Optimal portfolio choice for higher-order risk averters
Fang Y. Post T.
April 2022Elsevier B.V.
Journal of Banking and Finance
2022#137
The effects of higher-order risk aversion on optimal cross-sectional portfolio choice are investigated using portfolio optimization with Stochastic Dominance constraints. Tractable sufficient conditions for higher-degree dominance are introduced that take the form of a system of linear inequalities. Existing studies of active equity industry rotation are extended from lower degrees to higher degrees of dominance. Fourth-degree dominance assumes that investors are ‘prudent’ and ‘temperate’ and therefore like skewness and dislike kurtosis. Using this dominance criterion leads to superior out-of-sample investment performance, by allowing for more concentration in recent winner industries which tend to show persistent positive abnormal returns and a favorable higher-order risk profile due to the industry-level price momentum effect.
Active portfolio management , Higher-order risk , Linear programming , Portfolio choice , Portfolio optimization
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Professor of Quantitative Economics at the Center for Quantitative Economics, Jilin University and Business School, Jilin University, Changchun, 130012, China
Professor of Finance at the Graduate School of Business of Nazarbayev University and Director at the National Analytical Center ‘Analytica’ JSC, Qabanbay Batyr Ave 53, Astana, 010000, Kazakhstan
Professor of Quantitative Economics at the Center for Quantitative Economics
Professor of Finance at the Graduate School of Business of Nazarbayev University and Director at the National Analytical Center ‘Analytica’ JSC
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