It’s October 1987, and the US stock market has crashed. In New York City, the mood is grim. Fortunes accumulated over years have evaporated. Dazed expressions everywhere. Some weep openly.
A man in a suit wanders the streets, lost in thought. His name is Nassim Taleb and the strong emotion he feels isn’t sadness. It’s excitement. Taleb had been developing a trading strategy based around rare events. What came to be known as “Black Monday” proved his theories right – and made him rich.
If you interact with markets you must understand Taleb’s perspective. It may save you a fortune in investment mistakes.
Taleb’s first book, “Fooled By Randomness” was written at the dawn of the new millennium, which coincided with the peak of the “dot-com” bubble. It describes his philosophy further articulated in “The Black Swan”, “Antifragile”, and “Skin in the Game”.
If you only read one of Taleb books, read Fooled by Randomness.
Short on time? I scoured the book for some takeaways that will make you a better investor 👇👇👇
WE AREn’t as RATIONAL as we think
“We are still very close to our ancestors who roamed the savannah. The formation of our beliefs is fraught with superstitions” (p.26)
Taleb argues that despite our technological advancements, our decision-making processes remain fundamentally emotional. He writes, “One cannot make a decision without emotion. … Psychologists call [emotions] ‘lubricants of reason.’” (241)
He describes scientific studies of brain-damaged people with no emotional capacity. They are unable to make the smallest decisions, falling prey to “analysis paralysis”. We need shortcuts to function in the world; emotions provide this.
This insight challenges the common belief that investors make purely rational choices in modern financial markets. Throughout the book, Taleb emphasizes how rationality takes a backseat to emotion in the human mind.
“Rational thinking has little, very little, to do with risk avoidance. Much of what rational thinking seems to do is rationalize one’s actions by fitting some logic to them.” (71)
We take large risks when enticed by greed and run from profitable investments when scared. Then we justify our decisions after the fact. Whether it’s tech stocks at sky high valuations, cryptocurrencies, or JPG files of apes, we can find a reason. Emotional decision-making in the moment, then rationalizing afterward is how we fool ourselves.
the nature of risk
Taleb challenges our understanding of risk in financial markets. He argues that “over a short time increment, one observes the variability of the portfolio, not the returns.” (102) This insight leads to a crucial observation: “The closer he observes his performance, the more pain he will experience owing to the greater variability at a higher resolution.” (148)
Consider a hypothetical investment with a 15% average annual return and 10% volatility. This strategy would be profitable in:
- 93% of annual periods
- 67% of monthly periods
- 50.02% of one-second periods
Over time, the strategy is likely to be profitable. But the more frequent you check performance, the more likely you are to be disappointed.
Real-world market behavior poses a greater challenge for investors. The S&P 500 Total Return index, over the past century, has averaged 10% annual returns with 20% volatility.
Taleb warns against relying too heavily on past experiences to predict future outcomes. He reminds us that “history teaches us that things that never happened before do happen” (146) and that “rare events exist precisely because they are unexpected.” (147) This perspective challenges the notion that we can fully anticipate or model market risks.
The danger of overconfidence in risk modeling is exemplified by the 1998 Long-Term Capital Management (LTCM) crisis. LTCM was a hedge fund founded by Nobel Prize-winners. They used complex statistical models to exploit price differences between securities. Arrogance in their models led them to “lever up”, using borrowed money to increase their investments. Markets moved against them and the firm had to be bailed out. Had LTCM been allowed to fail, the extent of their leverage and being unable to repay the loans would have caused a cascading effect likely leading to a financial crisis.
Taleb observes, “Somehow [LTCM] thought they could scientifically ‘measure’ their risks. They made absolutely no allowance in the LTCM episode for the possibility of their not understanding markets and their methods being wrong.” (281)
It is not possible to perfectly model reality using statistics. Theories like Efficient Market Hypothesis, while helpful, may create a false sense of security. Such theories fail to explain bubbles, crashes, and other recurring market episodes.
luck vs. skill
“Nobody accepts randomness in his own success, only his failure.” p.192
The higher the degree of randomness in an occupation, the larger role luck has in the outcomes. Investing involves a lot of randomness (especially in the short-term). Therefore, it’s essential to remain humble, acknowledging that there’s much we don’t know.
We often fall into the trap of Monday-morning quarterbacking, criticizing decisions only after knowing the results. Judging decisions by their outcomes is flawed. Taleb points out that “a mistake is not something to be determined after the fact, but in the light of the information until that point.” (91)
Some investments, for example, need time to show their true value. Just because an investment loses money in the short term doesn’t mean the decision to invest was wrong.
If you have one billion monkeys on typewriters, one might randomly produce Shakespeare. That doesn’t mean we should follow that monkey’s stock tips. The same caution applies to so-called market gurus who “predicted the last market crash.” Taleb suggests, “rhetoric can be constructed randomly, but not genuine scientific knowledge.” (107)
The financial world often glorifies those who are merely lucky. “At any point in time, the richest traders are often the worst traders…the most successful traders are likely to be those that are best fit to the latest cycle” (121). We’re drawn to dramatic success stories highlighted by the financial media. Today’s obsession is NVIDIA and AI stocks; 10 years ago it was marijuana stocks; in 2000 it was telecoms and “dot-coms”.
Chasing the latest market darling is risky. Often, the best-performing investments are more a product of luck than skill. For example, who could have predicted in the mid-2010s that Tesla, despite its struggles at the time, would later be added to the S&P 500, causing its share price to soar?
There is always a flavor of the month. Don’t chase it.
adverse selection
“There is a high probability of the investment coming to you if its success is caused entirely by randomness.” 194
Unhealthy people want to buy health insurance. Investment managers who got lucky want you to believe they’re skilled.
The harder the sales pitch, the more likely they’re mediocre.
Non-linear risks (and returns)
Today’s world, Taleb notes, offers the chance for ideas to catch fire. “It is better to have a handful of enthusiastic advocates than hordes of people who appreciate your work.” (217) Raving fans keep ideas, writers, artists etc. going long enough to hone their craft and hit it big.
A musician in rural Virginia posts a song online that goes viral. He has over 3 million listeners on Spotify.
“The information age”, Taleb says, “by homogenizing our tastes, is causing the unfairness to be even more acute – those who win capture almost all the customers.” (212)
Whether Zoom for meetings, Google for search, or Apple for cell phones, popular technology has “winter-take-all” attributes. Large tech companies reinforce their advantage by improving functionality repeatedly after studying troves of data from more user interactions.
Be aware of asymmetric “tipping points” where upside and downside don’t match. “The important fact is knowing the existence of these nonlinearities, not trying to model them.” (215)
Traders selling volatility made steady income for years. They got wiped out in two market sessions in early August 2024.
Don’t try to model or predict these watershed moments, Taleb advises. Instead, avoid picking up pennies in front of the train, and build your life (and portfolio) in a way that can BENEFIT from them.
