A new particle swarm optimization based on MATLAB for portfolio selection problem
This paper focuses on the constrained portfolio selection problem and develops an improved particle swarm optimization (IPSO) algorithm to solve it.As an alternative and extension to the standard Markowitz model,a constrained portfolio selection model with transaction costs and quantity limit is formulated for selecting portfolios.Due to these complex constraints,the process becomes a high-dimensional constrained optimization problem.Traditional optimization algorithms fail to work efficiently and heuristic algorithms with effective searching ability can be the best choose for the problem,so we design an improved particle swarm optimization to solve our problem.In order to prevent premature convergence to local minima,we design a new definition for global point.Finally,a numerical example of a portfolio selection problem is given to illustrate our proposed method,the simulation results demonstrate good performance of the IPSO in solving the complex constrained portfolio selection problem.
Swarm Intelligence Particle Swarm Optimization Portfolio selection
Jian-wei Gao Zhong-hua Chu
School of Business Administration,North China Electric Power University,Beijing,102206,China
国际会议
International Conference on Modelling,Identification and Control(模拟、鉴定、控制国际会议)
上海
英文
2008-06-29（万方平台首次上网日期，不代表论文的发表时间）