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The optimal portfolio of α-maxmin mean-VaR problem for investors

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  • Kang, Zhilin
  • Zhao, Linhai
  • Sun, Jingyun

Abstract

Value-at-Risk (VaR) is one of the most widely accepted risk measures in the financial industries, yet efficient computation of VaR remains a challenging issue. In this paper, we investigate an α-maxmin mean-VaR portfolio selection problem for investors when only partial information of the underlying distribution is available. Unlike the classical worst-case approach, which only deal with extremely ambiguity-averse attitude, our model is flexible and allows for investors with different levels of ambiguity aversion. Closed-form expressions for the optimal investment strategies are achieved and hence can be easily applied in practice. We illustrate the efficiency of our results with an example.

Suggested Citation

  • Kang, Zhilin & Zhao, Linhai & Sun, Jingyun, 2019. "The optimal portfolio of α-maxmin mean-VaR problem for investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119303784
    DOI: 10.1016/j.physa.2019.04.014
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