An island-based algorithm for group stock portfolio optimization

摘要

This paper presents an island-based optimization approach to speed up the evaluation process for optimizing a diverse group stock portfolio which can provide various chooses for users to make investment decisions. It first initializes a population for each island. For every t generation, the best chromosome of each island is selected and putted into a master island. Then, chromosomes in master island will migrate to other islands in order to get a near optimal solution. Experimental results on a real dataset were also conducted and indicated that the proposed approach is better than the previous approach in terms of evolution time and returns of the optimized stock portfolios.