Michael O. AdairManaging Director, Senior Investment Consultant | 2018

The Origins of Behavioral Finance

The origin of behavioral finance can be attributed to the publication of prospect theory in 1979—the behavioral economist’s replacement for expected utility theory.

The origin of behavioral finance can be attributed to the publication of prospect theory in 1979—the behavioral economist’s replacement for expected utility theory.7 Prospect theory built on several previous articles that showcased cognitive shortcuts, also known as heuristics, and their substantial impact on decision-making.8 The theory consists of four major components: reference points, probability weighting, loss aversion, and diminishing sensitivity.

The most salient feature of prospect theory for investment professionals is loss aversion. Prospect theory asserts that losses loom larger than gains.3

In other words, the feeling associated with a loss is much stronger than the positive feeling experienced with a gain. For instance, individuals report that a 50% chance of losing $100 must be offset by a 50% chance of gaining $200.9 A 50/50 chance of winning or losing $100 is deemed too risky. In order to be comfortable with the bet, people require a better upside—on average one that’s twice the size of the loss. According to standard economics, however, people should accept a gamble as long as the positive gain surpasses $100. This phenomenon only scratches the surface of the influence of loss aversion.

Turning to the stock market, investors are prone to keep losing stocks, hoping they will rebound, and are more likely to sell gaining stocks, afraid of a potential downturn. Historical data indicate that the momentum of a gaining stock is likely to continue and those with a negative return should be sold off.10 Nevertheless, loss aversion can promote disadvantageous behaviors in the market.

Similarly, prospect theory argues that people are risk-seeking over losses but risk-averse in gains. The following finding illustrates the asymmetrical shape of risk preferences shown in the graph below. Most people prefer the certainty of receiving $3,000 over the 80% chance of $4,000. However, when these figures enter the negative domain, people prefer the 80% chance of losing $4,000 over the certainty of losing $3,000.11

The existence of this phenomenon can be explained by another tenet of prospect theory: probability weighting. Behavioral finance research suggests that people critically misjudge probabilities and their objective value. In general, individuals tend to put extra weight on low probabilities but underweight high probabilities. For instance, people stated that a 5% chance of winning $100 was worth $10 but a 90% chance of winning $100 was only worth $63.12 This finding depicts how even objective values can be perceived subjectively and demonstrates a common theme in behavioral finance: almost everyone struggles with statistics.

This leads to further errors of judgment in the markets. Investors buy too many positively skewed stocks—shares that have long right tails—in the hopes that the companies turn out to be the next Google. Their optimistic expectations lead to inefficient asset allocations and increased risk, particularly because positively skewed stocks tend to have below average returns.13

Prospect theory has also led to the development of a more robust asset pricing model that incorporates loss aversion and the influence of past outcomes.14 Research has shown how investors become more risk-seeking after experiencing gains, but risk-averse after realizing losses.15 Commonly referred to as the “house money effect” in the behavioral finance field, the phenomenon can explain the dynamic nature of risk preferences over time. After seeing positive returns, people are willing to take on more risk because they see the gains as a cushion against potential losses. That sentiment certainly rings true in the current bull market and record-setting stock market in 2017. By integrating the fluctuations in risk and loss aversion, the behavioral finance pricing model can explain more stock market data, including high historical returns and volatile periods.

REFERENCE POINTS

Behavioral finance also relies upon the influence of reference points. Prospect theory argues that individuals make decisions based not merely on final outcomes, but how those outcomes compare to a reference point, typically the status quo. Take the following example adapted from Kahneman’s speech upon receiving the Nobel Prize in Economics in 2002. One investor sees their portfolio increase from $1 million to $1.5 million. Another investor witnesses their portfolio fall to $2 million from its initial position of $3 million. Consider these questions: Who has the higher welfare of the two? And who is happier?16

That simple example demonstrates that the final state is not as salient as the context or point of reference. Although the second investor still has more wealth, it would be hard to argue that they are happier. A similar phenomenon is observed when comparing the levels of happiness when receiving $200 instead of $100 than when receiving $1,200 instead of $1,100.17 Both represent a $100 difference, but relatively the first is a significantly happier event. These instances illustrate how relative changes matter more than the ultimate outcome.

Despite the importance of assessing reference points, locating them for every person can prove difficult. This could partially explain why behavioral finance has experienced a slow uptake in practice.18 For some individuals the reference point might be their current wealth, but for others it might be the expected returns of a portfolio, or perhaps a return above the risk-free rate. Any positive returns would be seen as a gain for the first person, but for the second and third investor, a certain threshold of returns must be reached. Advisors should pay close attention to their clients in order to gauge their reference point and maintain a positive relationship.

The origin of behavioral finance can be attributed to the publication of prospect theory in 1979—the behavioral economist’s replacement for expected utility theory.

Sources

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