareto efficiency, passive investing, Peter Thiel, plutocrats, principal–agent problem, profit motive, public intellectual, purchasing power parity, race to the bottom, rent-seeking, risk tolerance, road to serfdom, Robert Shiller, Robert Solow, savings glut, Scientific racism, secular stagnation, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, Social Justice Warrior, Social Responsibility of Business Is to Increase Its Profits, sovereign wealth fund, Stanislav Petrov, Steven Pinker, structural adjustment programs, surveillance capitalism, tail risk, tech bro, TED Talk, The Spirit Level, The Wealth of Nations by Adam Smith, too big to fail, trade liberalization, transatlantic slave trade, trolley problem, unbiased observer, universal basic income, Vilfredo Pareto, Washington Consensus, Winter of Discontent, Y2K, young professional, zero-sum game

., “Ambush in Mogadishu”, Frontline, Jan. 2011, https://www.pbs.org/wgbh/pages/frontline/shows/ambush/etc/script.html 27 Pinker, S., The Better Angels of Our Nature, pg. 88 28 Eisner, M., “Long-Term Trends in Violent Crime”, Crime and Justice, 30, 1 Nov. 2003, http://doi.org/10.1086/449082 29 Pinker, S., The Better Angels of Our Nature, Ch 5-6 30 Cirillo, P. and Taleb, N.N., “On the statistical properties and tail risk of violent conflicts”, Physica A: Statistical Mechanics and its Applications, 452, 15 Jun. 2016, https://doi.org/10.1016/j.physa.2016.01.050 31 Clauset, A., “Trends and Fluctuations in the Severity of Interstate Wars”, Science Advances, 4(2), Feb. 2018, https://doi.org/10.1126/sciadv.aao3580 32 Brecke, P.

Planet Ponzi by Mitch Feierstein

Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, Asian financial crisis, asset-backed security, bank run, banking crisis, barriers to entry, Bear Stearns, Bernie Madoff, book value, break the buck, centre right, collapse of Lehman Brothers, collateralized debt obligation, commoditize, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, disintermediation, diversification, Donald Trump, energy security, eurozone crisis, financial innovation, financial intermediation, fixed income, Flash crash, floating exchange rates, frictionless, frictionless market, Future Shock, Glass-Steagall Act, government statistician, high net worth, High speed trading, illegal immigration, income inequality, interest rate swap, invention of agriculture, junk bonds, light touch regulation, Long Term Capital Management, low earth orbit, low interest rates, mega-rich, money market fund, moral hazard, mortgage debt, negative equity, Neil Armstrong, Northern Rock, obamacare, offshore financial centre, oil shock, pensions crisis, plutocrats, Ponzi scheme, price anchoring, price stability, proprietary trading, purchasing power parity, quantitative easing, risk tolerance, Robert Shiller, Ronald Reagan, tail risk, too big to fail, trickle-down economics, value at risk, yield curve

It sounds boring. It sounds like a case of just buying a bigger computer. But risk management kills firms. And there’s only one way to avoid it: only play with stuff that you really, truly understand. And stick close to actual market pricing, because only then do you stay close to reality. Long tail risk There’s a variant on risk quantification which carries its own separate hazards. Back in the 1990s, JP Morgan‌—‌then and now, one of the best-run banks on the market‌—‌invented a risk management technology which measured ‘value at risk’ or VAR. That is, it could tell you how much money you would stand to lose on your entire portfolio if interest rates rose a little, or if the yen fell a little, and so on.

Fed Up: An Insider's Take on Why the Federal Reserve Is Bad for America by Danielle Dimartino Booth

Affordable Care Act / Obamacare, Alan Greenspan, asset-backed security, bank run, barriers to entry, Basel III, Bear Stearns, Bernie Sanders, Black Monday: stock market crash in 1987, break the buck, Bretton Woods, business cycle, central bank independence, collateralized debt obligation, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, financial deregulation, financial engineering, financial innovation, fixed income, Flash crash, forward guidance, full employment, George Akerlof, Glass-Steagall Act, greed is good, Greenspan put, high net worth, housing crisis, income inequality, index fund, inflation targeting, interest rate swap, invisible hand, John Meriwether, Joseph Schumpeter, junk bonds, liquidity trap, London Whale, Long Term Capital Management, low interest rates, margin call, market bubble, Mexican peso crisis / tequila crisis, money market fund, moral hazard, Myron Scholes, natural language processing, Navinder Sarao, negative equity, new economy, Northern Rock, obamacare, Phillips curve, price stability, proprietary trading, pushing on a string, quantitative easing, regulatory arbitrage, Robert Shiller, Ronald Reagan, selection bias, short selling, side project, Silicon Valley, stock buybacks, tail risk, The Great Moderation, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, yield curve

Once remunerated by a fixed salary, financial managers in deregulated banks vied with each other and institutions like mutual funds to attract investors’ cash. Because their pay was increasingly tied to short-term returns, managers tried to maximize their compensation by betting on complex derivatives with potentially huge payoffs. Though a price decline of the securities could be disastrous, the probability of such an event—the “tail risk”—was low. Since financial managers’ pay is set relative to their peers, everyone follows the same path. A herd instinct takes over. But if something went wrong, the results could be ruinous. The more crowded the trade, the greater the chance an unexpected turn in prices would cascade from institution to institution and potentially throughout the entire system.

Succeeding With AI: How to Make AI Work for Your Business by Veljko Krunic

AI winter, Albert Einstein, algorithmic trading, AlphaGo, Amazon Web Services, anti-fragile, anti-pattern, artificial general intelligence, autonomous vehicles, Bayesian statistics, bioinformatics, Black Swan, Boeing 737 MAX, business process, cloud computing, commoditize, computer vision, correlation coefficient, data is the new oil, data science, deep learning, DeepMind, en.wikipedia.org, fail fast, Gini coefficient, high net worth, information retrieval, Internet of things, iterative process, job automation, Lean Startup, license plate recognition, minimum viable product, natural language processing, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, six sigma, smart cities, speech recognition, statistical model, strong AI, tail risk, The Design of Experiments, the scientific method, web application, zero-sum game

Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), Portorož, Slovenia. 2016:261–266. Taleb NN, Douady R. Mathematical definition, mapping, and detection of (anti)fragility. arXiv. 2012 Aug;arXiv:1208.1189 [q-fin.RM]. Taleb NN, Canetti E, Kinda T, Loukoianova E, Schmieder C. A new heuristic measure of fragility and tail risks: Application to stress testing. IMF Working Papers. 2012 Aug;12. Taleb NN. The black swan: the impact of the highly improbable. 2nd ed. New York: Random House Trade Paperbacks; 2010. Johnson K. Nvidia trains world’s largest Transformer-based language model. VentureBeat. [Cited 2019 Aug 19.] Available from: https://venturebeat.com/2019/ 08/13/nvidia-trains-worlds-largest-transformer-based-language-model/ Halevy A, Norvig P, Pereira F.

The Great Displacement: Climate Change and the Next American Migration by Jake Bittle

augmented reality, clean water, climate anxiety, climate change refugee, coronavirus, cotton gin, COVID-19, decarbonisation, digital map, Donald Trump, energy transition, four colour theorem, gentrification, Google Earth, housing crisis, illegal immigration, immigration reform, longitudinal study, McMansion, off-the-grid, oil shock, place-making, Ralph Waldo Emerson, risk tolerance, smart cities, tail risk, Tipper Gore, Tragedy of the Commons, urban planning, urban renewal, urban sprawl, white flight, Yom Kippur War, young professional

Unlike Jess Di Stefano and her neighbors from Paradise, Sally might never have left New Orleans were it not for the storm, but like Jess, she was fortunate enough to choose where she landed. It might seem odd that someone whose life had been so upended by the weather would choose to live in one of the hottest and driest cities in the United States, but the decision has its own sympathetic logic. Sally’s desire to avoid future storms was more emotional than calculated, and the tail risks of extreme heat and drought seemed far less real than those of a tropical cyclone. She doesn’t mind collecting rainwater during the driest summer months, and her yard, like all her neighbors’ yards, has been planted with a desert-adapted rockscape. Sally’s aim in moving out west was not to avoid all climate risk, but to reduce her exposure to one kind of risk.

