Constrained Portfolio Optimisation: The State-of-the-Art Markowitz Models

Yan Jin, Rong Qu, Jason Atkin

Abstract

This paper studies the state-of-art constrained portfolio optimization 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.

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Paper Citation


in Harvard Style

Jin Y., Qu R. and Atkin J. (2016). Constrained Portfolio Optimisation: The State-of-the-Art Markowitz Models . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 388-395. DOI: 10.5220/0005758303880395


in Bibtex Style

@conference{icores16,
author={Yan Jin and Rong Qu and Jason Atkin},
title={Constrained Portfolio Optimisation: The State-of-the-Art Markowitz Models},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2016},
pages={388-395},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005758303880395},
isbn={978-989-758-171-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Constrained Portfolio Optimisation: The State-of-the-Art Markowitz Models
SN - 978-989-758-171-7
AU - Jin Y.
AU - Qu R.
AU - Atkin J.
PY - 2016
SP - 388
EP - 395
DO - 10.5220/0005758303880395