Behavioral Finance & Prospect Theory

In the previous article about Randomness, Efficiency, we learned that markets frequently experience extreme events, known as fat tails, in contrast to the normal distribution assumed by the Efficient Market Hypothesis.

These are the moments when prices move within the realm of Extremistan, forming trends that are easily recognizable. In general, price movements in this zone are less random and tend to exhibit significantly larger swings than during normal market conditions. This is precisely the foundation upon which we can build an edge in trading. So, where do these fat tails come from?

In reality, trying to determine the exact cause of these fat tails is not important. As traders—not theoretical researchers—what matters to us is the outcome. However, if we want a solid foundation to build upon, we need a theory that supports the empirical data. If statistical data points us to a conclusion that isn’t backed by any theoretical framework, then no matter how much data we use, there’s a high chance that the result is merely a random occurrence. A statistical outcome that aligns with theory is less likely to be random. When a statistical result is supported by theory, it ceases to be an isolated fact—it becomes part of a larger, coherent picture, where theory explains reality and reality confirms theory.

Traditional economists following the Efficient Market Hypothesis assumed that humans behave rationally, and markets move randomly as a result of their actions. In their pursuit to maximize utility and increase wealth, rational agents would quickly buy undervalued assets—pushing prices up—and sell overvalued ones—pushing prices down—thereby eliminating profit opportunities rapidly. Each person may act based on different motivations, but since everyone is rational and intelligent, profits and losses would be evenly distributed over time. One person might win while another loses, and vice versa, but no group would consistently outperform others. This is the fundamental flaw that prevents the theory from accounting for the existence of fat tails.

Today, behavioral finance has emerged as a theory capable of explaining many of the shortcomings of traditional economics. In modern behavioral finance research, we are all biased, emotional, and often make decisions that deviate from the rational standards assumed by traditional economists. More importantly, this irrationality often creates feedback loops with exponentially growing consequences. These loops generate massive trends in the market, where prices are driven far away from their intrinsic values. In reality, markets don’t react directly to new information—they respond after the information has passed through the emotional and biased lens of human perception. People make deeply emotional decisions in response to market events; information gets ignored, overemphasized, or exaggerated during analysis. Human memory, biases, conservatism, and emotional states—such as hope, fear, and pain from price fluctuations—all strongly influence behavior.

In the ideal world of random walks, prices are unaffected by past prices or information. But in the real world, prices are determined by traders making buy or sell decisions at specific moments. Traders often believe they are smarter than others, and as a result, they rarely admit when they are wrong. This stubbornness stems from a cognitive bias known as “confirmation bias.” When holding a position based on prior decisions, traders tend to give more weight to new information that confirms their view and overreact to it. Conversely, when new information contradicts their previous decision, they tend to ignore it, treat it with skepticism, and underreact. This leads to increasingly extreme confidence in their decisions over time, regardless of their validity. They may even double down on their positions—buying or selling more—thus amplifying the existing price trend. It is this human bias, emotionality, and irrationality that gives rise to fat tails.

When prices are in the realm of Mediocristan, they fluctuate mildly and behave in a normal, predictable manner. People remain calm and rational, and traders’ account balances experience little change. Different motivations lead to diverse buying and selling decisions, making price movements appear truly random. But when prices begin to rise, those who bought earlier become more confident in their decisions—they buy more aggressively, believing they are smart and spreading this belief to others. Positive news begins to flood in, and more investors start thinking that prices will continue to rise. Slowly, they lose their rationality. At such moments, their motivations become aligned—they all become greedy, fearful, biased, and emotional in the same way, creating a positive feedback loop that drives prices sharply higher into the realm of Extremistan. This is when the fat tails emerge. And once the price has gone too far, it eventually collapses in a loop that mirrors the path it took on the way up.

Another implication of the Efficient Market Hypothesis is that smart investors cannot consistently earn higher returns than less skilled investors, because the market is assumed to move randomly. However, in reality, there is a group of individuals who consistently generate profits in the market. They have built and refined systems and methods designed to trigger fat tails (major trends), allowing them to profit from emotionally driven investors.

We can observe this phenomenon quite frequently in the crypto market, where countless projects are built in a typical “pump and dump” fashion. Developers and market makers create hype, news, and trading algorithms to push prices into an upward trend—what can be called a bait trend—after having accumulated a large number of tokens beforehand. Once the price reaches a certain threshold, emotionally-driven investors begin to spread the word and rush in to buy, driving prices to extreme levels and triggering massive pumps.

Right at that moment, those market makers begin to sell. They cleverly exploit the greed, fear, and irrationality of others to make money. They repeat this exact behavior over and over—month after month, year after year.

Money on the market keeps flowing from the pockets of emotional traders into the hands of those who are rational and intelligent. Although this kind of manipulation can typically only occur in low-cap markets where supply is largely controlled by a few individuals, it clearly demonstrates how flawed the assumptions of the efficient market hypothesis truly are.

The graph above is a value function that accurately reflects human nature. Our emotions are much more strongly affected by losses than by gains—the pain we feel from losing $50 is far greater than the joy of gaining the same amount.

The right side of the curve, representing the domain of gains, shows how our sensitivity to profit diminishes as the profit increases. We perceive the difference between earning $10 and $20 more strongly than between earning $1,010 and $1,020.

In contrast, on the left side of the curve—the loss domain—our sensitivity decreases as the losses grow larger. If we observe the chart carefully, it reveals a deeper insight: humans are generally risk-averse when seeking gains, but they become far more willing to take risks in order to avoid losses.

Humans have a much stronger fear of losing money they already possess compared to losing money they haven’t yet acquired. This is because the pain of loss is far greater than the pleasure of gain. Results from Prospect Theory experiments show that most people are unable to hold onto winning trades—they tend to close them too early to secure a small profit. On the other hand, they do the opposite with losing trades: unwilling to admit they were wrong, they refuse to take a small loss and instead hold on, hoping the trade will return to breakeven. As a result, the loss often grows excessively.

These individuals act primarily on emotion rather than expected value. They view reality through a distorted lens shaped by personal feelings. Those who let emotions drive their actions clearly fail to take advantage of the positive outcomes associated with fat tails in the market. They lose money consistently and ultimately become a steady source of profit for more rational and intelligent participants.

Therefore, if we want to be among the winners, we must act against our natural instincts—learn to admit when we’re wrong and avoid holding onto losing positions for too long. We need to build trading strategies where losses are strictly controlled with tight stop-loss orders, while profits are left open and allowed to run as far as possible.

We must wait for a trend to form and enter early in its development. These small trends can evolve into much larger ones. When prices begin to move sharply and enter the Extremistan zone, our results will be heavily influenced by extreme values. Since we’ve already cut off the negative outcomes, we’ll be positioned to capture the positive ones. That is the foundation for making a profit.