A Man for All Markets by Edward O. Thorp

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", 3Com Palm IPO, Alan Greenspan, Albert Einstein, asset allocation, Bear Stearns, beat the dealer, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, Black-Scholes formula, book value, Brownian motion, buy and hold, buy low sell high, caloric restriction, caloric restriction, carried interest, Chuck Templeton: OpenTable:, Claude Shannon: information theory, cognitive dissonance, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Edward Thorp, Erdős number, Eugene Fama: efficient market hypothesis, financial engineering, financial innovation, Garrett Hardin, George Santayana, German hyperinflation, Glass-Steagall Act, Henri Poincaré, high net worth, High speed trading, index arbitrage, index fund, interest rate swap, invisible hand, Jarndyce and Jarndyce, Jeff Bezos, John Bogle, John Meriwether, John Nash: game theory, junk bonds, Kenneth Arrow, Livingstone, I presume, Long Term Capital Management, Louis Bachelier, low interest rates, margin call, Mason jar, merger arbitrage, Michael Milken, Murray Gell-Mann, Myron Scholes, NetJets, Norbert Wiener, PalmPilot, passive investing, Paul Erdős, Paul Samuelson, Pluto: dwarf planet, Ponzi scheme, power law, price anchoring, publish or perish, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, RFID, Richard Feynman, risk-adjusted returns, Robert Shiller, rolodex, Sharpe ratio, short selling, Silicon Valley, Stanford marshmallow experiment, statistical arbitrage, stem cell, stock buybacks, stocks for the long run, survivorship bias, tail risk, The Myth of the Rational Market, The Predators' Ball, the rule of 72, The Wisdom of Crowds, too big to fail, Tragedy of the Commons, uptick rule, Upton Sinclair, value at risk, Vanguard fund, Vilfredo Pareto, Works Progress Administration

But they actually lost over 50 percent at their low in 2009, brought to the brink of ruin before finally recovering their losses in 2012. The credit collapse of 2008 was different in kind from the past worst cases for which they tested, and their near-extinction reflects the inadequacy of simply replaying the past. We took a more comprehensive view. We analyzed and incorporated tail risk, and considered extreme questions such as, “What if the market fell 25 percent in one day?” More than a decade later it did exactly that and our portfolio was barely affected. When, with our expanding range and size of trades, we moved our account to Goldman Sachs as our prime broker, one of the questions I asked was: “What happens to our account if Goldman Sachs New York is destroyed by a terrorist nuclear bomb smuggled into New York Harbor?”

Shutdown: How COVID Shook the World's Economy by Adam Tooze

2021 United States Capitol attack, air freight, algorithmic trading, Anthropocene, Asian financial crisis, asset-backed security, Ayatollah Khomeini, bank run, banking crisis, Basel III, basic income, Ben Bernanke: helicopter money, Benchmark Capital, Berlin Wall, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, Black Monday: stock market crash in 1987, blue-collar work, Bob Geldof, bond market vigilante , Boris Johnson, Bretton Woods, Brexit referendum, business cycle, business process, business process outsourcing, buy and hold, call centre, capital controls, central bank independence, centre right, clean water, cognitive dissonance, contact tracing, contact tracing app, coronavirus, COVID-19, credit crunch, Credit Default Swap, cryptocurrency, currency manipulation / currency intervention, currency peg, currency risk, decarbonisation, deindustrialization, Donald Trump, Elon Musk, energy transition, eurozone crisis, facts on the ground, failed state, fake news, Fall of the Berlin Wall, fear index, financial engineering, fixed income, floating exchange rates, friendly fire, George Floyd, gig economy, global pandemic, global supply chain, green new deal, high-speed rail, housing crisis, income inequality, inflation targeting, invisible hand, It's morning again in America, Jeremy Corbyn, junk bonds, light touch regulation, lockdown, low interest rates, margin call, Martin Wolf, mass immigration, mass incarceration, megacity, megaproject, middle-income trap, Mikhail Gorbachev, Modern Monetary Theory, moral hazard, oil shale / tar sands, Overton Window, Paris climate accords, Pearl River Delta, planetary scale, Potemkin village, price stability, Productivity paradox, purchasing power parity, QR code, quantitative easing, remote working, reserve currency, reshoring, Robinhood: mobile stock trading app, Ronald Reagan, secular stagnation, shareholder value, Silicon Valley, six sigma, social distancing, South China Sea, special drawing rights, stock buybacks, tail risk, TikTok, too big to fail, TSMC, universal basic income, Washington Consensus, women in the workforce, yield curve

A succession of horrifying wildfires consumed tens of millions of acres of bush and forest.54 California suffered blackouts as air conditioners struggled to meet a sweltering summer. As forests burned, the prison crews on which the Golden State normally relies to fight its fires were quarantined by the Covid lockdown.55 Europe was, in fact, spared most of these blows, but opinion polls show that people understood coronavirus as an indication of how seriously to take tail risks.56 The year 2020 had been billed as one of climate action. The key date was to have been COP26 in Glasgow in November.57 Five years on from the Paris climate agreement of 2015, it was time to update the so-called Nationally Determined Contributions (NDCs) to decarbonization. If Europe was to maintain its credibility as a climate leader, it needed to do better than the 40 percent cut by 2030 it had promised in 2015.

The Best Business Writing 2013 by Dean Starkman

Alvin Toffler, Asperger Syndrome, bank run, Basel III, Bear Stearns, call centre, carbon tax, clean water, cloud computing, collateralized debt obligation, Columbine, computer vision, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, Erik Brynjolfsson, eurozone crisis, Evgeny Morozov, Exxon Valdez, Eyjafjallajökull, factory automation, fixed income, fulfillment center, full employment, Future Shock, gamification, Goldman Sachs: Vampire Squid, hiring and firing, hydraulic fracturing, Ida Tarbell, income inequality, jimmy wales, job automation, John Markoff, junk bonds, Kickstarter, late fees, London Whale, low interest rates, low skilled workers, Mahatma Gandhi, market clearing, Maui Hawaii, Menlo Park, Occupy movement, oil shale / tar sands, One Laptop per Child (OLPC), Parag Khanna, Pareto efficiency, price stability, proprietary trading, Ray Kurzweil, San Francisco homelessness, Silicon Valley, Skype, sovereign wealth fund, stakhanovite, Stanford prison experiment, Steve Jobs, Stuxnet, synthetic biology, tail risk, technological determinism, the payments system, too big to fail, Vanguard fund, wage slave, warehouse automation, warehouse robotics, Y2K, zero-sum game

—not correct to say, as everyone does, that Iksil was long $100 billion of corporate credit in his CDX book. It is certainly correct to say that the CIO was overall long credit—that’s what it does! invest JPMorgan’s money in credit instruments!—or that JPMorgan as a whole was long credit—it’s a bank!—but the credit derivatives book probably was a hedge designed to hedge tail risk. The second is, his model was wrong. At a bank, that little flow chart of the bet that I set out above gets programmed into a computer, and the computer knows your cash flows and what the expected value of them is based on market conditions. If the market is predicting seven defaults, the computer knows that, and knows that I will pay you $14 and you will pay me $11, and it will discount those cash flows and spit out a present value of the bet based on current market conditions.

The Default Line: The Inside Story of People, Banks and Entire Nations on the Edge by Faisal Islam

"World Economic Forum" Davos, Alan Greenspan, Asian financial crisis, asset-backed security, balance sheet recession, bank run, banking crisis, Basel III, Ben Bernanke: helicopter money, Berlin Wall, Big bang: deregulation of the City of London, bond market vigilante , book value, Boris Johnson, British Empire, capital controls, carbon credits, carbon footprint, carbon tax, Celtic Tiger, central bank independence, centre right, collapse of Lehman Brothers, credit crunch, Credit Default Swap, crony capitalism, Crossrail, currency risk, dark matter, deindustrialization, Deng Xiaoping, disintermediation, energy security, Eugene Fama: efficient market hypothesis, eurozone crisis, Eyjafjallajökull, financial deregulation, financial engineering, financial innovation, financial repression, floating exchange rates, forensic accounting, forward guidance, full employment, G4S, ghettoisation, global rebalancing, global reserve currency, high-speed rail, hiring and firing, inflation targeting, Irish property bubble, junk bonds, Just-in-time delivery, labour market flexibility, light touch regulation, London Whale, Long Term Capital Management, low interest rates, margin call, market clearing, megacity, megaproject, Mikhail Gorbachev, mini-job, mittelstand, Money creation, moral hazard, mortgage debt, mortgage tax deduction, mutually assured destruction, Myron Scholes, negative equity, North Sea oil, Northern Rock, offshore financial centre, open economy, paradox of thrift, Pearl River Delta, pension reform, price mechanism, price stability, profit motive, quantitative easing, quantitative trading / quantitative finance, race to the bottom, regulatory arbitrage, reserve currency, reshoring, Right to Buy, rising living standards, Ronald Reagan, savings glut, shareholder value, sovereign wealth fund, tail risk, The Chicago School, the payments system, too big to fail, trade route, transaction costs, two tier labour market, unorthodox policies, uranium enrichment, urban planning, value at risk, WikiLeaks, working-age population, zero-sum game

The Financial Times quoted Goldman Sachs’ chief financial officer during the 2007 credit crunch as saying that twenty-five standard deviation moves were happening several days in a row. To put that in context, he was suggesting that occurrences that his financial model suggested would only happen once in a period of many trillions of lifetimes of the universe, were actually happening every day. The ‘fatal flaw’ of VaR, as Haldane argues, is that it is silent about the tail risk. A trader could be given a so-called 99 per cent VaR limit of $10 million, but VaR would be blind to the trader’s construction of a portfolio that gave a 1 per cent chance of a $1 billion loss. J. P. Morgan itself discovered in May 2012 that the ‘London Whale’ corporate credit portfolio that was assessed with a 95 per cent VaR of $67 million in early 2012 had lost them $2 billion within weeks.

