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arXiv · 2303.15830

Mean-variance hybrid portfolio optimization with quantile-based risk measure

Weiping Wu·Yu Lin·Jianjun Gao·Ke Zhou
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Abstract

This paper addresses the importance of incorporating various risk measures in portfolio management and proposes a dynamic hybrid portfolio optimization model that combines the spectral risk measure and the Value-at-Risk in the mean-variance formulation. By utilizing the quantile optimization technique and martingale representation, we offer a solution framework for these issues and also develop a closed-form portfolio policy when all market parameters are deterministic. Our hybrid model outperforms the classical continuous-time mean-variance portfolio policy by allocating a higher position of the risky asset in favorable market states and a less risky asset in unfavorable market states. This desirable property leads to promising numerical experiment results, including improved Sortino ratio and reduced downside risk compared to the benchmark models.

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Weiping Wu, Yu Lin, Jianjun Gao, Ke Zhou. 2023-03-28. Mean-variance hybrid portfolio optimization with quantile-based risk measure. https://arxiv.org/abs/2303.15830

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