{"id":4555,"date":"2019-11-22T18:17:01","date_gmt":"2019-11-22T22:17:01","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=4555"},"modified":"2022-03-11T16:26:30","modified_gmt":"2022-03-11T20:26:30","slug":"black-swan-finance","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/black-swan-finance\/","title":{"rendered":"Black Swans in Finance: What They Are, How to Prepare"},"content":{"rendered":"\n<p><a href=\"https:\/\/www.shortform.com\/blog\/black-swan-theory\/\">What is a black swan<\/a> in finance? Is there a way to predict and prepare for black swans in finance?<\/p>\n\n\n\n<p>We&#8217;ll look at some examples of black swans in the financial world and business and explore how to best prepare for future black swans.<\/p>\n\n\n\n<!--more-->\n\n\n\n<h2 class=\"wp-block-heading\">Black Swans<\/h2>\n\n\n\n<p><em>The Black Swan<\/em> is the second book in former options trader Nassim Nicholas Taleb\u2019s five-volume series on uncertainty. This book analyzes so-called \u201cBlack Swans\u201d\u2014extremely unpredictable events that have massive impacts on human society.<\/p>\n\n\n\n<p>In his April 2007 review of <em>The Black Swan <\/em>in the <em>New York Times<\/em>, Gregg Easterbrook, riffing on the author\u2019s skepticism about forecasts of any kind, noted, \u201cAt the beginning of 2006, the <em>Wall Street Journal <\/em>forecast a bad year for stocks; the Dow Jones Industrial Average rose 16% that year. (Disturbingly, the <em>Journal <\/em>has forecast a good year for 2007.)\u201d Mere months later, the world economy would be in a tailspin\u2014and <a href=\"https:\/\/www.shortform.com\/blog\/nassim-nicholas-taleb\/\">Nassim Nicholas Taleb<\/a>, who in <em>The Black Swan <\/em>warned that the global financial system was vulnerable to collapse, would be treated as a seer. Black swans in business and finance are rare, but they have monumental consequences.<br><\/p>\n\n\n\n<p>The Black Swan is named after a classic error of induction wherein an observer assumes that because all the swans he\u2019s seen are white, all swans <em>must <\/em>be white. Black Swans have three salient features:<br><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>They are rare (statistical outliers);<\/li><li>They are disproportionately impactful; and, because of that outsize impact,&nbsp;<\/li><li>They compel human beings to explain <em>why <\/em>they happened\u2014to show, after the fact, that they were indeed predictable.<\/li><\/ul>\n\n\n\n<p>Taleb\u2019s thesis, however, is that <strong>Black Swans, by their very nature, are<em> always <\/em>unpredictable<\/strong>\u2014they are the \u201cunknown unknowns\u201d<em> <\/em>for which even our most comprehensive models can\u2019t account. The <a href=\"https:\/\/www.shortform.com\/blog\/importance-of-the-fall-of-the-berlin-wall\/\">fall of the Berlin Wall<\/a>, the 1987 stock market crash, the creation of the Internet, 9\/11, the 2008 financial crisis\u2014all are Black Swans. Many black swans in finance have a huge economic impact.<br><\/p>\n\n\n\n<p>Once Taleb introduces the concept of the Black Swan in finance, he delves into human society and psychology, analyzing why modern civilization invites wild randomness and why humans can neither accept nor control that randomness.<br><\/p>\n\n\n\n<p><a href=\"https:\/\/www.shortform.com\/blog\/extremistan\/\">Extremistan<\/a> is defined by extreme <em>concentration<\/em>\u2014of prestige, income, capital, influence, size, or what have you. <strong>These concentrations create the <em>appearance<\/em> of stability\u2014larger, more powerful entities are more resilient\u2014but they actually create the potential for catastrophic black swans<\/strong>.<br><\/p>\n\n\n\n<p>The example par excellence of the risks of concentration is the banking industry. The explosive growth and interrelation of the major global financial institutions were the catalysts for the Great Recession of 2008.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Limits of the Bell Curve and Black Swans in Finance<\/h3>\n\n\n\n<p>One of the reasons black swans in finance are so visible is that they have a huge impact and they&#8217;re rarely predicted. One of the reasons black swans in business and finance surprise us is that analysts use the wrong tools.