University of Cambridge
February 2007 (revised April 2010)
Abstract An introduction to behavioural ﬁnance, including a review of the major works and a summary of important heuristics.
Behavioural ﬁnance is the study of the inﬂuence of psychology on the behaviour of ﬁnancial practitioners and the subsequent eﬀect on markets. Behavioural ﬁnance is of interest because it helps explain why and how markets might be ineﬃcient. For more information on behavioural ﬁnance, see Sewell (2001).
Back in 1896, Gustave le Bon wrote The Crowd: A Study of the Popular Mind, one of the greatest and most inﬂuential books of social psychology ever written (le Bon 1896). Selden (1912) wrote Psychology of the Stock Market. He based the book ‘upon the belief that the movements of prices on the exchanges are dependent to a very considerable degree on the mental attitude of the investing and trading public’. In 1956 the US psychologist Leon Festinger introduced a new concept in social psychology: the theory of cognitive dissonance (Festinger, Riecken and Schachter 1956). When two simultaneously held cognitions are inconsistent, this will produce a state of cognitive dissonance. Because the experience of dissonance is unpleasant, the person will strive to reduce it by changing their beliefs. Pratt (1964) considers utility functions, risk aversion and also risks considered as a proportion of total assets. Tversky and Kahneman (1973) introduced the availability heuristic: ‘a judgmental heuristic in which a person evaluates the frequency of classes or the probability of events by availability, i.e. by the ease with which relevant instances come to mind.’ The reliance on the availability heuristic leads to systematic biases. 1
In 1974, two brilliant psychologists, Amos Tversky and Daniel Kahneman, described three heuristics that are employed when making judgments under uncertainty (Tversky and Kahneman 1974): representativeness When people are asked to judge the probability that an object or event A belongs to class or process B, probabilities are evaluated by the degree to which A is representative of B, that is, by the degree to which A resembles B. availability When people are asked to assess the frequency of a class or the probability of an event, they do so by the ease with which instances or occurrences can be brought to mind. anchoring and adjustment In numerical prediction, when a relevant value (an anchor) is available, people make estimates by starting from an initial value (the anchor) that is adjusted to yield the ﬁnal answer. The anchor may be suggested by the formulation of the problem, or it may be the result of a partial computation. In either case, adjustments are typically insuﬃcient. The most cited paper ever to appear in Econometrica, the prestigious academic journal of economics, was written by the two psychologists Kahneman and Tversky (1979). They present a critique of expected utility theory (Bernoulli 1738; von Neumann and Morgenstern 1944; Bernoulli 1954) as a descriptive model of decision making under risk and develop an alternative model, which they call prospect theory. Kahneman and Tversky found empirically that people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty; also that people generally discard components that are shared by all prospects under consideration. Under prospect theory, value is assigned to gains and losses rather than to ﬁnal assets; also probabilities are replaced by decision weights. The value function is deﬁned on deviations from a reference point and is normally concave for gains (implying risk aversion), commonly convex for losses (risk seeking) and is generally steeper for losses than for gains (loss aversion) (see Figure 1 (page 3)). Decision weights are generally lower than the corresponding probabilities, except in the range of low probabilities. The...
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