Optimal Portfolio Choice for Higher-order Risk Averters

Abstract

Optimal portfolio choice is investigated for investors with various types of higher-order risk aversion. Finite systems of convex inequalities are introduced to evaluate the efficiency of a given benchmark, and for constructing enhanced portfolios which dominate the benchmark for all higher-order risk averters. An analysis of equity industry rotation strategies shows that accounting for skewness love and kurtosis aversion increases long positions in recent winner industries which feature more favorable skewness and kurtosis than the market index. An analysis of equity stock index options combinations shows that accounting for higher-order risk aversion leads to buying of underpriced option series in addition to the standard solution of writing of overpriced options. In both applications, optimization with higher-order risk constraints appears leads to superior out-of-sample performance compared with simpler strategies based on heuristic rules, single utility functions and limiting portfolio variance.

Keywords: Portfolio choice, Higher-order risk, Enhanced indexing, Equity industry rotation, Equity index options

JEL Classification: C61, D81, G11