Subjective probabilities under behavioral heuristics

Abstract

We develop an approach to forming the subjective probabilities of future stock returns in the presence of multiple behavioral heuristics. This approach relaxes the assumption that behavioral heuristics are independent and makes it possible to investigate the individual effects as well as the joint effect of different behavioral heuristics on the investor’s probability assessment. In contrast to the objective probabilities, these subjective probabilities reflect the investor’s attitudes towards anticipated changes in the market conditions. They coincide with the objective probabilities when the investor is rational. To illustrate the use of this approach, we explore the implications of anchoring, overconfidence/doubt, and the availability heuristic for the predictability of individual stock returns based on past return data. We find empirically that the existing evidence against the random walk hypothesis may stem from the fact that the objective probabilities of large stock returns of either sign overstate the probabilities that the investor assigns to these returns given the market conditions that are anticipated to occur in the next period, which generates the “peso problem” in the data. Allowing for overconfidence in the subjective distribution of stock returns (induced by the anticipated decrease in the return volatility or the inability of the investor to adequately adjust the limits of the confidence interval away from the anchoring value) substantially decreases (compared with the case of the investor’s rationality) the degree, to which individual stock returns are predictable based on their past history, and, therefore, helps solve the stock return predictability puzzle.