A multi-objective evolutionary approach to the portfolio optimization problem

The portfolio optimization problem is a well-known difficult problem occurring in financial real world. The problem consists in choosing an optimal set of assets in order to minimize the risk and maximize the profit of the investment. A multiobjective approach to this problem is suggested in this paper. We use three well-known evolutionary algorithms (namely NSGA2, PESA and SPEA2) for solving the bi-objective portfolio optimization problem. Several numerical experiments are performed using real-world data. The results show that PESA outperforms NSGA2 and SPEA2 for the considered test cases