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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2001: Applications of Evolutionary Computing pp 343–352Cite as

Evolving Market Index Trading Rules Using Grammatical Evolution

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2037))

Abstract

This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical trading rules for the UK FTSE 100 stock index. Index values for the period 26/4/1984 to 4/12/1997 are used to train and test the model. The preliminary findings indicate that the methodology has much potential, outperforming the benchmark strategy adopted.

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Author information

Authors and Affiliations

  1. Dept. Of Accountancy, University College Dublin, Ireland

    Anthony Brabazon

  2. Dept. Of Computer Science And Information Systems, University of Limerick, Ireland

    Michael O’Neill, Conor Ryan & J. J. Collins

Authors
  1. Michael O’Neill
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  2. Anthony Brabazon
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  3. Conor Ryan
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  4. J. J. Collins
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Editor information

Editors and Affiliations

  1. Leiden University, Niels Bohrweg1, 2333, CA, Leiden, The Netherlands

    Egbert J. W. Boers

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© 2001 Springer-Verlag Berlin Heidelberg

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O’Neill, M., Brabazon, A., Ryan, C., Collins, J.J. (2001). Evolving Market Index Trading Rules Using Grammatical Evolution. In: Boers, E.J.W. (eds) Applications of Evolutionary Computing. EvoWorkshops 2001. Lecture Notes in Computer Science, vol 2037. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45365-2_36

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  • DOI: https://doi.org/10.1007/3-540-45365-2_36

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41920-4

  • Online ISBN: 978-3-540-45365-9

  • eBook Packages: Springer Book Archive

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