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

Jin, Yan; Qu, Rong; Atkin, Jason

Authors

Yan Jin

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RONG QU rong.qu@nottingham.ac.uk
Associate Professor



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 http://eprints.nottingham.ac.uk/id/eprint/33887
Publisher URL http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=NWkb4YbVZOo=&t=1
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
Additional Information Proceedings of 5th the International Conference on Operations Research and Enterprise Systems, pages 388-395. ISBN 9789897581717, DOI: 10.5220/0005758303880395

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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