When making financial decisions or decisions about other attributes, such as quality of life, do people perform precise calculations that maximize the utility of each of their choices?

Starting from this question, researchers Daniel Kahneman and Amos Tversky developed the well-known Prospect Theory to assess with greater precision how people make decisions in contexts of uncertainty or risk.

The basis of their studies challenged the utility theory, which had been accepted until then, but which, according to Kahneman and Tversky, left a series of gaps in the understanding of individual decision-making under risk or uncertainty.

In one experiment, for example, they asked people if they preferred a 50% chance of winning 1000 or 450 for sure. From the point of view of utility theory, option 1 would offer a higher expected result (500). But would this be the most chosen option among people? What would be the expected behavior, and how could this be seen as an evolution of utility theory?

One of the points raised in Prospect Theory is that, in general, people give more weight to “guaranteed” outcomes than to probable outcomes, a phenomenon called by researchers the “Certainty Effect.”

Through a series of studies conducted with “option A vs. option B” type questions, it was demonstrated that participants systematically violated utility theory by choosing outcomes whose certainty was guaranteed, even if the expected utility was lower. These exercises involved questions about both money and other attributes, such as the chance of winning a trip.

Another interesting learning is that when the chance of winning is more probable, people opt for what is closest to 100%, even if the expected utility is lower. However, when the chance of winning is possible but not probable—for example, 1% or 2%—people tend to choose the option with the higher expected gain, even if it is less probable. From then on, Prospect Theory began to also evaluate preferences involving real chances of loss, since, until then, evaluations were only made between possibilities of gain.

Some learnings show that, while we have greater risk aversion in positive preferences, we reduce this aversion when faced with real possibilities of loss. This “dilemma” was called Risk Aversion vs. Risk Seeking. These are contradictory behaviors that occur according to the probabilities faced in decision-making.

This example materializes in what the authors call the Reflection Effect. This effect implies that, when we invert the charge/symbol of an example whose preferences are positive, people invert their choice. In one example, 80% of people preferred the certainty of winning 3000 to an 80% chance of winning 4000. However, applying the Reflection Effect, the overwhelming majority of people preferred an 80% chance of losing 4000 to the certainty of losing 3000. This proves that, in guaranteed loss scenarios, the tendency is for people to make even more irrational bets with a greater utilitarian possibility of loss.

In other words: in the field of positive preferences, people prefer a smaller guaranteed gain compared to a larger uncertain gain; in the field of negative preferences, they prefer to take the risk of losing a probable amount versus a smaller, but guaranteed, amount. Both behaviors are governed by the psychological principle that we give greater weight to certainty.

Another point evaluated by Prospect Theory was reverse preferences, which show that the decision is not only related to the probabilities of losses and gains, but also to other events that may influence the outcome in question. In other words, when looking at an expected outcome, if there is something before or after that somehow influences that outcome, people tend to consider that context when making a decision. This means that preferences can be altered according to how probabilities are presented.

One of the factors that influences this is what Prospect Theory defines as a reference point, or neutral point. Imagine, for example, that a grandfather gave 1000 reais to each of his two grandchildren when they turned 15. However, when the third grandchild turned 15, he received only 500. For this third grandchild, more than a reduced gain compared to his siblings, the experience is interpreted as a loss, since the reference point was the 1000 received by the others. The authors argue that the reference point can be altered by the way a person encodes and edits the problem, and this can lead to different decision-making.

Another insight from Prospect Theory is that people underestimate the weight of small probabilities and overestimate the weight of larger probabilities. To illustrate, the researchers present the following example: in a game of Russian roulette, how much would you pay to reduce the number of bullets from 4 to 3? Now, if the option was to reduce it from 1 to 0, would you pay more or less? In both cases, the reduction is only one bullet. However, in the second option, any degree of uncertainty is eliminated, and this is reason enough for people to be willing to pay much more, according to the research. From an economic point of view, however, since the chance of survival in the first case is much lower, the amount invested should be greater in that situation.

In summary, Prospect Theory has shown that there are several variables that impact decision-making under risk or uncertainty, such as the weight we give to certainty, the errors we make when comparing low- or high-probability situations, and the fact that we perceive results from an initial state of gains or losses—which can also vary depending on how we interpret each situation.