A sparse enhanced indexation model with chance and cardinality constraints

doi:10.1007/s10898-017-0513-1

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 计算数学与科学工程计算研究所

	A sparse enhanced indexation model with chance and cardinality constraints
	Xu, Fengmin 2; Wang, Meihua 1,2; Dai, Yu-Hong3 ; Xu, Dachuan 4
刊名	JOURNAL OF GLOBAL OPTIMIZATION
	2018
卷号	70 期号:1 页码:5-25
关键词	Enhanced indexation Chance constraint Mixed integer programming Distributionally robust approach
ISSN号	0925-5001
DOI	10.1007/s10898-017-0513-1
英文摘要	Enhanced indexation aims to construct a portfolio to track and outperform the performance of a stock market index by employing both passive and active fund management strategies. This paper presents a novel sparse enhanced indexation model with chance and cardinality constraints. Its goal is to maximize the excess return that can be attained with a high probability, while the model allows a fund manger to limit the number of stocks in the portfolio and specify the maximum tolerable relative market risk. In particular, we model the asset returns as random variables and estimate their probability distributions by the Capital Asset Pricing Model or Fama-French 3-factor model, and measure the relative market risk with the coherent semideviation risk function. We deal with the chance constraint via distributionally robust approach and present a second-order cone programming and a semidefinite programming safe approximation for the model under different sets of potential distribution functions. A hybrid genetic algorithm is applied to solve the NP-hard problem. Numerical tests are conducted on the real data sets from major international stock markets, including USA, UK, Germany and China. The results demonstrate that the proposed model and the method can efficiently solve the enhanced indexation problem and our approach can generally achieve sparse tracking portfolios with good out-of-sample excess returns and high robustness.
资助项目	National Natural Science Foundation of China[11571271] ; National Natural Science Foundation of China[11631013] ; National Natural Science Foundation of China[71501155] ; National Natural Science Foundation of China[11601409] ; National Natural Science Foundation of China[11331012] ; National Natural Science Foundation of China[71331001] ; National Natural Science Foundation of China[11531014] ; Postdoctoral Science Foundation of China[2013M530418] ; Postdoctoral Science Foundation of China[2014T70908] ; National Funds for Distinguished Young Scientists[11125107] ; National 973 Program of China[2015CB856000]
WOS研究方向	Operations Research & Management Science ; Mathematics
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000419940800002
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/29340]
专题	计算数学与科学工程计算研究所
通讯作者	Wang, Meihua
作者单位	1.Xidian Univ, Sch Econ & Management, Xian 710071, Shaanxi, Peoples R China 2.Xi An Jiao Tong Univ, Sch Econ & Finance, Xian 710061, Shaanxi, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 4.Beijing Univ Technol, Dept Informat & Operat Res, Coll Appl Sci, Beijing 100124, Peoples R China
推荐引用方式 GB/T 7714	Xu, Fengmin,Wang, Meihua,Dai, Yu-Hong,et al. A sparse enhanced indexation model with chance and cardinality constraints[J]. JOURNAL OF GLOBAL OPTIMIZATION,2018,70(1):5-25.
APA	Xu, Fengmin,Wang, Meihua,Dai, Yu-Hong,&Xu, Dachuan.(2018).A sparse enhanced indexation model with chance and cardinality constraints.JOURNAL OF GLOBAL OPTIMIZATION,70(1),5-25.
MLA	Xu, Fengmin,et al."A sparse enhanced indexation model with chance and cardinality constraints".JOURNAL OF GLOBAL OPTIMIZATION 70.1(2018):5-25.