Prospect Theory
Prospect Theory was developed by daniel-kahneman and amos-tversky (1979) as a descriptive replacement for Expected Utility Theory (EUT). Where EUT describes how a rational agent should choose under uncertainty, prospect theory describes how humans actually choose — capturing systematic deviations from rationality with mathematical precision.
Primary source: kahneman-2011-thinking-fast-and-slow
Why Expected Utility Theory Failed
EUT predicts that people evaluate outcomes as absolute levels of wealth and weigh them by their objective probabilities. Kahneman and Tversky showed through dozens of experiments that this is false:
- People are risk-averse for gains but risk-seeking for losses of the same magnitude.
- The same objective outcome produces opposite preferences depending on how it is framed.
- Small probabilities are treated as if they were larger; high probabilities are discounted.
Four Core Principles
1. Reference Dependence
Outcomes are not evaluated in absolute terms but as gains or losses relative to a reference point (usually the status quo, but also expectations, aspirations, or any salient anchor). A salary of 50,000 and a loss to someone who expected $70,000 — even though the objective amount is identical.
2. Loss Aversion
loss-aversion is the most powerful principle: losses loom roughly 2× larger than equivalent gains. Losing 200 feels good. This asymmetry:
- Makes people irrationally risk-averse when potential losses are visible
- Makes people irrationally risk-seeking when facing a certain loss (gamble to break even)
- Explains the endowment effect (reluctance to sell owned objects at market price)
- Explains the status quo bias (inaction preferred over action when both have uncertain outcomes)
3. Diminishing Sensitivity
The value function is concave for gains (each extra dollar of gain matters less than the previous) and convex for losses (each extra dollar of loss matters less in magnitude). Moving from 100 feels larger than moving from 1000; losing 0 hurts more than losing 900.
The shape: an S-curve bending steeply near the reference point and flattening in both directions.
4. Probability Weighting
People do not use objective probabilities; they use a weighting function that:
- Overweights small probabilities (5% feels like 10–15%) — drives lottery ticket purchases, fear of rare catastrophes
- Underweights large probabilities (95% feels like 85%) — drives insurance purchases even for near-certainties
- Treats 0% and 100% as categorical rather than quantitative (the possibility effect and the certainty effect)
The Fourfold Pattern of Risk Preferences
These four principles combine to produce a characteristic pattern:
| High-probability outcome | Low-probability outcome | |
|---|---|---|
| Gain | Risk-averse (certainty preferred; “bird in hand”) | Risk-seeking (overweight small chance of big gain → lottery) |
| Loss | Risk-seeking (gamble to avoid certain loss; “doubling down”) | Risk-averse (overweight small chance of catastrophe → insurance) |
Framing Effects
Because outcomes are evaluated relative to reference points, how a choice is framed determines which mental account is activated:
- “90% survival rate” vs. “10% mortality rate” for a surgery — logically identical, but patients choose more often with the survival frame.
- “This beef is 95% fat-free” vs. “5% fat” — same information, different evaluations.
- Policy choices framed as “200 lives saved” vs. “400 lives lost” from the same program produce opposite majorities.
The framing-effect demonstrates that preferences are constructed by context, not merely revealed by choices.
Implications
| Domain | Implication |
|---|---|
| Finance | Investors hold losing stocks too long (loss aversion) and sell winners too early (lock in gains) — the disposition effect |
| Negotiation | Framing proposals as preventing losses rather than achieving gains increases compliance |
| Marketing | ”Save 100 discount” |
| Policy | Opt-out defaults exploit loss aversion (changing defaults increases pension enrollment dramatically) |
| Medicine | Treatment framing (survival vs. mortality) affects patient choices and physician recommendations |
Relationship to cognitive-biases
Prospect theory provides the formal mathematical foundation for several biases described in the heuristics-and-biases programme. It is the theoretical core of Kahneman’s Part IV (Choices) in Thinking, Fast and Slow.
Related Concepts
- loss-aversion — the 2:1 asymmetry between gains and losses
- framing-effect — different frames of the same fact produce different choices
- cognitive-biases — hub page for all systematic errors in judgement
- system-1-system-2 — the dual-process architecture generating these effects