Portfolio optimization is concerned with the optimal allocation of limited capital to the available financial assets to achieve a reasonable tradeoff between risk and profit. The main contribution of this paper is to introduce a new risk measure, conditional value-at-risk (CVaR) of fuzzy variable, to build a class of credibilistic mean-CVaR portfolio optimization model. In the proposed credibilistic portfolio optimization model, the CVaR is used as a measure tool to assess market risk resulted from the financial asset price fluctuations. The computational formulas for common triangular, trapezoidal and normal fuzzy variables are established. Under mild assumptions on the uncertain returns, the proposed credibilistic portfolio optimization model can be turned into its equivalent deterministic mixed-integer parametric programming models, which can be solved by the CPLEX software. The computational results from our numerical experiments demonstrate the efficiency of the proposed CVaR modeling approach as a risk management tool.
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