Management of Stochastic Portfolio using Improved Genetic Algorithm

The problem of portfolio selection in investment is concerned with minimizing the risk for a specified level of return. In this paper, the portfolio investment in which expected return rates are stochastic variables is studied and the improved genetic algorithms is applied to solve this problem. First, the stochastic portfolio model and reliable decision are presented. Second, considering the deficiency of the standard genetic algorithm, several improvements are introduced to the GA to speed up its convergence as well as to improve performances. Finally, a numerical example of a portfolio selection problem is given to illustrate our proposed effective means. Compared with adaptive genetic algorithm, the new algorithm is effective and has potential to solve the portfolio management problem in real time