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Prospect theory (Kahneman & Tversky, 1979) is the most influential alternative to expected utility theory for modeling decision-making under risk. It introduces three key departures from standard theory: (1) outcomes are evaluated as gains or losses relative to a reference point rather than as final wealth states; (2) the value function is concave for gains (risk aversion) but convex for losses (risk seeking), with losses looming larger than equivalent gains (loss aversion); and (3) people overweight small probabilities and underweight large probabilities (probability weighting function). Prospect theory explains a wide range of anomalies that expected utility theory cannot — including the simultaneous purchase of insurance and lottery tickets, the endowment effect, and the disposition effect in financial markets.
Expected utility theory, the standard framework for decision-making under risk since von Neumann and Morgenstern (1944), treats people as evaluating options based on their final wealth states, with consistent risk attitudes and linear probability assessment. It is elegant and powerful, but it fails to explain a large and systematic set of observed behaviors. Prospect theory was developed to account for these failures — not by tweaking expected utility at the margins but by proposing a fundamentally different model of how people evaluate risky outcomes.
The first key innovation is reference-dependence. Standard theory says that a person evaluating a gamble considers how each possible outcome would affect their total wealth. Prospect theory says people evaluate outcomes relative to a reference point — typically the status quo — and code them as gains or losses from that reference. This seemingly subtle shift has profound consequences because the value function is not symmetric around the reference point. Gains and losses of the same magnitude do not have equal psychological impact.
The value function has three defining features. First, it is concave in the domain of gains: the subjective difference between gaining $0 and $100 is larger than between gaining $900 and $1,000 (diminishing sensitivity to gains). This produces risk aversion for gains — people prefer a certain $100 to a 50/50 chance of $200. Second, it is convex in the domain of losses: the subjective difference between losing $0 and $100 is larger than between losing $900 and $1,000 (diminishing sensitivity to losses). This produces risk seeking for losses — people prefer a 50/50 gamble between losing $200 and losing nothing to a certain loss of $100. Third, the value function is steeper for losses than for gains — loss aversion, estimated at roughly 2:1. Losing $100 feels about twice as bad as gaining $100 feels good. This single feature explains why people reject gambles with positive expected value (like a coin flip for +$110 or -$100), why they hold losing stocks too long, and why they demand much more to sell a good they own than they would pay to acquire it.
The probability weighting function is the second major innovation. Standard theory assumes that people weight outcomes by their objective probabilities. Prospect theory proposes a nonlinear weighting function: small probabilities are overweighted (making both lottery tickets and insurance attractive) and large probabilities are underweighted (reducing the subjective certainty of very likely outcomes). This probability distortion explains why people simultaneously insure against rare catastrophes (overweighting small probabilities of loss) and buy lottery tickets (overweighting small probabilities of gain) — a pattern that expected utility theory cannot reconcile.
Prospect theory's impact extends far beyond the laboratory. In finance, it explains the disposition effect (selling winners too early and holding losers too long), the equity premium puzzle (the surprisingly large premium demanded for holding risky stocks), and loss-averse investor behavior. In labor economics, it explains why taxi drivers work fewer hours on high-wage days (they have a daily income target — a reference point — and quit once they reach it). In public policy, it explains why framing a policy as preventing a loss is more persuasive than framing the same policy as achieving a gain. The theory earned Kahneman the 2002 Nobel Prize in Economics — the first psychologist to receive the economics prize — and remains the cornerstone of behavioral economics.