Algorithm research based on multi period fuzzy portfolio optimization model.

Because the investment market in real life is complex and mobile, there are many other factors to consider when meeting the risk and income equilibrium, such as transaction cost, diversification degree and so on. 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 discusses a multi-objective portfolio optimization problem for practical portfolio selection in fuzzy environment, in which the return rates and the turnover rates are characterized by fuzzy variables. Under the premise of meeting the two wishes level of investors' maximum and minimum risk, we assume that the rate of return is a fuzzy variable, and get the corresponding fuzzy portfolio optimization model. What's more, we apply a particle swarm optimization algorithm to solve the proposed multi-period fuzzy portfolio selection models. To reflect investor's aspiration levels for the two objectives, a fuzzy decision technique is employed to transform the proposed model into a single objective mixed-integer nonlinear programming problem. Finally, a numerical example is given to illustrate the application of our models. Comparative results show that the designed algorithm is effective for solving the proposed models. [ABSTRACT FROM AUTHOR]