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Dynamic Index Trading Using a Gene Regulatory Network Model

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Book cover Applications of Evolutionary Computation (EvoApplications 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8602))

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Abstract

This paper presents a realistic study of applying a gene regulatory model to financial prediction. The combined adaptation of evolutionary and developmental processes used in the model highlight its suitability to dynamic domains, and the results obtained show the potential of this approach for real-world trading.

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Author information

Authors and Affiliations

  1. Natural Computing Research and Applications Group, University College Dublin, Dublin, Ireland

    Miguel Nicolau, Michael O’Neill & Anthony Brabazon

Authors
  1. Miguel Nicolau
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  2. Michael O’Neill
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  3. Anthony Brabazon
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Corresponding author

Correspondence to Miguel Nicolau .

Editor information

Editors and Affiliations

  1. Depto. Estadística e Investigación, Universidad Politécnica de Valencia, Valencia, Spain

    Anna I. Esparcia-Alcázar

  2. University of Granada, Granada, Spain

    Antonio M. Mora

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Nicolau, M., O’Neill, M., Brabazon, A. (2014). Dynamic Index Trading Using a Gene Regulatory Network Model. In: Esparcia-Alcázar, A., Mora, A. (eds) Applications of Evolutionary Computation. EvoApplications 2014. Lecture Notes in Computer Science(), vol 8602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45523-4_21

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  • DOI: https://doi.org/10.1007/978-3-662-45523-4_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45522-7

  • Online ISBN: 978-3-662-45523-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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