Them And Us: Politics, Greed And Inequality - Why We Need A Fair Society by Will Hutton

Abraham Maslow, Alan Greenspan, Andrei Shleifer, asset-backed security, bank run, banking crisis, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Blythe Masters, Boris Johnson, bread and circuses, Bretton Woods, business cycle, capital controls, carbon footprint, Carmen Reinhart, Cass Sunstein, centre right, choice architecture, cloud computing, collective bargaining, conceptual framework, Corn Laws, Cornelius Vanderbilt, corporate governance, creative destruction, credit crunch, Credit Default Swap, debt deflation, decarbonisation, Deng Xiaoping, discovery of DNA, discovery of the americas, discrete time, disinformation, diversification, double helix, Edward Glaeser, financial deregulation, financial engineering, financial innovation, financial intermediation, first-past-the-post, floating exchange rates, Francis Fukuyama: the end of history, Frank Levy and Richard Murnane: The New Division of Labor, full employment, general purpose technology, George Akerlof, Gini coefficient, Glass-Steagall Act, global supply chain, Growth in a Time of Debt, Hyman Minsky, I think there is a world market for maybe five computers, income inequality, inflation targeting, interest rate swap, invisible hand, Isaac Newton, James Dyson, James Watt: steam engine, Japanese asset price bubble, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, knowledge economy, knowledge worker, labour market flexibility, language acquisition, Large Hadron Collider, liberal capitalism, light touch regulation, Long Term Capital Management, long term incentive plan, Louis Pasteur, low cost airline, low interest rates, low-wage service sector, mandelbrot fractal, margin call, market fundamentalism, Martin Wolf, mass immigration, means of production, meritocracy, Mikhail Gorbachev, millennium bug, Money creation, money market fund, moral hazard, moral panic, mortgage debt, Myron Scholes, Neil Kinnock, new economy, Northern Rock, offshore financial centre, open economy, plutocrats, power law, price discrimination, private sector deleveraging, proprietary trading, purchasing power parity, quantitative easing, race to the bottom, railway mania, random walk, rent-seeking, reserve currency, Richard Thaler, Right to Buy, rising living standards, Robert Shiller, Ronald Reagan, Rory Sutherland, Satyajit Das, Savings and loan crisis, shareholder value, short selling, Silicon Valley, Skype, South Sea Bubble, Steve Jobs, systems thinking, tail risk, The Market for Lemons, the market place, The Myth of the Rational Market, the payments system, the scientific method, The Wealth of Nations by Adam Smith, three-masted sailing ship, too big to fail, unpaid internship, value at risk, Vilfredo Pareto, Washington Consensus, wealth creators, work culture , working poor, world market for maybe five computers, zero-sum game, éminence grise

The new mantras were mathematics, probability and diversification of risk – all of which were based on the faulty assumption that the financial markets were efficient. With investors chasing ever-higher yields, the new risk-management techniques allowed banks to recategorise high-yield but risky assets – those outside the normal distribution of risk, so-called ‘tail risks’ – as ‘normal’. Thus were born structured investment vehicles and securitisation. But these assets still generated the higher yields. It seemed to be financial magic. Banks could use the interbank markets to raise finance for almost any activity as long as they could put up the necessary collateral or had a sufficiently high credit rating.

The Shifts and the Shocks: What We've Learned--And Have Still to Learn--From the Financial Crisis by Martin Wolf

air freight, Alan Greenspan, anti-communist, Asian financial crisis, asset allocation, asset-backed security, balance sheet recession, bank run, banking crisis, banks create money, Basel III, Bear Stearns, Ben Bernanke: helicopter money, Berlin Wall, Black Swan, bonus culture, break the buck, Bretton Woods, business cycle, call centre, capital asset pricing model, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, collateralized debt obligation, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, currency risk, debt deflation, deglobalization, Deng Xiaoping, diversification, double entry bookkeeping, en.wikipedia.org, Erik Brynjolfsson, Eugene Fama: efficient market hypothesis, eurozone crisis, Fall of the Berlin Wall, fiat currency, financial deregulation, financial innovation, financial repression, floating exchange rates, foreign exchange controls, forward guidance, Fractional reserve banking, full employment, Glass-Steagall Act, global rebalancing, global reserve currency, Growth in a Time of Debt, Hyman Minsky, income inequality, inflation targeting, information asymmetry, invisible hand, Joseph Schumpeter, Kenneth Rogoff, labour market flexibility, labour mobility, Les Trente Glorieuses, light touch regulation, liquidationism / Banker’s doctrine / the Treasury view, liquidity trap, Long Term Capital Management, low interest rates, mandatory minimum, margin call, market bubble, market clearing, market fragmentation, Martin Wolf, Mexican peso crisis / tequila crisis, Minsky moment, Modern Monetary Theory, Money creation, money market fund, moral hazard, mortgage debt, negative equity, new economy, North Sea oil, Northern Rock, open economy, paradox of thrift, Paul Samuelson, price stability, private sector deleveraging, proprietary trading, purchasing power parity, pushing on a string, quantitative easing, Real Time Gross Settlement, regulatory arbitrage, reserve currency, Richard Feynman, risk-adjusted returns, risk/return, road to serfdom, Robert Gordon, Robert Shiller, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, shareholder value, short selling, sovereign wealth fund, special drawing rights, subprime mortgage crisis, tail risk, The Chicago School, The Great Moderation, The Market for Lemons, the market place, The Myth of the Rational Market, the payments system, The Wealth of Nations by Adam Smith, too big to fail, Tyler Cowen, Tyler Cowen: Great Stagnation, vertical integration, very high income, winner-take-all economy, zero-sum game

Given this situation, the willingness or even ability of any German government to support an EU programme, which would be a necessary condition for implementation of the OMT, is in grave doubt and so, therefore, is the workability of the OMT.29 Fortunately, at the time this book went to press these contradictions had not been tested. Not just the announcement but also its tacit acceptance by all member state governments had an extraordinary impact on markets, because it was seen as largely eliminating the tail risk of break-up. As the International Monetary Fund noted in its July 2013 report on the Eurozone: ‘The ECB’s commitment to do “whatever it takes” – including by establishing the OMT’s framework – improved the functioning of monetary policy and safeguarded the viability of the euro.’30 In particular, as Figures 6 and 7 show, a marked and general decline ensued in spreads on the bonds of riskier sovereigns.

All the Devils Are Here by Bethany McLean

Alan Greenspan, Asian financial crisis, asset-backed security, bank run, Bear Stearns, behavioural economics, Black-Scholes formula, Blythe Masters, break the buck, buy and hold, call centre, Carl Icahn, collateralized debt obligation, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, diversification, Dr. Strangelove, Exxon Valdez, fear of failure, financial innovation, fixed income, Glass-Steagall Act, high net worth, Home mortgage interest deduction, interest rate swap, junk bonds, Ken Thompson, laissez-faire capitalism, Long Term Capital Management, low interest rates, margin call, market bubble, market fundamentalism, Maui Hawaii, Michael Milken, money market fund, moral hazard, mortgage debt, Northern Rock, Own Your Own Home, Ponzi scheme, proprietary trading, quantitative trading / quantitative finance, race to the bottom, risk/return, Ronald Reagan, Rosa Parks, Savings and loan crisis, shareholder value, short selling, South Sea Bubble, statistical model, stock buybacks, tail risk, Tax Reform Act of 1986, telemarketer, the long tail, too big to fail, value at risk, zero-sum game

Later, many Wall Street CEOs would view their daily VaR number as an expression of their firm’s worst-case scenario. But it was nothing of the sort. The most important information VaR conveyed was not the absolute number, but the trend over the course of weeks or months. Were the bank’s risks increasing or diminishing? Were problems arising on this desk or that one? And so on. And then there was the tail risk issue. The fact that VaR told you how much your firm might lose 95 percent of the time didn’t say a thing about what might happen the other 5 percent of the time. Maybe you would lose a little more than the VaR number—no big deal. Or maybe you’d get caught in a black swan and lose billions. The fact that VaR had been created didn’t mean you could stop worrying about risk.

