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Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management

Shushang Zhu¹; Masao Fukushima²

¹ Department of Management Science, School of Management, Fudan University, Shanghai 200433, China; · ² Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan

This paper considers the worst-case Conditional Value-at-Risk (CVaR) in the situation where only partial information on the underlying probability distribution is available. The minimization of the worst-case CVaR under mixture distribution uncertainty, box uncertainty, and ellipsoidal uncertainty are investigated. The application of the worst-case CVaR to robust portfolio optimization is proposed, and the corresponding problems are cast as linear programs and second-order cone programs that can be solved efficiently. Market data simulation and Monte Carlo simulation examples are presented to illustrate the proposed approach.

DOI

10.1287/opre.1080.0684

Volume

57 (5)

Pages

1155-1168

Language

en

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BibTeX

Sources

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