Fooled By Randomness: The Hidden Role of Chance in Life and in the Markets

This chapter presents a side-by-side comparison of two different individuals. The first is Nero Tulip. Nero is an intellectual who pursues a career in finance after he witnesses a man pull up in a red Porsche in front of the Chicago Stock Exchange. The man rushes into his office, leaving the car running and blocking traffic. Eventually, a worker at the office comes out to properly park the man’s car. Taleb refers to this moment as “a coup de foudre, a sudden intense (and obsessive) infatuation that strikes like lightning” (38). The excitement and bustle of the business world appeals more to him than the quiet and pedestrian lifestyle of an academic, the profession he had been pursuing.

The narrative jumps forward 10 years. Nero insists that the profession of a trader is the most exciting profession available to anyone. Nero is skilled at communication and can employ both the speech patterns of academia and the more vulgar style of the stock market floor. He is highly educated having enrolled in a PhD program in statistics in which he eventually lost interest.

Nero quickly moves up the ranks in the profession and leaves Chicago to move to New York where he works on Wall Street. Although he is successful, he does not like the glitzy lifestyle of a successful trader. Eventually, he shifts gears and becomes a proprietary trader, which affords him much more independence and the ability to work at his own pace while also enjoying his intellectual pursuits. Taleb points out that Nero’s trading style is conservative; he does not pursue high-risk ventures, instead opting to accumulate wealth in more predictable, albeit less financially lucrative ways. His strategy makes him less vulnerable to rare events such as crashes and other calamities.

The other character introduced in this section is named John. John is a high-yield trader, though not anywhere near Nero’s intellectual equivalent. John is ostentatious about his success, buying bigger and bigger houses and driving luxury sports cars. John’s wife also shows off their wealth, which irritates Nero’s wife. The way John parades his wealth and success makes Nero feel both contempt and envy. Nero recognizes that he is superior to John in almost every dimension, especially as it relates to intelligence. Nero secretly starts to wish for John’s downfall, and one day, his wish comes true. Nero sees John outside, shoddily dressed and smoking a cigarette. His posture signals to Nero that John has been fired. But that is only part of it. John has lost everything to bankruptcy. Nero feels shame about his ill wishes, but John’s story also reinforces to Nero that his conservative trading strategy is the right one, since it is much less likely that he will ever end up experiencing such total failure.

The chapter shifts away from the narrative of Nero and John. Taleb discusses the relationship between success and the levels of the neurotransmitter serotonin in the brain, particularly as this relationship manifests itself in trading. The more intensely one experiences high-risk victories, the more one is likely to have an increase in serotonin in the brain. Such a person is also likely to have a demeanor and posture that suggests their success. When a random adverse event happens, and they experience a catastrophic loss, that demeanor likewise changes. Taleb mentions that a taxi driver once told him that he could tell which traders are doing well and which ones are not simply by the way they carry themselves.

Finally, Taleb closes the chapter by comparing Nero’s conservative trading strategy to John’s high-risk strategy. Nero is protected against catastrophe because he plans around black swan events; however, because of this approach, he misses opportunities to achieve the same heights of success that John does. Taleb asks the reader to imagine if Nero had to live his life a million times over. Since he plans for the rare event, it is highly unlikely that one random event would bring him either great fortune or misfortune. Taleb then asks us to consider another hypothetical: A person named John Doe A, a janitor who wins the lottery and moves into a new neighborhood next to John Doe B, a dentist. If John Doe A’s life were to be lived a million times over, he would likely be a janitor in all of them. John Doe B would experience very little variation between extreme success or catastrophic loss in different lives.

Taleb introduces the concept of alternative histories. He says that alternative histories are the only way one should judge any performance in a field. Rather than measuring the performance based on the outcome, it is better to measure it against the cost of the alternative outcome. He uses the infamous game of Russian Roulette as an analogy to help explain the concept. Taleb says that of the six possible outcomes (corresponding to the number of chambers in a revolver), only one is observed. The winner is the person who survives the trigger pull when the chamber is empty. Taleb contends that the more one plays the game, the more likely they are to experience a loss, which in the case of Russian Roulette is death. Taleb equates this to trading. The tendency is to see the rewards of high-risk trading without acknowledging alternative outcomes. At some point, as was the case for John in the previous chapter, risky trading strategies will lead to potentially catastrophic losses.

Taleb notes that the idea of alternative histories has been covered in other academic disciplines. In philosophy, Taleb points to the work of 17th-century German philosopher and mathematician Leibniz and his idea of possible worlds. Leibniz posited that the world that we exist in is just one of an infinite number of possible worlds; we exist in this one in particular, Leibniz argued, because God selected it. Taleb mentions that there are branches of philosophy that have stemmed from Leibniz’s possible worlds idea and investigates whether there is any property that is the same throughout all possible worlds. He then discusses how in quantum mechanics, the possible worlds concept leads to the idea of parallel universes. Finally, he discusses how economics incorporates the possible worlds concept.

