Optimal Portfolio Choice for Higher-order Risk Averters

44 Pages Posted: 14 May 2019 Last revised: 2 Apr 2021

See all articles by Yi Fang

Yi Fang

Jilin University (JLU) - Center for Quantitative Economics

Thierry Post

Graduate School of Business of Nazarbayev University

Date Written: April 23, 2019

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

Suggested Citation

Fang, Yi and Post, Thierry, Optimal Portfolio Choice for Higher-order Risk Averters (April 23, 2019). Available at SSRN: https://ssrn.com/abstract=3376468 or http://dx.doi.org/10.2139/ssrn.3376468

Yi Fang

Jilin University (JLU) - Center for Quantitative Economics ( email )

Changchun, Jilin 130012
China

Thierry Post (Contact Author)

Graduate School of Business of Nazarbayev University ( email )

53 Kabanbay Batyra Avenue
Astana, 010000
Kazakhstan

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