KMS Of Academy of mathematics and systems sciences, CAS
| A sparse enhanced indexation model with chance and cardinality constraints | |
Xu, Fengmin2; Wang, Meihua1,2; Dai, Yu-Hong3 ; Xu, Dachuan4
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| 2018 | |
| Source Publication | JOURNAL OF GLOBAL OPTIMIZATION
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| ISSN | 0925-5001 |
| Volume | 70Issue:1Pages:5-25 |
| Abstract | 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. |
| Keyword | Enhanced indexation Chance constraint Mixed integer programming Distributionally robust approach |
| DOI | 10.1007/s10898-017-0513-1 |
| Language | 英语 |
| Funding Project | 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 Research Area | Operations Research & Management Science ; Mathematics |
| WOS Subject | Operations Research & Management Science ; Mathematics, Applied |
| WOS ID | WOS:000419940800002 |
| Publisher | SPRINGER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/29341 |
| Collection | 计算数学与科学工程计算研究所 |
| Corresponding Author | Wang, Meihua |
| Affiliation | 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 |
| Recommended Citation 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. |
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