Taleb shifts back to the Russian Roulette analogy, saying that “reality is more vicious” than even that game (59). First, he asserts that after a series of successes, the person winning the game tends to underestimate the risk that he encounters each time he plays. The player gains a false sense of security, which Taleb defines as the Black Swan problem. Secondly, unlike Russian Roulette, which has well-defined risks, reality does not offer clarity about the odds of our choices. One could have a false sense of confidence that they are engaged in a low-risk activity while they are in fact engaged in a high-risk activity.

Taleb states that randomness is an abstract concept and by nature is difficult to accurately measure. Because of this, Taleb argues that using a more scientific approach to risk analysis is beneficial, and states that a scientific mind that is intellectually driven but also restless and unwilling to settle on one specific scientific problem is the most beneficial. Nero from the previous chapter is an example of this kind of mind. Taleb sees a continuum of how people approach risk from those who pay no attention to it to those who are tortured by it. Taleb argues that many MBAs, especially of the 1980s era when he began his work on Wall Street, were of the former category. In the 1990s, according to Taleb, more people with backgrounds in science populated Wall Street, which he says introduced a higher degree of intellectual depth. Taleb states that while the scientific people had a better success rate overall than the MBAs, they still struggled with practical knowledge. However, Taleb points out that “on occasion a fast-thinking scientific-minded person with street smarts would emerge” (63) to demonstrate the utility of a combination of the practicality of the businessperson with the intellectual curiosity of the scientist.

Taleb shifts gears and discusses two of his former bosses. The first, Kenny, appeared on the surface to be the kind of person one would want for a boss. He was a family man who tended to have a very conservative approach to life, except when it came to trading. He relied heavily on high-risk ventures, and though he was polite as a boss, Taleb did not respect his work. By contrast, Jean-Patrice was a flamboyant, hot-tempered man who lived a comparatively wild life. He was a philanderer, not a family man. However, he was extremely conscientious about risk, and Taleb says that he learned more about the nature of risk in trading from Jean-Patrice than Kenny by a wide margin. He also says that the business world is full of people like Kenny, who eventually are terminated from their leadership positions because of their unwise trading strategies.

Taleb moves on to point out that various historical figures are remembered for their outcomes. He mentions Alexander the Great and Julius Caesar as examples of men who have retained historical significance because of their successful political calculations. However, Taleb mentions that there are many other leaders whose significance has been forgotten by history. He claims that this is an example of randomness and that the famous leaders of history just happened to have things turn out in their favor when those things could have gone the other way.

Taleb then discusses an interview the journalist George Will conducted with Robert Schiller, an economics professor known for his “remarkable insights about the structure of market randomness and volatility” (68). The debate between Will and Schiller was an uneven contest, mainly because Will had the distinct advantage of winnowing down abstract concepts into easily digestible information for a mass audience. Will’s primary impetus was to disprove Schiller’s position that “it is foolish to think that an irrational market cannot become even more irrational” (69). Taleb argues that Will was effectively making and unmaking “prophets based on the roll of a roulette wheel” (69). Taleb claims that when speaking of probability, most results are counter-intuitive and are thus not easily apprehended by a mass audience. The failure to understand the depth of risk and probability is one reason why MBAs have not fared well on Wall Street, in Taleb’s view.

Taleb discusses the findings of psychologists Daniel Kahneman and Amos Tversky that demonstrate that “people do not like to insure against something abstract; the risk that merits their attention is always something vivid” (71). When speaking of risk, it is better to be as specific as possible. Taleb additionally mentions that risk is generally not processed in the thinking part of the brain but is instead processed in emotional ways. He uses the example of “Mad Cow” disease to illustrate how risk can be sensationalized because it is processed irrationally and emotionally. Taleb argues that as a result of media over-sensationalizing news stories, “the mental probabilistic map in one’s mind is so geared toward the sensational that one would realize informational gains by dispensing with the news” (72).

He pivots from this to an examination of a new trend in the business world to hire risk managers. He envies the financial security of the position but says that risk managers are hired to give the appearance that risk is being evenly and accurately assessed, when in fact, it likely is not. Taleb points out that “the existence of a risk manager has less to do with actual risk reduction than it has to do with the impression of risk reduction” (75).

Finally, Taleb closes the chapter by discussing “the central paradox of my career in financial randomness” (75). Since he sees a financial opportunity for himself in people being fooled by randomness, he wishes for this to be so; however, if everyone is fooled by randomness, then he would have nobody to hire him.

