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Efficient frontiers in portfolio optimisation with minimum proportion constraints

Published: 13 July 2019 Publication History

Abstract

This work chronicles research into the solution of portfolio problems with metaheuristic solvers. In particular, a genetic algorithm for solving the cardinality constrained portfolio optimisation problem with minimum asset proportions is presented and tested on the datasets of [1]. These datasets form benchmark instances used to test portfolio optimisers and are based upon indices ranging from 31 to 225 assets. The results of the GA are indicatively compared to solutions of [2] for a variety of minimum proportions, suggesting that solutions exhibit certain clustering characteristics for higher proportions. Further work is also discussed. This research is based upon the first part of the ongoing PhD thesis of the first author.

References

[1]
John E Beasley. 2000. OR-Library. http://people.brunel.ac.uk/~mastjjb/jeb/orlib/portinfo.html.
[2]
Francesco Cesarone, Andrea Scozzari, and Fabio Tardella. 2009. Efficient Algorithms for Mean-Variance Portfolio Optimization With Hard Real-World Constraints. Giornale dell'Istituto Italiano degli Attuari 72, 37--56.
[3]
T-J Chang, Nigel Meade, John E Beasley, and Yazid M Sharaiha. 2000. Heuristics for Cardinality Constrained Portfolio Optimisation. Computers & Operations Research 27, 13, 1271--1302.
[4]
Matthew J Craven and David I Graham. 2017. Exploring the Efficient) Frontiers of Portfolio Optimization. In Proceedings of the Genetic and Evolutionary Computation Conference Companion. ACM, 19--20.
[5]
Iakovos Kakouris and Berç Rustem. 2014. Robust portfolio optimization with copulas. European Journal of Operational Research 235, 1, 28--37.
[6]
Khin Lwin, Rong Qu, and Graham Kendall. 2014. A Learning-Guided Multi-Objective Evolutionary Algorithm for Constrained Portfolio Optimization. Applied Soft Computing 24, 757--772.
[7]
Renata Mansini and Maria Grazia Speranza. 1999. Heuristic Algorithms for the Portfolio Selection Problem with Minimum Transaction Lots. European Journal of Operational Research 114, 2, 219--233.
[8]
Harry Markowitz. 1952. Portfolio Selection. The Journal of Finance 7, 1, 77--91.

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cover image ACM Conferences
GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
July 2019
2161 pages
ISBN:9781450367486
DOI:10.1145/3319619
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 July 2019

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Author Tags

  1. cardinality constraint
  2. copula
  3. efficient frontier
  4. genetic algorithm
  5. minimum proportion

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  • Research-article

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GECCO '19
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GECCO '19: Genetic and Evolutionary Computation Conference
July 13 - 17, 2019
Prague, Czech Republic

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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