Prospect Theory and the Failure of Invariance

The book dives into the study of human psychology and the interplay between risk and reward. Life doesn't follow the rules of a game, like "balla" or dice, and predictable outcomes don't necessarily guide rational human decision-making. Instead, humans weigh decisions based on the balance between risk and reward. Credit for the following analysis and interpretations goes to Kenneth Arrow, Daniel Kahneman, Amos Tversky, Harry Markowitz, William Sharpe, John von Nuemann, Oskar Morgenstern, Peter Bernstein, Francis Galton, and others. Apologies for any oversimplified or myopic statements.

Game Theory offers a rational framework for understanding decision-making among humans. For instance, it was developed during the Cold War to consider adversaries' perspectives and their potential gains or losses. This theory relies on a set of variables and outcomes determined by human actions. This is the when the book challenges conventional theories.

Kahneman and Tversky conducted experiments to explore how positive and negative reinforcement affect the training of combat pilots. They found that pilots who were positively reinforced for their recent landings tended to perform worse on their next flight, while those who were negatively reinforced improved. This phenomenon is known as reversion to the mean. Galton's pea experiments illustrate a similar concept: extreme pea sizes tend to produce offspring closer to the average size (larger peas=smaller offspring; smaller peas=larger offspring). This is nature's way of operating. It's worth mentioning that Galton was a pioneer of eugenics, while Kahneman and Tversky served as IDF officers. However, the latter built upon the former's groundbreaking pea experiments and theories, finding common ground in their work.

The groundbreaking findings of Kahneman and Tversky led to profound insights into human psychology and eventually to Prospect Theory. They proposed that an individual's reference point is more influential than the potential for gain or loss.

In one experiment, participants were presented with a scenario involving two programs to combat a disease outbreak. The majority chose the risk-averse option of saving 200 people for certain over a gamble with uncertain outcomes.

The experiment: “Imagine that a rare disease is breaking out in some community and is expected to kill 600 people. Two different programs are available to deal with the threat. If Program A Is adopted, 200 people will be saved; if Program B is adopted, there is a 33% probability that everyone will be saved and a 67% probability that no one will be saved.” The risk averse and “rational” crowd might choose to save 200 people for certain rather than take the gamble with Program B.

72% of the subjects chose the risk-averse “life-saving” certainty of Program A over Program B.

Khaneman and Tversky then ask about the same problem in a different way: “If Program C is adopted, 400 of the 600 people will die, while Program D entails a 33% chance that no one will die and a 67% probability that 600 people will die. Note that the first of the two choices [are] now expressed in terms of 400 deaths rather than 200 survivors, while the second program offers a 33% chance that no one will die.”

The results are shocking: 78% of respondents chose the risk-seeking gamble and would not accept “the sure loss of 400” people.

When the same scenario was framed differently, with the emphasis on potential deaths rather than lives saved, the majority opted for the riskier option. This experiment challenges the notion of rational behavior and highlights the inadequacy of static references in predicting human behavior.

Tversky later remarked, "It's not uncertainty that people hate, but rather, losing."

This leads to the concept of the "Failure of Invariance," which suggests that rational people should maintain consistent preferences across different scenarios. However, research shows that preferences can vary depending on how choices are presented. Or the respondents reference point.

These examples underscore the importance of framing questions and how humans assess risk and probability. The exploration of human decision-making psychology has profound implications for capital markets, influencing them more than we might realize or acknowledge.

The sayings "You never get poor if you take a profit" and "Always cut your losses" seem rational, but they're often driven more by emotion than participants in the market are willing to admit. It ultimately boils down to greed, the desire for greater profit, and the fear of admitting failure and loss of ego.