Never Let a Serious Crisis Go to Waste: How Neoliberalism Survived the Financial Meltdown by Philip Mirowski

"there is no alternative" (TINA), Adam Curtis, Alan Greenspan, Alvin Roth, An Inconvenient Truth, Andrei Shleifer, asset-backed security, bank run, barriers to entry, Basel III, Bear Stearns, behavioural economics, Berlin Wall, Bernie Madoff, Bernie Sanders, Black Swan, blue-collar work, bond market vigilante , bread and circuses, Bretton Woods, Brownian motion, business cycle, capital controls, carbon credits, Carmen Reinhart, Cass Sunstein, central bank independence, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, constrained optimization, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, dark matter, David Brooks, David Graeber, debt deflation, deindustrialization, democratizing finance, disinformation, do-ocracy, Edward Glaeser, Eugene Fama: efficient market hypothesis, experimental economics, facts on the ground, Fall of the Berlin Wall, financial deregulation, financial engineering, financial innovation, Flash crash, full employment, George Akerlof, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Greenspan put, Hernando de Soto, housing crisis, Hyman Minsky, illegal immigration, income inequality, incomplete markets, information asymmetry, invisible hand, Jean Tirole, joint-stock company, junk bonds, Kenneth Arrow, Kenneth Rogoff, Kickstarter, knowledge economy, l'esprit de l'escalier, labor-force participation, liberal capitalism, liquidity trap, loose coupling, manufacturing employment, market clearing, market design, market fundamentalism, Martin Wolf, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Naomi Klein, Nash equilibrium, night-watchman state, Northern Rock, Occupy movement, offshore financial centre, oil shock, Pareto efficiency, Paul Samuelson, payday loans, Philip Mirowski, Phillips curve, Ponzi scheme, Post-Keynesian economics, precariat, prediction markets, price mechanism, profit motive, public intellectual, quantitative easing, race to the bottom, random walk, rent-seeking, Richard Thaler, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, Savings and loan crisis, savings glut, school choice, sealed-bid auction, search costs, Silicon Valley, South Sea Bubble, Steven Levy, subprime mortgage crisis, tail risk, technoutopianism, The Chicago School, The Great Moderation, the map is not the territory, The Myth of the Rational Market, the scientific method, The Theory of the Leisure Class by Thorstein Veblen, The Wisdom of Crowds, theory of mind, Thomas Kuhn: the structure of scientific revolutions, Thorstein Veblen, Tobin tax, tontine, too big to fail, transaction costs, Tyler Cowen, vertical integration, Vilfredo Pareto, War on Poverty, Washington Consensus, We are the 99%, working poor

Shleifer’s model initially “seems” to call into question the validity of certain classes of dubious artificial derivatives by suggesting someone is being misled by the market; but as usual, the devil is in the details. Shleifer combines some “behavioral” themes with a standard neoclassical model to blame the crisis on the investors, who unaccountably ignore the extreme tail risk of newly invented derivatives when they are minted. In other words, the crisis happens because the suitably adjusted agents are blind to its possibility. (Rabbit in hat; rabbit out.) Actually, the EMH is not “refuted” so much as reinforced in the model, since “the market” still emits the correct signals (which really do come out of nowhere in the mathematics); as in most neoliberal scenarios, the crash is the fault of the victims beset with “local thinking” (Shleifer’s terminology) rushing to dump their wonky assets all at the same time.

More Money Than God: Hedge Funds and the Making of a New Elite by Sebastian Mallaby

Alan Greenspan, Andrei Shleifer, Asian financial crisis, asset-backed security, automated trading system, bank run, barriers to entry, Bear Stearns, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Bonfire of the Vanities, book value, Bretton Woods, business cycle, buy and hold, capital controls, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency manipulation / currency intervention, currency peg, deal flow, do well by doing good, Elliott wave, Eugene Fama: efficient market hypothesis, failed state, Fall of the Berlin Wall, financial deregulation, financial engineering, financial innovation, financial intermediation, fixed income, full employment, German hyperinflation, High speed trading, index fund, Jim Simons, John Bogle, John Meriwether, junk bonds, Kenneth Rogoff, Kickstarter, Long Term Capital Management, low interest rates, machine translation, margin call, market bubble, market clearing, market fundamentalism, Market Wizards by Jack D. Schwager, Mary Meeker, merger arbitrage, Michael Milken, money market fund, moral hazard, Myron Scholes, natural language processing, Network effects, new economy, Nikolai Kondratiev, operational security, pattern recognition, Paul Samuelson, pre–internet, proprietary trading, public intellectual, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, risk-adjusted returns, risk/return, Robert Mercer, rolodex, Savings and loan crisis, Sharpe ratio, short selling, short squeeze, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical arbitrage, statistical model, survivorship bias, tail risk, technology bubble, The Great Moderation, The Myth of the Rational Market, the new new thing, too big to fail, transaction costs, two and twenty, uptick rule

The precise magnitude of Tudor’s losses is unknown, but traders at other firms estimate that emerging-market loans fell by at least two thirds, and given that the portfolio was leveraged, Tudor’s $2 billion presumably fell by more than that. Meanwhile, Paul Jones explains, “What I missed was the tail risk associated with something that for the prior eight years our manager had risk managed through in an excellent fashion. And also something that all of a sudden took on characteristics that heretofore it had never taken on, which was one hundred percent correlation with the U.S. stock market.” Jones interview. 22.

Antifragile: Things That Gain From Disorder by Nassim Nicholas Taleb

"World Economic Forum" Davos, Air France Flight 447, Alan Greenspan, Andrei Shleifer, anti-fragile, banking crisis, Benoit Mandelbrot, Berlin Wall, biodiversity loss, Black Swan, business cycle, caloric restriction, caloric restriction, Chuck Templeton: OpenTable:, commoditize, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, discrete time, double entry bookkeeping, Emanuel Derman, epigenetics, fail fast, financial engineering, financial independence, Flash crash, flying shuttle, Gary Taubes, George Santayana, Gini coefficient, Helicobacter pylori, Henri Poincaré, Higgs boson, high net worth, hygiene hypothesis, Ignaz Semmelweis: hand washing, informal economy, invention of the wheel, invisible hand, Isaac Newton, James Hargreaves, Jane Jacobs, Jim Simons, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Kenneth Arrow, knowledge economy, language acquisition, Lao Tzu, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, Marc Andreessen, Mark Spitznagel, meta-analysis, microbiome, money market fund, moral hazard, mouse model, Myron Scholes, Norbert Wiener, pattern recognition, Paul Samuelson, placebo effect, Ponzi scheme, Post-Keynesian economics, power law, principal–agent problem, purchasing power parity, quantitative trading / quantitative finance, Ralph Nader, random walk, Ray Kurzweil, rent control, Republic of Letters, Ronald Reagan, Rory Sutherland, Rupert Read, selection bias, Silicon Valley, six sigma, spinning jenny, statistical model, Steve Jobs, Steven Pinker, Stewart Brand, stochastic process, stochastic volatility, synthetic biology, tacit knowledge, tail risk, Thales and the olive presses, Thales of Miletus, The Great Moderation, the new new thing, The Wealth of Nations by Adam Smith, Thomas Bayes, Thomas Malthus, too big to fail, transaction costs, urban planning, Vilfredo Pareto, Yogi Berra, Zipf's Law

Goldstein, 2012, “The Problem Is Beyond Psychology: The Real World Is More Random Than Regression Analyses,” International Journal of Forecasting 28(3), 715–716. Taleb, N. N., Elie Canetti, Elena Loukoianova, Tidiane Kinda, and Christian Schmieder, 2012, “A New Heuristic Measure of Fragility and Tail Risks: Application to Stress Testing,” IMF Working Paper. Tatonetti, Nicholas P., et al., 2012, “Data-Driven Prediction of Drug Effects and Interactions.” Science Translational Medicine 4, 125ra31, doi: 10.1126/scitranslmed.3003377. Taubes, G., 2008, Good Calories, Bad Calories: Fats, Carbs, and the Controversial Science of Diet and Health.

Big Data and the Welfare State: How the Information Revolution Threatens Social Solidarity by Torben Iversen, Philipp Rehm

23andMe, Affordable Care Act / Obamacare, algorithmic bias, barriers to entry, Big Tech, business cycle, centre right, collective bargaining, COVID-19, crony capitalism, data science, DeepMind, deindustrialization, full employment, George Akerlof, income inequality, information asymmetry, invisible hand, knowledge economy, land reform, lockdown, loss aversion, low interest rates, low skilled workers, microbiome, moral hazard, mortgage debt, Network effects, new economy, obamacare, personalized medicine, Ponzi scheme, price discrimination, principal–agent problem, profit maximization, Robert Gordon, speech recognition, subprime mortgage crisis, tail risk, The Market for Lemons, The Rise and Fall of American Growth, union organizing, vertical integration, working-age population

Hence, PYLL is also a good indicator of underlying risks that are not directly observed as a disorder.22 Specifically, countries using fewer and less precise diagnostic tests will see people die earlier from any given disease than countries with more and better tests. Life insurance companies thrive when they have access to accurate information about life expectancy and can exclude tail risks, which in turn depends on an established infrastructure of laboratories, testing technology, and expertise. Our assembled data set contains close to 600 country-year observations, covering 22 countries over the period from the early 1980s to the late 2010s. Year coverage varies by country, giving us an unbalanced cross-section time-series data set`.

