Robust Mean-Conditional Value at Risk Portfolio Optimization
نویسندگان
چکیده
In the portfolio optimization, the goal is to distribute the fixed capital on a set ofinvestment opportunities to maximize return while managing risk. Risk and return are quantiti es that are used as input parameters for the optimal allocation of the capital in the suggested models. But these quantities are not known at the time of the formulation and solving problem. Thus they shou ld be estimated to solve the problem which might lead to large error. One of the widely used approaches to deal with such a situation, is robust optimization. In this paper we study the meanConditional Value at Risk (M-CVaR) portfolio selection problems under the estimation risk in mean return for both interval and ellipsoidal uncertainty sets. Equivalent formulations of the robust counterparts are given. At end an example is given to demonstrate the impact of uncertainty.
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