Behavioral Finance: Theories and Evidence
Abstract (Via CFA Institute)
That behavioral finance has revolutionized the way we think about investments cannot be denied. But its intellectual appeal may lie in its cross-disciplinary nature, marrying the field of investments with biology and psychology. This literature review discusses the relevant research in each component of what is known collectively as behavioral finance.
Introduction (Via CFA Institute)
This review of behavioral finance aims to focus on articles with direct relevance to practitioners of investment management, corporate finance, or personal financial planning. Given the size of the growing field of behavioral finance, the review is necessarily selective. As Shefrin (2000, p. 3) points out, practitioners studying behavioral finance should learn to recognize their own mistakes and those of others, understand those mistakes, and take steps to avoid making them. The articles discussed in this review should allow the practitioner to begin this journey. Traditional finance uses models in which the economic agents are assumed to be rational, which means they are efficient and unbiased processors of relevant information and that their decisions are consistent with utility maximization. Barberis and Thaler (2003, p. 1055) note that the benefit of this framework is that it is “appealingly simple.” They also note that “unfortunately, after years of effort, it has become clear that basic facts about the aggregate stock market, the cross-section of average returns, and individual trading behavior are not easily understood in this framework.”
Behavioral finance is based on the alternative notion that investors, or at least a significant minority of them, are subject to behavioral biases that mean their financial decisions can be less than fully rational. Evidence of these biases has typically come from cognitive psychology literature and has then been applied in a financial context.
Examples of biases include
• Overconfidence and overoptimism—investors overestimate their ability and the accuracy of the information they have.
• Representativeness—investors assess situations based on superficial characteristics rather than underlying probabilities.
• Conservatism—forecasters cling to prior beliefs in the face of new information.
• Availability bias—investors overstate the probabilities of recently observed or experienced events because the memory is fresh.
• Frame dependence and anchoring—the form of presentation of information can affect the decision made.
• Mental accounting—individuals allocate wealth to separate mental compartments and ignore fungibility and correlation effects.
• Regret aversion—individuals make decisions in a way that allows them to avoid feeling emotional pain in the event of an adverse outcome.
Behavioral finance also challenges the use of conventional utility functions based on the idea of risk aversion. For example, Kahneman and Tversky (1979) propose prospect theory as a descriptive theory of decision making in risky situations. Outcomes are evaluated against a subjective reference point (e.g., the purchase price of a stock) and investors are loss averse, exhibiting risk-seeking behavior in the face of losses and risk-averse behavior in the face of gains.