Constrained portfolio optimisation: the state-of-the-art Markowitz models

Jin, Yan; Qu, Rong; Atkin, Jason

Abstract

This paper studies the state-of-art constrained portfolio optimisation models, using exact solver to identify the optimal solutions or lower bound for the benchmark instances at the OR-library with extended constraints. The effects of pre-assignment, round-lot, and class constraints based on the quantity and cardinality constrained Markowitz model are firstly investigated to gain insights of increased problem difficulty, followed by the analysis of various constraint settings including those mostly studied in the literature. The study aims to provide useful guidance for future investigations in computational algorithms

Citation

Jin, Y., Qu, R., & Atkin, J. (2016). Constrained portfolio optimisation: the state-of-the-art Markowitz models.

• Conference Name: The 2016 International Conference on Operations Research and Enterprise Systems
• End Date: Feb 25, 2016
• Acceptance Date: Dec 1, 2015
• Publication Date: Feb 25, 2016
• Deposit Date: Jun 10, 2016
• Publicly Available Date: Jun 10, 2016
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/775292
• Publisher URL: http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=NWkb4YbVZOo=&t=1
• Additional Information: Proceedings of 5th the International Conference on Operations Research and Enterprise Systems, pages 388-395. ISBN 9789897581717, DOI: 10.5220/0005758303880395