New methods for portfolio selection problem with fuzzy random variable returns (Q2627562)

Summary: In conventional portfolio optimisation models, the market condition is predicted by historical data and the asset returns are random variables. In this paper, a special class of portfolio selection problems is introduced where the asset returns are fuzzy random variables. Then, the proposed problem is formulated and solved by using new methods. In the presented methods, we use the scalar expected value of fuzzy random variables and fuzzy stochastic chance-constrained programming based on possibility and necessity measures. Furthermore, a numerical example is also given to show the efficiency of the methods discussed in this paper.