Age of Greed: The Triumph of Finance and the Decline of America, 1970 to the Present by Jeff Madrick

Abraham Maslow, accounting loophole / creative accounting, Alan Greenspan, AOL-Time Warner, Asian financial crisis, bank run, Bear Stearns, book value, Bretton Woods, business cycle, capital controls, Carl Icahn, collapse of Lehman Brothers, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, desegregation, disintermediation, diversified portfolio, Donald Trump, financial deregulation, fixed income, floating exchange rates, Frederick Winslow Taylor, full employment, George Akerlof, Glass-Steagall Act, Greenspan put, Hyman Minsky, income inequality, index fund, inflation targeting, inventory management, invisible hand, John Bogle, John Meriwether, junk bonds, Kitchen Debate, laissez-faire capitalism, locking in a profit, Long Term Capital Management, low interest rates, market bubble, Mary Meeker, Michael Milken, minimum wage unemployment, MITM: man-in-the-middle, Money creation, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Myron Scholes, new economy, Nixon triggered the end of the Bretton Woods system, North Sea oil, Northern Rock, oil shock, Paul Samuelson, Philip Mirowski, Phillips curve, price stability, quantitative easing, Ralph Nader, rent control, road to serfdom, Robert Bork, Robert Shiller, Ronald Coase, Ronald Reagan, Ronald Reagan: Tear down this wall, scientific management, shareholder value, short selling, Silicon Valley, Simon Kuznets, tail risk, Tax Reform Act of 1986, technology bubble, Telecommunications Act of 1996, The Chicago School, The Great Moderation, too big to fail, union organizing, V2 rocket, value at risk, Vanguard fund, War on Poverty, Washington Consensus, Y2K, Yom Kippur War

Warren Buffett, who owned a large stake in Moody’s, the ratings agency, said at an investigatory hearing that almost no one had anticipated the problems. Alan Greenspan made similar comments in interviews. John Mack, head of Morgan Stanley, whose key mortgage trader lost $9 billion in a single trade, wiping out all the annual profits of the company in 2007, insisted the crisis was one of those events so rare it barely showed up statistically—a “tail risk” as it was now called. Bear Stearns CEO Jimmy Cayne (Illustration credit 19.1) Richard Fuld, CEO of Lehman Brothers, about to testify before Congress (Illustration credit 19.2) None of these claims was correct. Even if the housing market had only stopped rising rapidly, rather than plunging, Wall Street would have lost enormous amounts of money, jeopardizing the world credit markets.

Unelected Power: The Quest for Legitimacy in Central Banking and the Regulatory State by Paul Tucker

"Friedman doctrine" OR "shareholder theory", Alan Greenspan, Andrei Shleifer, bank run, banking crisis, barriers to entry, Basel III, battle of ideas, Bear Stearns, Ben Bernanke: helicopter money, Berlin Wall, Bretton Woods, Brexit referendum, business cycle, capital controls, Carmen Reinhart, Cass Sunstein, central bank independence, centre right, conceptual framework, corporate governance, diversified portfolio, electricity market, Fall of the Berlin Wall, financial innovation, financial intermediation, financial repression, first-past-the-post, floating exchange rates, forensic accounting, forward guidance, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, George Akerlof, Greenspan put, incomplete markets, inflation targeting, information asymmetry, invisible hand, iterative process, Jean Tirole, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, liberal capitalism, light touch regulation, Long Term Capital Management, low interest rates, means of production, Money creation, money market fund, Mont Pelerin Society, moral hazard, Northern Rock, operational security, Pareto efficiency, Paul Samuelson, price mechanism, price stability, principal–agent problem, profit maximization, public intellectual, quantitative easing, regulatory arbitrage, reserve currency, risk free rate, risk tolerance, risk-adjusted returns, road to serfdom, Robert Bork, Ronald Coase, seigniorage, short selling, Social Responsibility of Business Is to Increase Its Profits, stochastic process, subprime mortgage crisis, tail risk, The Chicago School, The Great Moderation, The Market for Lemons, the payments system, too big to fail, transaction costs, Vilfredo Pareto, Washington Consensus, yield curve, zero-coupon bond, zero-sum game

And, crucially, one of the US authorities’ innovations during the 2008–2009 phase of the crisis has given supervisors something concrete and important to say. Stress Testing: Finally, Something to Say in Public Since the spring of 2009, the Federal Reserve has led the world in seeking to undertake credible stress tests of banks’ capital adequacy. As well as being forward looking and focused on unlikely (tail) risks, the tests are conducted annually, concurrent for all firms above a certain size, systematic, and, by any previous standard of supervision, highly transparent.21 They help supervisors assess system resilience and make adjudicatory judgments on the safety and soundness of individual firms, taking into account correlated exposures across intermediaries.

Crashed: How a Decade of Financial Crises Changed the World by Adam Tooze

"there is no alternative" (TINA), "World Economic Forum" Davos, Affordable Care Act / Obamacare, Alan Greenspan, Apple's 1984 Super Bowl advert, Asian financial crisis, asset-backed security, bank run, banking crisis, Basel III, Bear Stearns, Berlin Wall, Bernie Sanders, Big bang: deregulation of the City of London, bond market vigilante , book value, Boris Johnson, bread and circuses, break the buck, Bretton Woods, Brexit referendum, BRICs, British Empire, business cycle, business logic, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Celtic Tiger, central bank independence, centre right, collateralized debt obligation, company town, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, currency risk, dark matter, deindustrialization, desegregation, Detroit bankruptcy, Dissolution of the Soviet Union, diversification, Doha Development Round, Donald Trump, Edward Glaeser, Edward Snowden, en.wikipedia.org, energy security, eurozone crisis, Fall of the Berlin Wall, family office, financial engineering, financial intermediation, fixed income, Flash crash, forward guidance, friendly fire, full employment, global reserve currency, global supply chain, global value chain, Goldman Sachs: Vampire Squid, Growth in a Time of Debt, high-speed rail, housing crisis, Hyman Minsky, illegal immigration, immigration reform, income inequality, interest rate derivative, interest rate swap, inverted yield curve, junk bonds, Kenneth Rogoff, large denomination, light touch regulation, Long Term Capital Management, low interest rates, margin call, Martin Wolf, McMansion, Mexican peso crisis / tequila crisis, military-industrial complex, mittelstand, money market fund, moral hazard, mortgage debt, mutually assured destruction, negative equity, new economy, Nixon triggered the end of the Bretton Woods system, Northern Rock, obamacare, Occupy movement, offshore financial centre, oil shale / tar sands, old-boy network, open economy, opioid epidemic / opioid crisis, paradox of thrift, Peter Thiel, Ponzi scheme, Post-Keynesian economics, post-truth, predatory finance, price stability, private sector deleveraging, proprietary trading, purchasing power parity, quantitative easing, race to the bottom, reserve currency, risk tolerance, Ronald Reagan, Savings and loan crisis, savings glut, secular stagnation, Silicon Valley, South China Sea, sovereign wealth fund, special drawing rights, Steve Bannon, structural adjustment programs, tail risk, The Great Moderation, Tim Cook: Apple, too big to fail, trade liberalization, upwardly mobile, Washington Consensus, We are the 99%, white flight, WikiLeaks, women in the workforce, Works Progress Administration, yield curve, éminence grise

The question was who would run against her: a traditional conservative, a centrist modernizer in the form of Emmanuel Macron or the real terror of the establishment, the left-wing Mélenchon? A Le Pen versus Mélenchon runoff was the nightmare of the markets.87 Whatever else divided these two, they had in common their antipathy toward Germany. In the spring of 2017 the world held its breath. The euro gyrated. European political uncertainty was the key “tail risk” for fund managers. The ECB’s bond buying was the one major source of stability. However unlikely the scenario, if Le Pen were to break through in France, it was hard to see how even the ECB’s largest program could have avoided another sovereign debt crisis. As it turned out, the center held. In every case the electorate opted against the populist right wing.

