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

Author

Listed:
  • Shushang Zhu

    (Department of Management Science, School of Management, Fudan University, Shanghai 200433, China)

  • Masao Fukushima

    (Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan)

Abstract
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.

Suggested Citation

  • Shushang Zhu & Masao Fukushima, 2009. "Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management," Operations Research, INFORMS, vol. 57(5), pages 1155-1168, October.
    • Handle: RePEc:inm:oropre:v:57:y:2009:i:5:p:1155-1168
    DOI: 10.1287/opre.1080.0684
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    References listed on IDEAS

    as
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