Behavioral Finance

Behavioral finance is a field of study that examines how psychology influences the financial decisions of individuals and institutions, and how those decisions affect market prices. It starts from the observation that people do not always act as the fully rational, well-informed agents assumed in traditional finance theory. Instead they rely on mental shortcuts, are swayed by emotions and social pressure, and make predictable errors when judging risk and probability.

The field grew out of behavioral economics and challenges parts of the efficient market hypothesis, which holds that prices fully reflect available information. Behavioral finance is used to explain market anomalies, bubbles and crashes, and to design better savings plans and financial products. Its insights have been taken up by regulators, pension designers, advisers and fintech firms, and it is now a standard part of finance courses.

Classic finance theory imagines investors as calculators: they weigh every fact, never panic and always choose the option with the best expected outcome. Real people are not like that. They hold on to losing shares because selling would mean admitting a mistake, they buy what everyone else is buying, and they feel a loss far more sharply than a gain of the same size.

Behavioral finance studies these habits. It asks why people make the choices they do with money, and what happens to prices when millions of people share the same habits. It also asks how small changes, such as signing workers up to a pension automatically, can help people make choices they are happier with later.

Psychologists Daniel Kahneman and Amos Tversky laid the foundations in the 1970s with their work on judgement under uncertainty and prospect theory, published in 1979, which showed that people evaluate outcomes as gains and losses relative to a reference point. Economist Richard Thaler applied these ideas to markets and savings from the 1980s, and Robert Shiller showed that share prices move far more than changes in dividends would justify. Kahneman received the Nobel memorial prize in economics in 2002, Shiller shared it in 2013, and Thaler won it in 2017. Their work was popularised by books such as Shiller's Irrational Exuberance and Thaler and Cass Sunstein's Nudge.

Behavioral finance has catalogued many systematic tendencies, including:

• Loss aversion. Losses hurt roughly twice as much as equal gains please, a central finding of prospect theory described in loss aversion.
• Anchoring. People rely too heavily on an initial number, such as a purchase price, a pattern known as anchoring and adjustment.
• Overconfidence. Investors overrate their skill and information, leading to excessive trading.
• The disposition effect. Investors sell winners too early and hold losers too long.
• Herding. People follow the crowd, the theme of the bandwagon effect.
• Framing. The same choice can be judged differently depending on how it is presented, the framing effect.
• Mental accounting. Money is treated differently depending on its source or label, such as a bonus versus a salary.

If enough investors share the same biases, prices can move away from fundamental value for long periods. Behavioral explanations have been offered for momentum, in which recent winners keep rising for a time; for overreaction and later reversal; and for bubbles such as the dot-com boom. In theory, arbitrage by rational traders should correct mispricing, but behavioral researchers point out that arbitrage is risky and costly, so mispricing can persist. The same ideas help explain why investors chase past fund performance, under-diversify into familiar companies and react strongly to vivid news. John Maynard Keynes's notion of animal spirits anticipated many of these themes.

Behavioral insights have changed policy. Automatic enrolment in workplace pensions, with an opt-out rather than an opt-in, raised participation sharply in the United States and United Kingdom. Regulators use behavioral research to design disclosures and to curb sales techniques that exploit biases. Crypto markets provide many examples: fear of missing out, captured in FOMO, drives buying near peaks; loyalty to a coin can resemble the endowment effect; and trading apps that gamify investing raise concerns about encouraging overtrading. Sentiment indices that try to measure fear and greed are popular among crypto traders, although their predictive value is limited.

Critics argue that behavioral finance offers a list of biases rather than a single unified theory, and that for almost any market move a bias can be found to explain it after the fact. Some laboratory findings have not replicated well, and effects seen in small experiments may weaken when real money and professional investors are involved. Defenders of efficient markets, notably Eugene Fama, argue that many anomalies disappear once risk is properly measured. Most economists now see the two approaches as complementary: markets are often efficient enough to be hard to beat, yet human behaviour can still produce bubbles, crashes and costly personal mistakes.