Money and Power: How Goldman Sachs Came to Rule the World by William D. Cohan

"Friedman doctrine" OR "shareholder theory", "RICO laws" OR "Racketeer Influenced and Corrupt Organizations", Alan Greenspan, asset-backed security, Bear Stearns, Bernie Madoff, Bob Litterman, book value, business cycle, buttonwood tree, buy and hold, collateralized debt obligation, Cornelius Vanderbilt, corporate governance, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, deal flow, diversified portfolio, do well by doing good, fear of failure, financial engineering, financial innovation, fixed income, Ford paid five dollars a day, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Gordon Gekko, high net worth, hiring and firing, hive mind, Hyman Minsky, interest rate swap, John Meriwether, junk bonds, Kenneth Arrow, London Interbank Offered Rate, Long Term Capital Management, managed futures, margin call, market bubble, mega-rich, merger arbitrage, Michael Milken, moral hazard, mortgage debt, Myron Scholes, paper trading, passive investing, Paul Samuelson, Ponzi scheme, price stability, profit maximization, proprietary trading, risk tolerance, Ronald Reagan, Saturday Night Live, short squeeze, South Sea Bubble, tail risk, time value of money, too big to fail, traveling salesman, two and twenty, value at risk, work culture , yield curve, Yogi Berra, zero-sum game

She suggested the mezzanine tranches be packaged up and sold as part of other CDOs. “We have been thinking collectively as a group about how to help move some of the risk,” she wrote in an e-mail released in January 2011 by the Financial Crisis Inquiry Commission. “While we have made great progress moving the tail risks—[super-senior] and equity—we think it is critical to focus on the mezz risk that has been built up over the past few months.… Given some of the feedback we have received so far [from investors,] it seems that cdo’s maybe the best target for moving some of this risk but clearly in limited size (and timing right now not ideal).”

Stigum's Money Market, 4E by Marcia Stigum, Anthony Crescenzi

accounting loophole / creative accounting, Alan Greenspan, Asian financial crisis, asset allocation, asset-backed security, bank run, banking crisis, banks create money, Bear Stearns, Black-Scholes formula, book value, Brownian motion, business climate, buy and hold, capital controls, central bank independence, centralized clearinghouse, corporate governance, credit crunch, Credit Default Swap, cross-border payments, currency manipulation / currency intervention, currency risk, David Ricardo: comparative advantage, disintermediation, distributed generation, diversification, diversified portfolio, Dutch auction, financial innovation, financial intermediation, fixed income, flag carrier, foreign exchange controls, full employment, Glass-Steagall Act, Goodhart's law, Greenspan put, guns versus butter model, high net worth, implied volatility, income per capita, intangible asset, interest rate derivative, interest rate swap, inverted yield curve, junk bonds, land bank, large denomination, locking in a profit, London Interbank Offered Rate, low interest rates, margin call, market bubble, market clearing, market fundamentalism, Money creation, money market fund, mortgage debt, Myron Scholes, offshore financial centre, paper trading, pension reform, Phillips curve, Ponzi scheme, price mechanism, price stability, profit motive, proprietary trading, prudent man rule, Real Time Gross Settlement, reserve currency, risk free rate, risk tolerance, risk/return, Savings and loan crisis, seigniorage, shareholder value, short selling, short squeeze, tail risk, technology bubble, the payments system, too big to fail, transaction costs, two-sided market, value at risk, volatility smile, yield curve, zero-coupon bond, zero-sum game

