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Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management
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Journal Article
Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management
2009
Overview
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.
Publisher
INFORMS,Institute for Operations Research and the Management Sciences
