Applying hueristic algorithms to portfolio selection problem

In this paper, we solve the portfolio selection problem. In our approach, we first propose a modified immune algorithm (IA) to reuse the memory cells we got in earlier stages, so that more information can be utilized in the next stages. Our experimental results show that the modified IA can successfully obtain significantly higher return than genetic algorithm (GA) and particle swarm optimization (PSO). Second, we also propose a hybrid of IA and PSO (IA-PSO), and a hybrid of GA and PSO. From our experiments, the hybrid IA-PSO maintains the high return while becoming more stable.