Taleb discusses the stereotype of a pure mathematician, in which the person is so engaged in the abstractions of pure mathematics that their general appearance reflects a complete disregard for basic hygiene. Taleb points to Ted Kaczynski as an example of this kind of eccentric mathematician and notes that much of what pure mathematicians discover and concern themselves with is so abstract that it defies simple analysis. Taleb then contrasts this image with what he calls the “Europlayboy,” who is much more erudite, and has a sophisticated, cosmopolitan appearance. This person is likely a gambler and has a knack for using his math skills to win at cards. Taleb fuses these two contrasting images into what he calls “Monte Carlo mathematics’’ (78). He mentions that this kind of math is highly practical and that he became addicted to it, to such an extent that he developed the term “Monte Carlo Generator” (78). Taleb says that “Monte Carlo methods consist of creating artificial history using the following concepts’’ (79). First is what Taleb refers to as “alternative sample paths,” which tend to de-prioritize outcome in favor of analyzing the path that led to the outcome against other possible paths, some of which might be random and some which might be deterministic. He presents various analogies of this concept, including a night at a casino. A person may end up with a certain amount of money at the end of the night, but that amount was likely highly variable if tracked every 15 minutes. Taleb refers to these random events as “stochastic processes” (79) and adds that “this branch of probability concerns itself with the study of the evolution of successive random events—one could call it the mathematics of history” (80).

Taleb explains the difference in pure mathematics, suggesting that mathematicians of this sort are “interested in improving mathematics” (82). Meanwhile, Taleb does not consider himself a mathematician except as this applies to solving a specific problem. For this reason, Taleb is interested in applied rather than pure mathematics. He describes this distinction, saying those like him “have more interest in the employment of the mathematical tool than in the tool itself” (82). Taleb claims that probability is integral to epistemology and that it is “impossible to assess the quality of the knowledge we are gathering without allowing a share of randomness in the manner it is obtained” (82).

Taleb further discusses his affinity for Monte Carlo simulators, which in the computer age can calculate “a million sample paths per minute” (84). He discusses the various ways in which he used these simulators, oftentimes branching into other scientific fields such as evolutionary biology. He claims that the reason he was drawn to Monte Carlo simulators was to foster a better sense of how sample paths could have led to some other outcome, saying, “by dint of playing with a Monte Carlo engine for years I can no longer visualize a realized outcome without reference to the nonrealized ones” (85). Taleb pivots to a discussion of how these simulators changed his perception of history, noting that as a general rule, people have trouble learning from history. He maintains that there are two ways of learning from history: One is from what he calls the “elders’’ and the other is from Monte Carlo simulators.

According to Taleb, part of why people have such difficulty learning from history is that they tend to denigrate the experience of others. As an example, he notes that children will learn not to touch the stove when they are burned, not by simply following the orders of others whose experience tells them that the child will be burned by a hot stove. Furthermore, people can experience failure in their lives and still not learn from it. This is because people tend to have an exaggerated view of their emotional reactions to events in their past. Events are never as good or as bad as we tend to remember them, according to the research that Taleb points to in this chapter. This translates in the world of trading as a propensity to denigrate history and, according to Taleb, predisposes people to emotional blow-ups. Taleb discusses the hindsight bias which gives people the opportunity to rectify the past while in the present, usually through some phrase such as “I knew it all along” (90). Taleb argues that a mistake cannot predicted after the historical fact and that because the world is unpredictable, predicting the past through the hindsight bias does not empower one to predict the future.

Taleb pivots back to his previous discussion of “distilled” information and examines how one might tell the difference between genuine information and noise. Much of what passes for news, in Taleb’s view, is nothing but noise meant to attract attention. He views with skepticism the tendency to assume that new information, simply because it is new, is superior. He advises people that when they are suspicious of new information, they should “systematically reject the new idea, information, or method” (94).

Taleb transitions once again to discuss the work of Robert Shiller, specifically a 1981 paper in which Shiller examined, in mathematical terms, how society handles information. Shiller “pronounced markets to be not as efficient as established by financial theory” (96), which attracted extensive criticism from commentators such as George Will. As much as Taleb criticizes journalism in general, he finally acknowledges that people in his profession depend on journalists.

Taleb examines the financial sector’s tendency to value those traders who have the most measurable profit or those who are young and energetic over veteran traders who have been around a long time and have accumulated enough experience to make informed decisions. The mere fact that they have survived in the industry means that they have proven themselves adept at managing risk both in the short-term and long-term.

Taleb provides a mathematical analysis of how to measure the distinction between information and noise. He also examines the tendency people have to experience bad moments more intensely than good ones and suggests that when people constantly check in on their stocks, they are likely to have a negative outlook over time compared to if they check their stock weekly, monthly, and quarterly. Taleb argues that the more we pay attention to noise, the more it will have negative impacts on our perceptions and even our physical health. Because he sees news as nothing but noise, he chooses to deny himself access to it. Taleb claims that it is preferable to read The New Yorker once a week rather than The Wall Street Journal every day.