Multiobjective Eztremal Optimization for Portfolio Optimization Problem

摘要：

Portfolio optimization plays a critical role in determining portfolio strategies for investors and it is intrinsically a discrete multiobjective optimization problem whose decision criteria conflict with each other. This paper extends a novel numerical multiobjective optimization algorithm, so-called Multiobjective Extremal Optimization (MOEO), to solve the portfolio optimization problem. The proposed approach is validated by five popular stock indexes. The simulation results indicate that the proposed approach is highly competitive with three state-ofthe-art multiobjective evolutionary algorithms, i.e., NSGA-II, SPKA2 and PAES. Thus, MOKO can be considered a good alternative to solve portfolio optimization problem.

关键词： multiobjective optimization multiobjective eztremal optimization portfolio optimization problem

作者: Min-Rong Chen Jian Weng Xia Li

作者单位: College of Information Engineering Shenzhen University Shenzhen,P.R.China Department of Computer Science Jinan University Guangzhou,P.R.China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 552-556

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）