Developments of Mean-Variance Model for Portfolio Selection in Uncertain Environment
نویسندگان
چکیده
This paper presents portfolio selection problems with ambiguous returns assumed as “return is about ξ” which is neither estimated by randomness nor fuzziness. Portfolio selection problems in uncertain environment are formulated as nonlinear programming models based on uncertain programming approaches. Since there is no efficient solution method to solve these problems directly, original problems are transformed into equivalent deterministic programming problems using expected value and variance via identification function of uncertain variables and finally to find the optimal solution of each problem is constructed. To illustrate the proposed models, some examples of portfolio selection problems in uncertain environment as a generalization of random environment and fuzzy environment are provided.
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