<\/p>\n\n\n\n<p>The classic bell curve\u2014which is also called the \u201cGaussian distribution\u201d after German mathematician Carl Friedrich Gauss\u2014is an accurate description of <a href=\"https:\/\/www.shortform.com\/blog\/mediocristan\/\">Mediocristan<\/a> phenomena, but it is dangerously misleading when it comes to Extremistan.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Black Swans in Finance, Example #1<\/h4>\n\n\n\n<p>In our contemporary moment, the most egregious misuse of <a href=\"https:\/\/www.shortform.com\/blog\/the-bell-curve\/\">bell curves<\/a> can be found among economists and financial-industry analysts. Most economists, including many Nobel Prize\u2013winners, treat financial markets as though they hail from Mediocristan when, in fact, they\u2019re from Extremistan.<br><\/p>\n\n\n\n<p>A stunning example of economists\u2019 misinterpretation of the market came in 1998, with the collapse of Long-Term Capital Management (LCTM), a hedge fund that included among its founding partners two Nobel Prize\u2013winners, Myron Scholes and Robert C. Merton (Robert K. Merton\u2019s son). Scholes and Merton won their Nobel Prize for a theory of stock option pricing; the theory, however, was based on a Gaussian model of the market that excluded the possibility of Black Swans.<br><\/p>\n\n\n\n<p>When markets were disrupted by the Asian financial crisis of 1997 and the Russian financial crisis of 1998\u2014a one-two punch of Black Swans\u2014Scholes and Merton\u2019s theory was revealed for the fantasy it was. The twin crises resulted in a crushing $4.6 billion loss for LCTM in fewer than four months. The firm had to be bailed out by a consortium of private banks, at the behest of the Federal Reserve.&nbsp;<br><\/p>\n\n\n\n<p>The problem is that economists\u2019 models are thoroughly Platonified: self-consistent, but bearing almost no resemblance to reality. <strong>Economists are like philosopher John Locke\u2019s madmen: they reason \u201ccorrectly from erroneous premises.\u201d<\/strong> This causes us to be totally unprepared for black swans in finance.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Flawed Methods of Predicting <\/strong>Black Swans in Finance<\/h2>\n\n\n\n<p>Why are we so impacted by black swans in finance? Because experts both (1) \u201ctunnel\u201d into the norms of their particular discipline and (2) base their predictive models exclusively on past events, their predictions are inevitably susceptible to the extremely random and unforeseen.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Black Swans in Finance, Example #2<\/h4>\n\n\n\n<p>Consider, for example, a financial analyst predicting the price of a barrel of oil in ten years. This analyst may build a model using the gold standards of her field: past and current oil prices, car manufacturers\u2019 projections, projected oil-field yields, and a host of other factors, computed using the techniques of regression analysis. The problem is that this model is innately narrow. It can\u2019t account for the truly random\u2014a natural disaster that disrupts a key producer, or a war that increases demand exponentially.<br><\/p>\n\n\n\n<p>Taleb draws a key distinction between experts in Extremistan disciplines (economics, finance, politics, history) and Mediocristan disciplines (medicine, physical sciences). Experts like biologists and astrophysicists are able to predict events with fair accuracy; experts like economists and financial planners are not.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>In Finance, Adopt the \u201cBarbell Strategy\u201d<\/strong><\/h3>\n\n\n\n<p>When Taleb was a trader, he pursued an idiosyncratic investment strategy to inoculate himself against a Black Swan in finance. He devoted 85%\u201390% of his portfolio to extremely safe instruments (Treasury bills, for example) and made extremely risky bets\u2014in venture-capital portfolios, for example\u2014with the remaining 10%\u201315%. (Another variation on the strategy is to have a highly speculative portfolio but to insure yourself against losses greater than 15%.) The high-risk portion of Taleb\u2019s portfolio was highly diversified: <strong>He wanted to place as many small bets as possible to increase the odds of a Black Swan in finance paying off in his favor<\/strong>.