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• W2140683749 abstract "One of the basic problems of applied finance is the optimal selection of stocks, with the aim of maximizing future returns and constraining risks by an appropriate measure. Here, the problem is formulated by finding the portfolio that maximizes the expected return, with risks constrained by the worst conditional expectation. This model is a straightforward extension of the classic Markovitz mean–variance approach, where the original risk measure, variance, is replaced by the worst conditional expectation. The worst conditional expectation with a threshold α of a risk X, in brief WCEα(X), is a function that belongs to the class of coherent risk measures. These are measures that satisfy a set of properties, such as subadditivity and monotonicity, that are introduced to prevent some of the drawbacks that affect some other common measures. This paper shows that the optimal portfolio selection problem can be formulated as a linear programming instance, but with an exponential number of constraints. It can be solved efficiently by an appropriate generation constraint subroutine, so that only a small number of inequalities are actually needed. This method is applied to the optimal selection of stocks in the Italian financial market and some computational results suggest that the optimal portfolios are better than the market index." @default.
• W2140683749 created "2016-06-24" @default.
• W2140683749 creator A5016272288 @default.
• W2140683749 date "2003-11-01" @default.
• W2140683749 modified "2023-09-27" @default.
• W2140683749 title "The optimal portfolio problem with coherent risk measure constraints" @default.
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• W2140683749 doi "https://doi.org/10.1016/s0377-2217(02)00785-3" @default.
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