research-article

Learning to optimize profits beats predicting returns -: comparing techniques for financial portfolio optimisation

Authors:

Martin V. Sewell,

Christopher D. ClackAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 1681 - 1688

https://doi.org/10.1145/1389095.1389409

Published: 12 July 2008 Publication History

Abstract

Stock selection for hedge fund portfolios is a challenging problem that has previously been tackled by many machine-learning, genetic and evolutionary systems, including both Genetic Programming (GP) and Support Vector Machines (SVM). But which is the better? We provide a head-to-head evaluation of GP and SVM applied to this real-world problem, including both a standard comparison of returns on investment and a comparison of both techniques when extended with a "voting" mechanism designed to improve both returns and robustness to volatile markets. Robustness is an important additional dimension to this comparison, since the markets (the environment in which the GP or SVM solution must survive) are dynamic and unpredictable.

Our investigation highlights a key difference in the two techniques, showing the superiority of the GP approach for this problem.

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Cited By

Byrum J(2022)AI in Financial Portfolio Management: Practical Considerations and Use CasesInnovative Technology at the Interface of Finance and Operations10.1007/978-3-030-75729-8_9(249-270)Online publication date: 1-Jan-2022
https://doi.org/10.1007/978-3-030-75729-8_9
Tong GNg KYap WKhor K(2021)Construction of Optimal Stock Market Portfolios Using Outlier Detection AlgorithmSoft Computing in Data Science10.1007/978-981-16-7334-4_12(160-173)Online publication date: 26-Oct-2021
https://doi.org/10.1007/978-981-16-7334-4_12
Ramezanian RPeymanfar AEbrahimi S(2019)An integrated framework of genetic network programming and multi-layer perceptron neural network for prediction of daily stock return: An application in Tehran stock exchange marketApplied Soft Computing10.1016/j.asoc.2019.105551(105551)Online publication date: Jun-2019
https://doi.org/10.1016/j.asoc.2019.105551
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Index Terms

Learning to optimize profits beats predicting returns -: comparing techniques for financial portfolio optimisation
1. Computing methodologies
  1. Artificial intelligence

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cover image ACM Conferences

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Copyright © 2008 ACM.

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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Publication History

Published: 12 July 2008

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GECCO08

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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

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Cited By

Byrum J(2022)AI in Financial Portfolio Management: Practical Considerations and Use CasesInnovative Technology at the Interface of Finance and Operations10.1007/978-3-030-75729-8_9(249-270)Online publication date: 1-Jan-2022
https://doi.org/10.1007/978-3-030-75729-8_9
Tong GNg KYap WKhor K(2021)Construction of Optimal Stock Market Portfolios Using Outlier Detection AlgorithmSoft Computing in Data Science10.1007/978-981-16-7334-4_12(160-173)Online publication date: 26-Oct-2021
https://doi.org/10.1007/978-981-16-7334-4_12
Ramezanian RPeymanfar AEbrahimi S(2019)An integrated framework of genetic network programming and multi-layer perceptron neural network for prediction of daily stock return: An application in Tehran stock exchange marketApplied Soft Computing10.1016/j.asoc.2019.105551(105551)Online publication date: Jun-2019
https://doi.org/10.1016/j.asoc.2019.105551
Viveros-Jiménez FLeón-Borges JCruz-Cortés N(2012)A simple adaptive algorithm for numerical optimizationProceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II10.1007/978-3-642-37798-3_11(115-126)Online publication date: 27-Oct-2012
https://dl.acm.org/doi/10.1007/978-3-642-37798-3_11
Gorgulho ANeves RHorta NGorgulho ANeves RHorta N(2012)Related WorkIntelligent Financial Portfolio Composition based on Evolutionary Computation Strategies10.1007/978-3-642-32989-0_2(5-30)Online publication date: 27-Sep-2012
https://doi.org/10.1007/978-3-642-32989-0_2
Das PBanerjee AApte CGhosh JSmyth P(2011)Meta optimization and its application to portfolio selectionProceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/2020408.2020588(1163-1171)Online publication date: 21-Aug-2011
https://dl.acm.org/doi/10.1145/2020408.2020588
Wilson GBanzhaf W(2010)Interday and Intraday Stock Trading Using Probabilistic Adaptive Mapping Developmental Genetic Programming and Linear Genetic ProgrammingNatural Computing in Computational Finance10.1007/978-3-642-13950-5_11(191-212)Online publication date: 2010
https://doi.org/10.1007/978-3-642-13950-5_11
Gorgulho ANeves RHorta NRothlauf F(2009)Using GAs to balance technical indicators on stock picking for financial portfolio compositionProceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers10.1145/1570256.1570273(2041-2046)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1570256.1570273
Wilson GBanzhaf WRothlauf F(2009)Soft memory for stock market analysis using linear and developmental genetic programmingProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1570119(1633-1640)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1570119
Aranha CIba H(2009)The Memetic Tree-based Genetic Algorithm and its application to Portfolio OptimizationMemetic Computing10.1007/s12293-009-0010-21:2(139-151)Online publication date: 25-Apr-2009
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