QQ客服 官方微博 反馈留言

	A Particle Swarm Optimization Heuristic for the Index Tacking Problem
	Zhu, Hanhong1; Chen, Yun1; Wang, Keshen
	2010
关键词	Particle swarm optimization Index tracking Track error Passive investment management
卷号	6063
页码	238-+
英文摘要	Considering the market is efficient, an obvious portfolio management strategy is passive where the challenge is to track a certain benchmark like a stock index such that equal returns and risks are achieved. An index tracking problem is to minimize the tracking error between a portfolio and a certain benchmark. In this paper, we present a heuristic approach based on particle swarm optimization (PSO) techniques to optimize the solution of the index tracking problem. Our objective is to replicate the performance of a given portfolio under the condition that the number of stocks allowed in the portfolio is smaller than the number of stocks in the benchmark index. In order to evaluate the performance of PSO, the results in this study has been used to compare with those obtained by the genetic algorithms (GAs). The computational results show that particle swarm optimization approach is efficient and effective for solving index tracking optimization problems and the performance of PSO is better than GAs.
会议录出版者	SPRINGER-VERLAG BERLIN
会议录出版地	HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
语种	英语
WOS研究方向	Computer Science
WOS记录号	WOS:000279593300031
内容类型	会议论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/3133]
专题	上海财经大学
作者单位	1.Shanghai Univ Finance & Econ, Sch Publ Econ & Adm, Shanghai 200433, Peoples R China; 2.Norwegian Univ Sci & Technol, Dept Prod & Qual Engn, N-7491 Trondheim, Norway
推荐引用方式 GB/T 7714	Zhu, Hanhong,Chen, Yun,Wang, Keshen. A Particle Swarm Optimization Heuristic for the Index Tacking Problem[C]. 见:.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。