A PIP-Based Approach for Optimizing a Group Stock Portfolio by Grouping Genetic Algorithm

摘要: Recently, some approaches have been proposed for finding a group stock portfolio (GSP). However, price series of stocks which are useful information may not be considered in those approaches. Hence, this study takes into consideration and presents perceptually important point (PIP)-based approach obtaining GSP. Since the PIP is used, can handle with different lengths, means that more GSP could found provided to investors. Each chromosome encoded by grouping, stock, parts. To measure similarity groups, distance designed used as part fitness function. At last, experiments were conducted on real dataset show advantages approach.