Portfolio Optimization Using Evolutionary Algorithms

Abstract

In this study, a double-stage evolutionary algorithm is proposed for portfolio optimization. In the first stage, a genetic algorithm is used to identify good-quality assets in terms of asset ranking. In the second stage, investment allocation in the selected good-quality assets is optimized using another genetic algorithm based on Markowitz’s theory. Through the two-stage genetic optimization process, an optimal portfolio can be determined. Experimental results obtained reveal that the proposed double-stage evolutionary algorithm for portfolio optimization provides a very useful tool to assist the investors in planning their investment strategy and constructing their portfolio.