An asset subset-constrained minimax optimization framework for online portfolio selection

Simple item page
dc.citation.volume254
dc.contributor.authorYin J
dc.contributor.authorZhong A
dc.contributor.authorXiao X
dc.contributor.authorWang R
dc.contributor.authorHuang JZ
dc.date.accessioned2024-07-30T03:11:15Z
dc.date.available2024-07-30T03:11:15Z
dc.date.issued2024-11-15
dc.description.abstractEffective online portfolio selection necessitates seamless integration of three key properties: diversity, sparsity, and risk control. However, existing algorithms often prioritize one property at the expense of the others due to inherent conflicts. To address this issue, we propose an asset subset-constrained minimax (ASCM) optimization framework, which generates optimal portfolios from diverse investment strategies represented as asset subsets. ASCM consists of: (i) a minimax optimization model that focuses on risk control by considering a set of loss functions constrained by different asset subsets; (ii) the construction of asset subsets via price-feature clipping, which effectively reduces redundant assets in the portfolio; (iii) a state-based estimation of price trends that guides all ASCM loss functions, facilitating the generation of sparse solutions. We solve the ASCM minimax model using an efficient iterative updating formula derived from the projected subgradient method. Furthermore, we achieve near O(1) time complexity through a novel initialization scheme. Experimental results demonstrate that ASCM outperforms eight representative algorithms, including the best constant rebalanced portfolio in hindsight (BCRP) on five out of the six real-world financial datasets. Notably, ASCM achieves a 67-fold improvement over BCRP in cumulative wealth on the TSE dataset.
dc.description.confidentialfalse
dc.identifier.citationYin J, Zhong A, Xiao X, Wang R, Huang JZ. (2024). An asset subset-constrained minimax optimization framework for online portfolio selection. Expert Systems with Applications. 254.
dc.identifier.doi10.1016/j.eswa.2024.124299
dc.identifier.eissn1873-6793
dc.identifier.elements-typejournal-article
dc.identifier.issn0957-4174
dc.identifier.number124299
dc.identifier.piiS0957417424011655
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/71154
dc.languageEnglish
dc.publisherElsevier Ltd
dc.publisher.urihttps://www.sciencedirect.com/science/article/pii/S0957417424011655
dc.relation.isPartOfExpert Systems with Applications
dc.rights(c) 2024 The Author/s
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectAsset subset-constrained online portfolio selection
dc.subjectMinimax optimization
dc.subjectProjected subgradient method
dc.subjectRobust online portfolio selection
dc.titleAn asset subset-constrained minimax optimization framework for online portfolio selection
dc.typeJournal article
pubs.elements-id489242
pubs.organisational-groupOther
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Published version.pdf
Size:
2.07 MB
Format:
Adobe Portable Document Format
Description:
489242 PDF.pdf
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
9.22 KB
Format:
Plain Text
Description:
Download
Collections
Journal Articles