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Fast algorithms for sparse portfolio selection considering industries and investment styles
Dong, Zhi-Long1; Xu, Fengmin1; Dai, Yu-Hong2
2020-05-25
Source PublicationJOURNAL OF GLOBAL OPTIMIZATION
ISSN0925-5001
Pages27
AbstractIn this paper, we consider a large scale portfolio selection problem with and without a sparsity constraint. Neutral constraints on industries are included as well as investment styles. To develop fast algorithms for the use in the real financial market, we shall expose the special structure of the problem, whose Hessian is the summation of a diagonal matrix and a low rank modification. Specifically, an interior point algorithm taking use of the Sherman-Morrison-Woodbury formula is designed to solve the problem without any sparsity constraint. The complexity in each iteration of the proposed algorithm is shown to be linear with the problem dimension. In the occurrence of a sparsity constraint, we propose an efficient three-block alternating direction method of multipliers, whose subproblems are easy to solve. Extensive numerical experiments are conducted, which demonstrate the efficiency of the proposed algorithms compared with some state-of-the-art solvers.
KeywordPortfolio selection Industry classification Style investment ADMM Sparse optimization
DOI10.1007/s10898-020-00911-1
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[11631013] ; National Natural Science Foundation of China[11991021] ; National Natural Science Foundation of China[11991020] ; National Natural Science Foundation of China[11971372] ; National Natural Science Foundation of China[11801433] ; National Natural Science Foundation of China[71501155] ; National Natural Science Foundation of China[11571271] ; Beijing Academy of Artificial Intelligence (BAAI)
WOS Research AreaOperations Research & Management Science ; Mathematics
WOS SubjectOperations Research & Management Science ; Mathematics, Applied
WOS IDWOS:000535168700001
PublisherSPRINGER
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/51480
Collection中国科学院数学与系统科学研究院
Corresponding AuthorXu, Fengmin
Affiliation1.Xi An Jiao Tong Univ, Sch Econ & Finance, Xian 710061, Shaanxi, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Dong, Zhi-Long,Xu, Fengmin,Dai, Yu-Hong. Fast algorithms for sparse portfolio selection considering industries and investment styles[J]. JOURNAL OF GLOBAL OPTIMIZATION,2020:27.
APA Dong, Zhi-Long,Xu, Fengmin,&Dai, Yu-Hong.(2020).Fast algorithms for sparse portfolio selection considering industries and investment styles.JOURNAL OF GLOBAL OPTIMIZATION,27.
MLA Dong, Zhi-Long,et al."Fast algorithms for sparse portfolio selection considering industries and investment styles".JOURNAL OF GLOBAL OPTIMIZATION (2020):27.
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