<br><br>The \u201cbarbell strategy\u201d is designed to minimize the pain of a negative Black Swan while, potentially, reaping a positive Black Swan\u2019s benefits. If the market collapses, a person pursuing this strategy isn\u2019t hurt beneath the \u201cfloor\u201d of the safe investments (say, 85%), but if the market explodes, he has a chance to capitalize by virtue of the speculative bets.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">History of Taleb&#8217;s Fascination with Black Swans in Finance<\/h2>\n\n\n\n<p>When and where did Taleb first come up with the idea of the black swan in finance?<\/p>\n\n\n\n<p>In the 1980s, as the war in Lebanon continued to rage, Taleb found himself in business school at the University of Pennsylvania\u2019s Wharton School. There, he discovered that the triplet of opacity didn\u2019t just affect his countrymen\u2014it affected his professors and the powerful corporate executives who came to lecture as well. Taleb realized that <em>no one\u2014<\/em>not even the \u201csmartest\u201d businesspeople in the world\u2014was prepared for <a href=\"https:\/\/www.shortform.com\/blog\/what-is-a-black-swan-event\/\">Black Swan events<\/a>.<br><\/p>\n\n\n\n<p>That realization became even more stark on October 19, 1987, when global stock markets crashed.<br><\/p>\n\n\n\n<p>At the time, Taleb was working for Credit Suisse First Boston; his specialty, honed at Wharton, was \u201cquantitative finance\u201d\u2014the application of complex mathematical models to markets to mitigate uncertainty. Taleb, however, used his knowledge as a \u201cquant\u201d not to apply those mathematical models directly, but to suss out <em>where those models failed <\/em>and invest accordingly. In other words, whereas everyone else was flying blind and didn\u2019t know it,<strong> Taleb was flying blind and <\/strong><strong><em>did <\/em><\/strong><strong>know it<\/strong><strong><em>, <\/em><\/strong><strong>and he placed bets that would pay off if the models were wrong<\/strong>.<br><\/p>\n\n\n\n<p>On the day of the crash, he was vindicated. So much so that his bonus was tantamount to \u201cF*** you\u201d money\u2014that is, it was large enough that he no longer needed to work to earn money. He chose to stay in finance, but he customized his roles so that he could spend ample time in solitude and contemplation.&nbsp;<br><\/p>\n\n\n\n<p>The focus of his sabbaticals? <em>Uncertainty<\/em>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Black Swans in Finance, Example #3: Faulty Reasoning<\/h2>\n\n\n\n<p>An example of faulty inductive reasoning from the world of finance concerns the hedge fund Amaranth (ironically named after a flower that\u2019s \u201cimmortal\u201d), which incurred one of the steepest losses in trading history: $7 billion in less than a week. Just days before the company went into tailspin, Amaranth had reminded its investors that the firm employed twelve risk managers to keep losses to a minimum. The problem was that these risk managers\u2014or suckers\u2014based their models on the market\u2019s <em>past performance<\/em>.&nbsp;The tailspin was a black swan in finance.<\/p>\n\n\n\n<p><br>In order not to be suckers of black swans in business and finance, we must (1) cultivate an \u201c<strong><a href=\"https:\/\/www.shortform.com\/blog\/empirical-skepticism-philosophy\/\">empirical skepticism<\/a><\/strong>\u201d\u2014that is, a skepticism steeped in fact and observation\u2014and (2) remain vigilant against the innately human tendencies that leave us vulnerable to Black Swans.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Who&#8217;s Most Susceptible to <\/strong>Black Swans in Finance?<\/h2>\n\n\n\n<p>The most arrogant group in terms of their predictions of black swans in finance\u2014and least aware of their own ignorance\u2014are so-called \u201cexperts.\u201d These are the credentialed and\/or laureled people whose opinions are granted weight by society.<br><\/p>\n\n\n\n<p>Taleb divides this group by two. There are those who are arrogant but also display some degree of competence, and then there are those who are arrogant <em>and <\/em>incompetent.