., Eurodollars foreign central banks, Fed foreign currency translation risk, BAs foreign-dominated commercial paper foreign exchange, commercial paper foreign-exchange market Fed intervention foreign-exchange risk, banks/banking foreign government bonds, Treasury futures foreign official holdings, Eurodollars foreign series bonds former forward market, federal funds market forward contracts, vs. futures forward forwards forward market, repos forward price, Treasury futures forward rate agreements (FRAs) advantages Eurodollars example features interest-rate expectations interest-rate swaps jargon market money market swaps precise hedge tiering forward transactions GIC FRAs (see forward rate agreements) fraud, dealers Freddie Mac (see Federal Home Loan Mortgage Corporation) free lunch, interest-rate swaps FSA (see Financial Services Act) FSLIC (see Federal Savings and Loan Insurance Corporation) full accrual pricing, Fed functions, money market funding a bank’s assets, domestic treasury funding choices, banks/banking funds flows by sector U.S. capital market funds, money (see money funds) funds rate, fed (see fed funds rate) funds rate targeting, fed funds transfer, Fedwire Funds Transfer Service future dates, immunizing a portfolio futures (see also Treasury futures) arbitrage basics bills futures CFTC clearing function CME commissions contract size counterparty risk day traders delivery electronic trading Eurodollars exchanges expiration dates fed funds futures financial futures vs. forward contracts hedging leverage liquidity margin deposits market makers market participants performance bonds pit trading portfolio diversification portfolios price quotes regulation risk scalpers SPAN speculation tick sizes transparency utility to investors futures markets arbitrage dealers Eurodollars technical analysis futures trading volume, Treasury futures futurity, bonds games, Treasury notes gamma, options gap, financing gap management domestic treasury interest-rate futures swaps GARVEEs (see Grant Anticipation Revenue Vehicles) GCF repos (see general collateral finance repos) general collateral finance (GCF) repos General Motors Acceptance Corporation (GMAC), commercial paper general obligation (GO) bonds general obligation (GO) securities GIC (see guaranteed income contract) Ginnie Mae (see Government National Mortgage Association) Glass-Steagall Act banks/banking global banks, Eurodollars global market, Eurodollars global master repurchase agreement (GMRA), repos global swap books GlobalCash-Europe96 survey, Eurodollars globalization banks/banking communications dealers debt markets investing payments systems trading systems GMAC (see General Motors Acceptance Corporation) GMRA (see global master repurchase agreement) GNMA (see Government National Mortgage Association) go-around, Fed GO (see general obligation securities) GO (general obligation) bonds Government National Mortgage Association (GNMA) pass-through securities REMICs Government Securities Act (1986) Government Securities Division, brokers’ market government-sponsored enterprises (GSEs) growth implicit guarantee Gramm-Leach-Bliley Act banks/banking merchant banks mergers and acquisitions Grant Anticipation Revenue Vehicles (GARVEEs) Greenspan, Alan gross debt, vs. net debt GSEs (see government-sponsored enterprises) guaranteed income contract (GIC), forward transactions haircuts, repos Hamilton, Alexander hawk/dove scale, Fed heading out, federal funds market hedges with basis risk hedging calendar spreads cash-and-carry trade cross hedging curve traders dealers Eurodollars futures hedge ratio hedges with basis risk interest-rate swaps long hedge with no basis risk risk second hedge with no basis risk spreading swap books Treasury Treasury bills Treasury futures zero-coupon approach hedging positions, MTNs HIC (see hold-in-custody repos) history banks/banking BAs ECP Eurodollars Fed federal funds market loans monetarism money market banks Treasury securities hold-in-custody repos (HIC) holding companies Bank Holding Company Act banks/banking IBFs (see International Banking Facilities) IDB (see interdealer brokers) ILCs (see industrial loan corporations) IMM (see International Monetary Market) immunizing a portfolio, future dates implicit guarantee, GSEs indexes, dealers indices Lehman aggregate index Lehman Brothers Global Family of Indices industrial loan corporations (ILCs), banks/banking industrial paper, commercial paper inflation data, trading notes inflation, Fed inflation-indexed securities, Treasury securities information, market sentiment (see market sentiment) information systems, market makers informational calls, discount window inside market, dealers institutional funds, money funds institutions, portfolios insurance, options integration banks/banking Eurodollars interbank placements, Eurodollars interdealer brokers (IDB), Treasury securities Interest Equalization Tax, Eurodollars interest-rate expectations, FRAs interest-rate futures, gap management interest-rate swaps 5-year, fixed-rate asset bank/nonbank dealers banks/banking bells and whistles bogy books brokers convergence trading counterparty risk coupon swaps currency swaps dealer books dealers defining dollar interest-rate-swap market end users Eurodollars exotic FRAs free lunch hedging ISDA jargon market makers master documentation netting offsetting a deposit parallel loans plain vanilla portfolios positive-sum game profit, swap books quanto risk Street-speak trading spreads interest rates auction procedures bonds dealers, predictions Fed FOMC Japan municipal securities (munis) nominal portfolios predictions, dealers real repo rate Treasury securities yield curve ZIRP intermediation banks/banking control Fed matched/mismatched book reasons total financial assets International Banking Act International Banking Facilities (IBFs), Eurodollars International Monetary Market (IMM), IMM swap International Swap Dealers Association (ISDA), interest-rate swaps internationalization, market for Treasuries Internet, electronic trading investing, globalization investors BAs CDs commercial paper corporations, munis ECP Eurobond market Eurodollar CDs loan participations money funds municipal securities (munis) ISDA (see International Swap Dealers Association) Japan deflation ZIRP jargon FRAs interest-rate swaps judgmental approach, Fed junk bonds buyers LBO loans latent investor demand, MTNs LBO loans bear-hug LBOs fears junk bonds legislation (see also regulation) Bank Holding Company Act Bank of England Act Banking Acts Check law Depository Institutions Deregulation and Monetary Control Act Employee Retirement Income Security Act (ERISA) Federal Reserve Act FSA Glass-Steagall Act Government Securities Act (1986) Gramm-Leach-Bliley Act International Banking Act Monetary Control Act (MCA) Riegle-Neal Banking and Branch Efficiency Act Sarbanes-Oxley Act Tax Reform Act Lehman aggregate index Lehman Brothers Global Family of Indices lender of last resort, Eurodollars lenders, Eurodollars lending business banks/banking Eurodollars letter repos portfolios leverage banks/banking futures repos liabilities/assets, corporate finance liability swaps LIBID (see London Interbank Bid Rate) LIBOR (London Interbank Offered Rate) Eurodollars interest-rate swaps lifting a leg, swap books LIMEAN, Eurodollars limits, Eurodollars LIONS (investment opportunity notes) liquidity commercial paper Eurodollars futures loan participations reverse market Treasury futures liquidity effect, federal funds market liquidity enhancements, commercial paper liquidity portfolios liquidity risk, BAs loan participations FASB investors LBO loans liquidity mechanics motivations sales volume short-term, high quality loans loans (see also distribution) asset-backed paper back-to-back banks/banking bullet commercial paper, backstop lines discount window distribution domestic treasury Eurodollars floating vs. fixed rate history ILCs junk bonds LBO loans loan participations parallel loans securitization short-term, high quality syndicated loans Treasury LOC (letter of credit) paper locked market, Eurodollars London Interbank Bid Rate (LIBID), Eurodollars London preeminence, Eurodollars long hedge with no basis risk long-term rates, yield curve M&A (see mergers and acquisitions) M1 Game, Fed MCA (see Monetary Control Act) Macaulay’s duration major players, Eurodollars margin deposits, futures market intelligence, Treasury futures market liquidity, commercial paper market makers analytics systems Bloomberg Professional system clearing banks communications dealers dealers as futures information systems interest-rate swaps MTNs trading systems market participants, futures market sentiment duration money funds Treasury futures marketable Treasury securities marking to market, portfolios master documentation, interest-rate swaps master notes, commercial paper master repo agreements, defining master repurchase agreement (MRA), defining matched/mismatched book covering shorts Eurodollars facilitation device Fed statistics financial intermediaries financing the dealer’s position functions generating borrowed funds growth mismatching the book, banks profit repos reverses trading collateral matched-sale purchases (MSPs) Fed repos maturities BAs CDs MTNs maturity choice dealers domestic treasury portfolios maturity distribution, BAs maturity of securities purchased, portfolios MBS (see mortgage-backed securities) medium-term money banks/banking Eurodollars medium-term notes (MTNs) 30/360 vs. actual/360 hurdle bank deposit notes bank notes banks/banking beginnings bells and whistles commercial paper vs. corporate bonds dealers Euro MTNs floating-rate MTNs growth, market hedging positions latent borrower demand latent investor demand market makers maturities Merrill money market swaps new-issue market new issues privately placed paper product rating secondary market shelf registration yields merchant banks Eurodollars Gramm-Leach-Bliley Act syndicated loans mergers and acquisitions (M&A) corporate finance Gramm-Leach-Bliley Act Merrill CMA money funds MTNs middleware trading platforms, electronic trading mismatch strategies banks/banking Eurodollars mismatching the book (see also matched/mismatched book) banks/banking MMDAs (see money market deposit accounts) monetarism downside Fed history pitfalls monetarist experiment, Fed Monetary Control Act (MCA) Fed monetary policy Fed implementing transmission effects Monetary Policy Report to Congress, Fed money center banks money creation money, defining money funds accounting procedures assets bank trust departments banks/banking central-asset accounts CMA consumers’uses demand notes flavors growth hot money institutional funds investing in investors management fee managing market sentiment Merrill money supply municipal securities (munis) penny-rounded fund portfolios raison d’être rising rates safety of principal STIFs strategies STRIPS tax-exempt taxable-fund portfolios VRDO withdrawing funds yields money market characteristics features functions overview scope money market banks (see also banks) history money market deposit accounts (MMDAs), Fed money market funds (see money funds) money market swaps arbitrage basis swaps classic deposit notes floating-to-floating swaps FRAs IMM swap MTNs speculative vehicle swapping spreads money supply control defining Fed fed funds rate federal funds market money funds mortgage-backed, pass-through securities mortgage-backed securities (MBS) MRA (see master repurchase agreement) MSPs (see matched-sale purchases) MTNs (see medium-term notes) multicurrency commercial paper municipal bond insurance, municipal securities (munis) municipal commercial paper municipal notes [see municipal securities (munis)] municipal securities (munis) BANs book entry brokers characteristics competitively bid deals corporations investors credit enhancements credit risk credit spreads dealers disclosure equivalent taxable yield GARVEEs GOs interest rates investors issuance market technicals money funds municipal bond insurance negotiated deals new-issue market price volatility RANs ratings real-time reporting revenue securities risk RTRS secondary market TANs tax reform Tax Reform Act taxable yield taxation TRANs types VRDO WI trading yearly issuance yield yield, taxable naked trading, dealers negative-sum game, portfolios negative value basis, Treasury futures negotiable order of withdrawal (NOW) accounts, Fed net debt, vs. gross debt net financial investment, by sector net interest margin, banks/banking net repo financing netting, interest-rate swaps new-issue market CDs MTNs municipal securities (munis) new issues, MTNs NIFs (see note issuance facilities) NOB (notes over bonds) trade, Treasury futures nominal interest rates, Fed nonborrowed-reserves procedure, Fed nonmarketable Treasury securities nonmember banks, discount window note issuance facilities (NIFs), ECP notes [see also medium-term notes; municipal securities (munis)] bank notes deposit notes trading notes Treasury notes Treasury securities NOW accounts (see negotiable order of withdrawal accounts) off–balance sheet items banks/banking Eurodollars off-the-run issues, Treasury notes oil dollars OPEC, Eurodollars open interest, Treasury futures open market operations (see also Federal Open Market Committee) Fed open repos open reverses, reverse market opening, brokers’ market operation twist, Fed opportunity cost portfolios risk options Black-Scholes model call options combining delta gamma insurance portfolios price of underlying