PARTICLE SWARM OPTIMIZATION FOR CONSTRAINED PORTFOLIO SELECTION PROBLEMS
Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions, modern portfolio theory is based on a rational investor choosing the proportions of assets in a portfolio so ns to minimize risk and maximize the expected return. In this paper, the constrained portfolio selection problem is studied and a heuristic algorithm based on the particle swarm optimization (PSO) is applied to solve this problem. At first,considering of some complex realistic constrains a new portfolio selection model is formulated. In addition, PSO algorithm is given to solve this new model because traditional optimization algorithms fail to work efficiently.Finally, a numerical example of a portfolio selection problem is given to illustrate our proposed effective means.
Portfolio selection transaction cost floor and ceiling constrains particle swarm optimization
WEI CHEN RUN-TONG ZHANG YONG-MING CAI FA-SHENG XU
School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China School of Science,Jinan University, Jinan, 250022, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
2425-2429
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）