Improved Particle Swarm Optimization for Realistic Portfolio Selection

In this paper, the realistic portfolio selection problem is studied and an algorithm named improved particle swarm optimization (IPSO) is presented to solve this problem. At first, a realistic portfolio selection model, as an alternative to the standard Markowitz model, is formulated for selecting portfolios with transaction costs and quantity constraint. In addition, due to these complex constraints traditional optimization algorithms fail to work efficiently and heuristic algorithms can be the best method, so we present an improved particle swarm optimization to solve our problem. Finally, a numerical example is given to illustrate our proposed effective model and method. Experiment results show that our proposed method is an efficient method for solving realistic portfolio selection problem and more superior than standard PSO method.