asset prices put-call parity put options replication rho risk-free-rate speculation strike price theta time to maturity trading uses value valuing vega volatility zero-sum game options trading volume, Treasury futures out trades brokers’ market risk over-the-counter derivatives markets, global turnover over-the-counter foreign exchange derivatives markets, swaps market overnight money, federal funds market overnight rates, Eurodollars overnight repo rate overview, money market own-name dealer paper, commercial paper pace/professionalism brokers Eurodollars packs, Eurodollars par bonds parallel loans, interest-rate swaps pass-through securities Fannie Maes Freddie Mac GNMA mortgage-backed private passes, Fed payments systems (see also communications) globalization penny-rounded fund, money funds pension funds debt absorption ERISA Treasury performance bonds, futures performance tracking, portfolios petrodollars, Eurodollars Phillips curve, Fed pit trading, futures plain vanilla swaps defining policy anticipation hypothesis, yield curve policy, monetary (see monetary policy) policy statements Fed federal funds market political pressures, Fed portfolio diversification, futures portfolio managers, dealers portfolios accounting hang-up arbitrage asymmetric positions, investor/issuer banks/banking big shooters break-even reverse rate compounding computer programs contrarian view credit risk dedicated domestic treasury extension swaps Fed futures institutions interest-rate swaps interest rates letter repos liquidity managing marking to market maturity choice maturity of securities purchased money funds negative-sum game opportunity cost options parameters performance tracking relative value repos restrictive guidelines reverses to maturity riding the yield curve risk short-term shorting securities small software stability of return strategies Street’s view term repos time horizon tracking performance trends unified World Bank yield curve yield spreads position limits, dealers position profits, dealers positioning, dealers positive-sum game, interest-rate swaps positive value basis, Treasury futures predictive power, yield curve preexport, BAs premium bonds prepayment BAs commercial paper present value, bonds price auctions, Treasury price fluctuations, bonds price quotes bonds futures price risk bonds dealers price sensitivity, duration price value of an 01, duration price volatility bonds municipal securities (munis) prices, options primary dealers Fed Treasury notes Treasury securities prime demise, corporate finance principal amount, Treasury futures principal investments, dealers principals, dealers private pass-throughs profit banks/banking matched/mismatched book position profits swap books Treasury notes profit sources, dealers proprietary products, dealers protocols, bill market put-call parity, options put options quanto interest-rate swaps quotes and maturities, Eurodollars quotes to retail, bill market quoting the market, brokers’ market raison d’être, Fed RANs (see Revenue Anticipation Notes) rate lid on bonds, Treasury rate risk, corporate finance rating tiering, commercial paper ratings commercial paper municipal securities (munis) REA series bonds (see Rural Electrification Administration series bonds) real estate mortgage investment conduits (REMICs), GNMA real interest rates real market bill market brokers’ market real-time reporting, municipal securities (munis) Real-Time Transaction Reporting System (RTRS), municipal securities (munis) real yields factors affecting trading notes rebooking, federal funds market recession probabilities, yield curve REFCorp (see Resolution Funding Corporation) refunding provisions, bonds regularization of debt, Treasury regulated securities, vs. exempt securities regulation (see also deregulation; legislation) Bank of England banks/banking Eurodollars foreign banks in London futures Regulation Q, Eurodollars regulatory purposes, Treasury regulatory reforms, repos relative value dealers portfolios REMICs (see real estate mortgage investment conduits) replication, options repos (see also reverses) brokering collateralized loan continuing contract credit risk dealer leverage dealer safekeeping dealers defining definitions domestic treasury Fed open market operations Fed statistics Fed use forward market full accrual pricing GCF repos GMRA Government Securities Act (1986) haircuts HIC letter repos margin market market decisions market growth master repo agreements matched/mismatched book MRA MSPs net repo financing open market operations open repos overnight repo rate portfolios regulatory reforms repo market repo rate repo rate, overnight reverse in reverse market right of substitution SEC term repos tri-party repos yield curve repurchase agreements (see repos) reputation risk, BAs reserve adjustments, federal funds market reserve requirements contemporaneous reserve accounting Fed reserves available to support private deposits (RPDs), Fed reserves-oriented operating procedure, Fed Resolution Funding Corporation (REFCorp) S&L crisis restrictive guidelines, portfolios Revenue Anticipation Notes (RANs) revenue bonds revenue securities, municipal securities (munis) reverse in dealers repos reverses (see also repos) borrowers brokering brokers dealers defining discount window Fed statistics Fed use Government Securities Act (1986) liquidity matched/mismatched book open reverses reverse market reverse rate risk SEC special collateral repo market specific issues market term reverses reverses to maturity portfolios reversing in securities, vs. borrowing securities revolving underwriting facilities (RUFs), ECP rho, options riding the yield curve, portfolios Riegle-Neal Banking and Branch Efficiency Act right of substitution, repos risk accounting hang-up arbitrage banks/banking BAs bonds brokers brokers’ market commercial paper communications counterparty risk country risk credit risk, BAs credit risk, municipal securities (munis) credit risk, portfolios credit risk, repos dealers Eurodollars foreign-exchange risk futures hedging interest-rate swaps municipal securities (munis) opportunity cost out trades portfolios price risk rate risk, corporate finance reverse market sovereign risk SPAN tails risk analysis, bonds risk-free rate, options risk premium, yield curve role, Fed roll-down, bonds round robin, fails RP agreements (see repos) RPDs (see reserves available to support private deposits) RTRS (see Real-Time Transaction Reporting System) RUFs (see revolving underwriting facilities) Rural Electrification Administration (REA) series bonds Russia, Eurodollars S&L crisis (see savings and loan crisis) sale-repurchase agreement, defining sales force, dealers Sallie Mae (see Student Loan Marketing Association) Sarbanes-Oxley Act, banks/banking Saturday Night Special savings and loan (S&L) crisis, federal agencies savings bonds debt absorption savings deposits, domestic treasury scalpers, futures scope, money market screens, brokers’ seasonal credit, discount window seasoning, Treasury notes SEC (see Securities and Exchange Commission) second hedge with no basis risk secondary market commercial paper dealers MTNs municipal securities (munis) Treasury securities securities governments vs. corporates maturity choice portfolios security choice taxable bond portfolios Securities and Exchange Commission (SEC) commercial paper repos/reverses Treasury securities Securities Industry Association (SIA), banks/banking Securities Investment Board (SIB) securitization banks/banking deregulation loans security choice, domestic treasury sentiment, market (see market sentiment) Separate Trading of Registered Interest and Principal Securities (STRIPS) arbitrage market STRIPS outstanding trading Treasury securities servicing customers, dealers settlement date, discount window settlement, Treasury securities settlement Wednesday, federal funds market short coupons, Treasury notes Short-Term European Paper (STEP), European commercial paper short-term, high-quality loans short-term investment funds (STIFs), money funds short-term investment pools (STIPs), money funds short-term portfolios short-term rates, Eurodollars shorting, dealers shorting securities, portfolios SIA (see Securities Industry Association) SIB (see Securities Investment Board) SLUGS (see State and Local Government Series) small portfolios Society for Worldwide Interbank Financial Telecommunications (SWIFT), Eurodollars soft arbitrage software, portfolios SOMA (see system open market account) sovereign borrowers, commercial paper sovereign risk SPAN (see standard portfolio analysis of risk) special collateral repo market, reverses specific issues market, reverses speculation dealers futures options Treasury speculative-grade bonds speculative vehicle, money market swaps spread products, Fed spreading, hedging spreads, bonds stability of return, portfolios standard portfolio analysis of risk (SPAN), futures State and Local Government Series (SLUGS) debt absorption Treasury securities STEP (see Short-Term European Paper) STIFs (see short-term investment funds) STIPs (see short-term investment pools) strategies money funds portfolios Street-speak, interest-rate swaps Street’s view, portfolios strike price, options STRIPS (see Separate Trading of Registered Interest and Principal Securities) strips, Treasury Student Loan Marketing Association (Sallie Mae) subscription issues, Treasury supply, money (see money supply) swap books assignment brokering global hedging lifting a leg profit swaps (see also interest-rate swaps; money market swaps) arbitrage cross-currency swaps dollars into yen Eurodollars gap management mechanics swapping yen into dollars swaps curve Eurodollars swaps market CDSs over-the-counter foreign exchange derivatives markets sizing up swaptions SWIFT (see Society for Worldwide Interbank Financial Telecommunications) syndicated loans ECP Eurodollars fees mechanics merchant banks system open market account (SOMA), Fed T-accounts, Eurodollars T-bills TAAPS (see Treasury Automated Auction Processing System) TABs (see tax anticipation bills) tail management, dealers tails dealers risk TANs (see Tax Anticipation Notes) targets, Fed Tax and Revenue Anticipation Notes (TRANs) tax anticipation bills (TABs), Treasury Tax Anticipation Notes (TANs) tax-exempt commercial paper tax-exempt money funds Tax Reform Act, municipal securities (munis) tax reform, municipal securities (munis) taxable bond portfolios, domestic treasury taxable-fund portfolios, money funds taxation, municipal securities (munis) team, trading technical analysis dealers futures markets technical arbitrage TED spread (see Treasury versus Eurodollar spread) Tennessee Valley Authority (TVA) term fed funds, federal funds market term repos arbitrage portfolios term reverses, reverse market term structure of interest rates, duration terminology, Eurodollars theta, options thrift CDs thrifts, discount window tiering across borders BAs CDs Eurodollars FRAs TIGRS (Treasury income growth receipts) time-deposit market, Eurodollars time deposits time drafts time horizon, portfolios time to maturity, options TIPS (see Treasury Inflation-Protected Securities) tolerance ranges, Fed top U.S. banks tracking performance, portfolios traders, dealers trading (see also electronic trading) banks/banking chain dealers team trading hours, Eurodollars trading notes announcements complexity data inflation data real yields trading options trading spreads, interest-rate swaps trading systems communications globalization market makers trading the sheet, brokers’ market TRANs (see Tax and Revenue Anticipation Notes) transaction risk, BAs transitory arbitrage transmission effects Fed monetary policy transparency futures Treasury Treasury bill auctions bill strips cash management bills debt absorption debt management, historical debt management, today debt regularization economic uses exchange offerings financing use hedging loans pension funds price auctions rate lid on bonds regularization of debt regulatory purposes speculation strips subscription issues TABs transparency yield auctions Treasury Automated Auction Processing System (TAAPS), Treasury securities Treasury balances, Fed Treasury bills hedging Treasury futures accrued interest basis basis trading bond basis calendar spreads carry carry-adjusted basis cheapest to deliver contract convergence conversion factor COT report deliverable grades delivery factor delivery options delivery period delivery provisions factor bias foreign government bonds forward price futures trading volume hedging invoice price invoicing principal liquidity market intelligence market sentiment NOB trade open interest options trading volume principal amount switch option timely deliveries TUT spread value basis yield-enhancement trade Treasury income growth receipts (TIGRS) Treasury Inflation-Protected Securities (TIPS) Treasury notes brokers current issues dealers games notes vs. notes off-the-run issues primary dealers profit seasoning short coupons trading notes trading with retail WI trading Treasury securities active market attraction to investors auction procedures benchmark status bidding systems bill auctions bills bond market bonds book-entry securities brokers debt absorption Dutch auctions ECN electronic trading expansion FICC flower bonds history IDB inflation-indexed securities interest rates marketable nonmarketable notes ownership primary dealers SEC secondary market settlement SLUGS STRIPS summary TAAPS TIPS trading volume types vs.