KMS Of Academy of mathematics and systems sciences, CAS
Fast algorithms for sparse portfolio selection considering industries and investment styles | |
Dong, Zhi-Long1; Xu, Fengmin1; Dai, Yu-Hong2 | |
2020-05-25 | |
Source Publication | JOURNAL OF GLOBAL OPTIMIZATION
![]() |
ISSN | 0925-5001 |
Pages | 27 |
Abstract | In 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. |
Keyword | Portfolio selection Industry classification Style investment ADMM Sparse optimization |
DOI | 10.1007/s10898-020-00911-1 |
Indexed By | SCI |
Language | 英语 |
Funding Project | National 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 Area | Operations Research & Management Science ; Mathematics |
WOS Subject | Operations Research & Management Science ; Mathematics, Applied |
WOS ID | WOS:000535168700001 |
Publisher | SPRINGER |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/51480 |
Collection | 中国科学院数学与系统科学研究院 |
Corresponding Author | Xu, Fengmin |
Affiliation | 1.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. |
Files in This Item: | There are no files associated with this item. |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment