Fuzzy multi-period portfolio selection optimization models using multiple criteria

To simulate the real transactions in financial market, multiple decision criteria in portfolio selection should be considered to provide investors with additional choices. This paper deals with multi-period portfolio selection problems in fuzzy environment by considering some or all criteria, including return, transaction cost, risk and skewness of portfolio. Two possibilistic portfolio optimization models by using multiple criteria are first presented for the basic multi-period portfolio selection problem. Then, they are naturally extended to dynamic feedback models with closed-loop control policies. A TOPSIS-compromised programming approach is designed originally to transform the proposed models into single objective models. After that, a genetic algorithm is devised for obtaining optimal solutions. Furthermore, a numerical example is given to illustrate the advantage of the proposed models and the efficiency of the designed algorithm over the existing approaches.