Prospect theory is a theory of behavioral economics, judgment and decision making that was developed by Daniel Kahneman and Amos Tversky in 1979. The theory was cited in the decision to award Kahneman the 2002 Nobel Memorial Prize in Economics. Based on results from controlled studies, it describes how individuals assess their loss and gain perspectives in an asymmetric manner (see loss aversion). For example, for some individuals, the pain from losing $1,000 could only be compensated by the pleasure of earning $2,000. Thus, contrary to the expected utility theory (which models the decision that perfectly rational agents would make), prospect theory aims to describe the actual behavior of people. In the original formulation of the theory, the term prospect referred to the predictable results of a lottery. However, prospect theory can also be applied to the prediction of other forms of behaviors and decisions. Prospect theory challenges the expected utility theory developed by John von Neumann and Oskar Morgenstern in 1944 and constitutes one of the first economic theories built using experimental methods.
History In the draft received by the economist Richard Thaler in 1976, the term "Value Theory" was used instead of Prospect Theory. Later on, Kahneman and Tversky changed the title to Prospect Theory to avoid possible confusions. According to Kahneman, the new title was 'meaningless.'
Overview
Prospect theory stems from loss aversion, the observation that agents asymmetrically feel losses more acutely than equivalent gains. It centers on the idea that people evaluate the utility of gains and losses relative to a certain "neutral" reference point regarding their current individual situation. Thus, rather than rationally maximizing a fixed expected utility, value decisions are made relative to the current neutral situation and not following any absolute measure of utility. Consider two choice scenarios:
a 100% chance of gaining $450 or a 50% chance of gaining $1000 a 100% chance of losing $500 or a 50% chance of losing $1100 It is assumed that the agent's individual utility is proportional to the dollar amount (e.g. $1000 would be twice as useful as $500). Prospect theory suggests that:
When faced with a risky choice leading to gains, agents are risk averse, preferring a certain outcome with a lower expected utility (i.e., the value function is concave). In the example, agents will choose the certain $450 even though the expected utility of the risky gain is higher. When faced with a risky choice leading to losses, agents are risk seeking, preferring the outcome that has a lower expected utility but the potential to avoid losses (i.e., the value function is convex). Agents will choose the 50% chance of losing $1100 even though the expected utility is lower, due to the chance that they lose nothing at all. These two examples are thus in contradiction with the theory of expected utility, which leads only to choices which maximize utility. Also, the concavity of gains and the convexity of losses implies diminishing marginal utility with increasing gains or losses. In other words, someone who has more money has a lower desire for a fixed amount of gain (and lower aversion to a fixed amount of loss) than someone who has less money. The theory continues with a second concept, based on the observation that people attribute excessive weight to events with low probability and insufficient weight to events with high probability. For example, individuals may unconsciously treat an outcome with a probability of 99% as if its probability were 95%, and an outcome with probability of 1% as if it had a probability of 5%. Under- and over-weighting of probabilities is importantly distinct from under- and over-estimating probabilities, a different type of cognitive bias which is observed for example in the overconfidence effect.
Model The theory describes the decision processes in two stages:
During an initial phase termed editing, outcomes of a decision are ordered according to a certain heuristic. In particular, people decide which outcomes they consider equivalent, set a reference point and then consider lesser outcomes as losses and greater ones as gains. The editing phase aims to alleviate any framing effects. It also aims to resolve isolation effects stemming from individuals' propensity to often isolate consecutive probabilities instead of treating them together. The editing process can be viewed as composed of coding, combination, segregation, cancellation, simplification and detection of dominance. In the subsequent evaluation phase, people behave as if they would compute a value (utility), based on the potential outcomes and their respective probabilities, and then choose the alternative having a higher utility. The formula that Kahneman and Tversky assume for the evaluation phase is (in its simplest form) given by:
V = ∑ i = 1 n π ( p i ) v ( x i ) {\displaystyle V=\sum _{i=1}^{n}\pi (p_{i})v(x_{i})}
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