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Journal of Undergraduate Research

Keywords

stock return distributions, Bayesian framework

College

Marriott School of Management

Department

Finance

Abstract

In order to make optimal portfolio choices, individuals, firms and portfolio managers are interested in the probabilities attached to their receiving various returns in the stock market. These probabilities of returns on securities are described by statistical functions called return distributions. However, much uncertainty concerning such return distributions exists and over the years many models have been created that attempt to predict the mean and variance of return distributions, and recently some have even been put forth that attempt to predict the skewness of such distributions. The skewness of return distributions is of import to investors in particular because the degree (positive or negative) of skewness the return distribution of a security exhibits is an indication of the chances an investor has to “hit the lottery” (in the case of positive skewness), or, on the other hand, “hit the cellar” (in the case of negative skewness) by investing in that security. If a particular stock has a positively (negatively) skewed return distribution, investors have a higher probability of receiving very large positive (negative) returns on that stock than they would have if the return distribution was not positively (negatively) skewed.

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