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Incompetent Arrogants<\/strong><br><\/h3>\n\n\n\n<p>\u201cIncompetent Arrogants\u201d are \u201cexperts\u201d whose predictive abilities and skills aren\u2019t significantly greater than the average person\u2019s. This group includes <strong>stockbrokers, intelligence analysts, clinical psychologists, psychiatrists, economists, finance professors, and personal financial advisors<\/strong>.<br><\/p>\n\n\n\n<p>In numerous empirical studies, the forecasting ability of the \u201cincompetent arrogants\u201d has been shown to be almost nonexistent.<br><\/p>\n\n\n\n<p>For example, over the course of several years, psychologist Philip Tetlock asked almost 300 specialists\u2014political scientists, economists, journalists, and politicians\u2014to offer predictions of world events (the timeframe was usually \u201cwithin the next five years\u201d). <strong>He discovered that the experts\u2019 predictions were barely more accurate than random selection and often worse than simple computer simulations<\/strong>.&nbsp;<br><\/p>\n\n\n\n<p>He also found that the more prominent a person was in his or her field, the worse were his or her predictions<em>.<\/em> The reason for this finding was that prominent people tend to become prominent based on their having <em>one big idea<\/em>. These experts marry themselves to their singular idea and neglect other possibilities\u2014and thus, when randomness rears its head, they\u2019re shown to have been woefully misguided.<br><\/p>\n\n\n\n<p>Tetlock\u2019s main interest, however, wasn\u2019t the fact of experts\u2019 poor forecasting abilities but rather those experts\u2019 <em><a href=\"https:\/\/www.shortform.com\/blog\/lack-of-accountability\/\">lack of accountability<\/a> <\/em>for being wrong. He found that experts (unconsciously) employ a number of excuses to explain away their errors.&nbsp;<\/p>\n\n\n\n<p>A major problem with financial and governmental projections is that <strong>they don\u2019t incorporate a margin of error<\/strong>. That is, the authors of these projections don\u2019t take into account (nor do they publicize) how significantly their projections might be off-target.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Preparing for <\/strong>Black Swans in Finance<\/h2>\n\n\n\n<p><strong>Distinguish Between Positive Contingencies and Negative Ones<\/strong><\/p>\n\n\n\n<p>Different areas of society have different exposure to Black Swans, both positive and negative.&nbsp;<br><\/p>\n\n\n\n<p>For example, scientific research and moviemaking are \u201cpositive Black Swan areas\u201d\u2014catastrophes are rare, and there is always the possibility of smashing success. The stock market or catastrophe insurance, meanwhile, are \u201cnegative Black Swan areas\u201d\u2014upsides are relatively modest compared to the possibility of financial ruin.&nbsp;<br><\/p>\n\n\n\n<p>It\u2019s important to note that the history of a negative\u2013Black Swan area will underrepresent the possibility of catastrophe. An obvious example is financial markets, which always appear stable until they crash. Positive\u2013Black Swan areas, oppositely, will underrepresent the possibility of serendipity: Despite years of research, a cure for cancer hasn\u2019t been found; but one <em>could <\/em>be found any day.<\/p>\n\n\n\n<p><br>Suffice it to say, <strong>we should take more risks in a positive Black Swan area in finance than in a negative Black Swan one<\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>What is a black swan in finance? Is there a way to predict and prepare for black swans in finance? We&#8217;ll look at some examples of black swans in the financial world and business and explore how to best prepare for future black swans.<\/p>\n","protected":false},"author":4,"featured_media":4573,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[45,31],"tags":[60],"class_list":["post-4555","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business","category-money","tag-black-swan","","tg-column-two"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.3 (Yoast SEO v24.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Black Swans in Finance: What They Are, How to Prepare - Shortform Books<\/title>\n<meta name=\"description\" content=\"What is a black swan in finance? A black swan is an unpredictable event with a massive impact on society. 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