Philosophy

Prospect Theory

Remnant Network

31 Jan 2026 — 6 min read

Introduction

Prospect theory is a theory within behavioural economics, judgement, and decision-making, developed in 1979. It is widely regarded as the foundation of modern behavioural economics and was a key reason for awarding the Nobel Memorial Prize in Economics. This theory describes how individuals evaluate potential losses and gains, noting that this evaluation is often asymmetric, with the pain of a loss being felt more intensely than the pleasure of an equivalent gain. Prospect theory aims to describe the actual behaviour of people when faced with risk, in contrast to expected utility theory, which models how perfectly rational agents should behave. Initially referred to as "Value Theory," the name was changed to "Prospect Theory" to avoid confusion.

Overview

Prospect theory is centred on the observation of loss aversion, where individuals feel the impact of losses more strongly than that of comparable gains. A core idea is that people derive their utility from gains and losses relative to a certain "neutral" reference point related to their current situation. Therefore, decisions are made based on the potential changes from this reference point, rather than on an absolute measure of utility. The theory suggests that people's attitudes towards gains and losses are fundamentally different. People hate losing much more than they like winning. The ratio by which people dislike losing more than they like winning is, on average, between two and three. For instance, individuals might require a potential gain of $25 to compensate for a potential loss of $10, demonstrating that the emotional impact of a loss outweighs the emotional impact of a gain of the same magnitude. This suggests that the emotional aspect often has a significant influence on decision-making.

Prospect theory challenges the expected utility theory, which assumes that individuals make decisions to maximise their expected utility and are indifferent to a reference point. Prospect theory, however, posits that the way individuals subjectively frame an outcome or transaction significantly affects the value they expect or receive.

Model

Prospect theory describes decision processes in two main stages: editing and evaluation.

Editing

In the initial editing phase, individuals organise and reframe the potential outcomes of a decision using various heuristics. This involves:

Coding: Defining outcomes as either gains or losses relative to a reference point.
Combination: Integrating probabilities associated with identical outcomes.
Segregation: Separating the riskless component from the risky component of a prospect.
Cancellation: Discarding common components between different prospects.
Simplification: Rounding probabilities or outcomes.
Detection of Dominance: Eliminating options that are clearly inferior to others. The editing phase aims to simplify the decision problem and alleviate framing effects.

Evaluation

In the subsequent evaluation phase, individuals assess the edited prospects and choose the one with the highest subjective value. This valuation is based on a function that considers both the potential outcomes and their respective probabilities. The formula for this evaluation phase can be represented as:

V = ∑ π(pᵢ)v(xᵢ)

Where:

V is the overall value of the prospect.
xᵢ are the potential outcomes.
pᵢ are the probabilities of those outcomes.
v is the value function that assigns a subjective value to each outcome.
π is the probability weighting function that reflects how individuals perceive and weigh probabilities.

The value function v(x) is typically s-shaped and asymmetrical around the reference point. It is concave for gains, indicating diminishing marginal sensitivity to increasing gains, and commonly convex for losses, indicating diminishing marginal sensitivity to increasing losses. Crucially, the value function is steeper for losses than for gains, reflecting loss aversion.

The probability weighting function π(p) deviates from objective probabilities. People tend to overweight small probability events and underweight medium to high probability events. This means that a small chance of a large gain or loss can have a disproportionately large impact on perceived value, while the difference between high probabilities and certainty might be underestimated. For example, the difference between a 99% chance and a 100% chance is often felt more strongly than the difference between a 40% chance and a 41% chance.

Example

Consider two scenarios:

A choice between a 100% chance to gain $450 or a 50% chance to gain $1000.
A choice between a 100% chance to lose $500 or a 50% chance to lose $1100.

Expected utility theory, assuming utility is proportional to the dollar amount, would suggest choosing the option with the higher expected value in both cases. However, prospect theory predicts that:

When faced with potential gains, individuals tend to be risk averse, often preferring the certain gain of $450 even though the expected value of the risky option ($500) is higher. This reflects the concave value function for gains and the certainty effect, where people overweigh certain outcomes.
When faced with potential losses, individuals tend to be risk seeking, often preferring the 50% chance to lose $1100 over the certain loss of $500, hoping to avoid any loss at all. This reflects the convex value function for losses and the hope of avoiding the negative outcome.

This pattern of risk aversion in the domain of gains and risk-seeking in the domain of losses is known as the reflection effect.

Myopic Loss Aversion (MLA)

Myopic loss aversion is a concept derived from prospect theory that describes the tendency for individuals to focus on short-term losses and gains and weigh them more heavily than long-term outcomes. This can lead to seemingly irrational decision-making, where people prioritise avoiding immediate losses over achieving greater long-term gains. Studies have shown that individuals may be more likely to take risks after a short-term loss to try and recover, and more risk-averse after a short-term gain. This bias can also influence investment decisions, leading to overreactions to short-term market fluctuations and a reluctance to invest in potentially higher-reward but riskier assets.

Applications

Prospect theory has been widely applied across various disciplines:

Economics: Explaining phenomena like the disposition effect (the tendency to sell winning investments too early and hold onto losing ones too long) and the equity premium puzzle (the historically higher returns of stocks over bonds). It is also fundamental to the development of behavioural economics and is used extensively in mental accounting, which describes how people categorise and evaluate financial outcomes. The framing of economic outcomes significantly impacts perceived utility.
Software: Applied in designing software interfaces and user experiences by considering how users perceive gains and losses in digital interactions.
Politics: Used to understand political decision-making, such as how politicians frame policies to gain public support (e.g., focusing on employment rates rather than unemployment rates) and why governments might avoid risky reforms due to the potential for negative reactions. It can also explain why politically weakened leaders might undertake riskier policy initiatives.
International Relations: Explaining why policymakers might take greater risks during wartime when in a perceived domain of loss. It has been used to analyse various foreign policy decisions and international agreements.
Insurance: Helping to understand consumer choices regarding premiums and deductibles, where the overweighting of small probabilities of claims can lead to the preference for lower deductibles despite higher overall costs.

Limits and Extensions

While influential, prospect theory has limitations:

The reference point can be difficult to define precisely and is influenced by various contextual factors and expectations.
The original formulation faced issues with stochastic dominance, which later versions like cumulative prospect theory addressed by using a rank-dependent probability weighting function, allowing for a wider range of outcomes.
Critics from psychology argue that prospect theory primarily describes behaviour without providing deep psychological explanations for the underlying processes. Factors like emotion, beyond the basic responses to gains and losses, are not fully incorporated.
Alternative models, such as the priority heuristic, have been proposed as simpler decision strategies that can also explain many observed choices.
Some research suggests that the effects predicted by prospect theory might diminish in complex decision environments or when the stakes are very high relative to an individual's wealth. Experience in markets may also lead to more rational behaviour.

Despite these limitations, international surveys have confirmed that prospect theory provides a good description of lottery choices across various cultures, and recent replications have supported its empirical foundations.

Critiques

Critiques of prospect theory include the difficulty in precisely determining the reference point in real-world scenarios, as it can be influenced by numerous external factors and individual expectations. Some argue that while it predicts choices, it doesn't fully explain the actual decision-making process and might even be more cognitively demanding than traditional expected utility theory. The importance of framing effects, a key element of prospect theory, has also been questioned in complex or experienced-based decision environments. Additionally, some experimental evidence in different cultural contexts suggests that the theory's predictions might not always hold, particularly when the financial incentives are large relative to an individual's wealth.