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Prospect Theory replaces expected utility with a value function exhibiting loss aversion (losses loom larger than gains) and reference dependence (utility depends on changes from a reference point). Probability weighting overweights small probabilities and underweights large ones. These features explain empirical regularities: reflection effect (risk-seeking for losses, risk-averse for gains), endowment effect (owning increases perceived value), and framing effects (choices depend on how outcomes are framed).
Standard expected utility theory, which you encountered through expected return and variance analysis, assumes that people evaluate outcomes based on final wealth levels and weight probabilities linearly. Prospect theory, developed by Kahneman and Tversky, starts from the observation that real human choices systematically violate these assumptions. People do not evaluate outcomes in terms of final wealth — they evaluate them as gains or losses relative to a reference point, typically the status quo. This single shift in framing transforms the entire theory of choice under uncertainty.
The value function in prospect theory has three distinctive features. First, it is defined over changes from the reference point, not absolute levels — losing $100 when you have $10,000 feels the same as losing $100 when you have $1,000,000. Second, it is concave for gains (diminishing sensitivity — the difference between gaining $100 and $200 feels larger than between $1,100 and $1,200) and convex for losses (the difference between losing $100 and $200 feels larger than between losing $1,100 and $1,200). Third, and most importantly, it is steeper for losses than for gains — this is loss aversion, typically estimated at about 2:1, meaning a loss of $100 feels roughly as bad as a gain of $200 feels good. The value function is therefore kinked at the reference point, creating an asymmetry that standard utility theory cannot capture.
The second major departure is probability weighting. Instead of multiplying values by objective probabilities, prospect theory applies a nonlinear weighting function π(p) that overweights small probabilities and underweights large ones. This explains why people simultaneously buy lottery tickets (overweighting the small probability of a large gain) and purchase insurance against rare disasters (overweighting the small probability of a large loss). The weighting function also exhibits a certainty effect: people strongly prefer outcomes that are certain over outcomes that are merely probable, even when the expected values are similar.
These features jointly explain a cluster of empirical puzzles. The reflection effect — people are risk-averse over gains but risk-seeking over losses — follows from the shape of the value function: its concavity in gains makes a sure gain attractive, while its convexity in losses makes a sure loss feel particularly painful, driving people to gamble for a chance of avoiding the loss entirely. The endowment effect — people demand more to give up an object than they would pay to acquire it — follows from loss aversion: giving up something you own is coded as a loss, which looms larger than the equivalent gain. Framing effects arise because the reference point determines whether an outcome is perceived as a gain or a loss, and different framings of the same objective outcome can shift the reference point, producing different choices. Prospect theory does not reject the idea that people respond to incentives — it refines our understanding of what the subjective incentives actually look like.