Adjusted robust mean-value-at-risk model: less conservative robust portfolios
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We examine the robust mean-VaR portfolio optimization problem when a parametric approach is used for estimating VaR. A robust optimization formulation is used to accommodate estimation risk, and we obtain an analytic solution when there is a risk-free asset and short-selling is allowed. This renders the model computationally tractable. Further, to avoid the conservatism of robust optimal portfolios, we suggest an adjusted robust optimization approach. Empirically, we evaluate the out-of-sample performance of the new approach, the robustness of obtained solutions and level of conservatism of the resulting portfolios. The empirical results highlight some benefits of our approach.
KeywordsMean-value-at-risk Estimation error Solution robustness Structure robustness Robust optimization Conservatism
Mathematics Subject Classification91G10 62H12 90C22
The authors would like to thank anonymous referees for their constructive comments which led to significant improvement on the early draft of this paper.
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