An Approach for Diverse Group Stock Portfolio Optimization Using the Fuzzy Grouping Genetic Algorithm

摘要: Previously, an algorithm has been proposed for optimizing a diverse group stock portfolio using the grouping genetic algorithm. However, it is not easy to set appropriate parameters operations when datasets are different in previous approach. In this paper, we propose approach that can only obtain but also tune dynamically fuzzy Three parts, grouping, stock, and used as encoding scheme. The fitness function defined utilized evaluate quality of chromosome. To deal with parameter setting operations, logic controller designed employed adjust them predefined knowledge base deriving better solution. Experiments on real dataset were conducted show effectiveness