Nonconvex multi-period mean-variance portfolio optimization

Zhongming Wu, Guoyu Xie, Zhili Ge and Valentina De Simone ()
Additional contact information
Zhongming Wu: Nanjing University of Information Science and Technology
Guoyu Xie: Nanjing University of Information Science and Technology
Zhili Ge: Nanjing Normal University of Special Education
Valentina De Simone: University of Campania “Luigi Vanvitelli”

Annals of Operations Research, 2024, vol. 332, issue 1, No 22, 617-644

Abstract: Abstract In this paper, we address the problem of long-term investment by exploring optimal strategies for allocating wealth among a finite number of assets over multiple periods. Based on the classical Markowitz mean-variance philosophy, we develop a new portfolio optimization framework which can produce sparse portfolios. The sparsity of the portfolio at each and across periods is characterized by the possibly nonconvex penalties. For the constructed nonconvex and nonsmooth constrained model, we propose a generalized alternating direction method of multipliers and its global convergence to a stationary point can be guaranteed theoretically. Moreover, some numerical experiments are conducted on several datasets generated from practical applications to illustrate the effectiveness and advantage of the proposed model and solving method.

Keywords: Portfolio optimization; Multi-period; Mean-variance; Nonconvex penalty; Alternating direction method of multipliers (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-023-05524-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:332:y:2024:i:1:d:10.1007_s10479-023-05524-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-023-05524-x

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().