Skewness-Aware Asset Allocation: Relation to Utility Theory and Empirical Evidence

This paper presents a new measure of skewness, skewness-aware deviation, that can be linked to tail risk measures such as Value-at-Risk. We show that this measure of skewness arises naturally also when one thinks of maximizing the certainty equivalent for an investor with a neg-ative exponential utility function, thus bringing together the mean-risk and the expected utility framework for an important class of investor preferences. We generalize the idea of variance and covariance in the new skewness-aware asset pricing and allocation framework. We show via computational experiments that the proposed approach results in improved and intuitively appealing asset allocation when returns follow real-world or simulated skewed distributions. We also suggest a skewness-aware equivalent of the classical CAPM beta, and study its consistency with the observed behavior of the stocks traded at the NYSE between 1963 and 2006