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Co-Evolutionary Multi-Agent System for Portfolio Optimization

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Natural Computing in Computational Finance

Part of the book series: Studies in Computational Intelligence ((SCI,volume 100))

Summary

Co-evolutionary techniques for evolutionary algorithms can enhance the adaptive capabilities of evolutionary algorithms and help maintain population diversity. In this chapter the concept and a formal model of an agent-based realization of a predator-prey coevolutionary algorithm is presented. The resulting system is applied to the problem of effective portfolio building and is compared to classical multi-objective evolutionary algorithms.

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Author information

Authors and Affiliations

  1. Department of Computer Science, AGH University of Science and Technology, Kraków, Poland

    Rafał Dreżewski & Leszek Siwik

Authors
  1. Rafał Dreżewski
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  2. Leszek Siwik
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Editors and Affiliations

  1. School of Business Quinn School, University College Dublin, Belfield, Dublin 4, Ireland

    Anthony Brabazon (Head of Research) (Head of Research)

  2. Natural Computing Research and Applications School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland

    Michael O’Neill (Director) (Director)

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Dreżewski, R., Siwik, L. (2008). Co-Evolutionary Multi-Agent System for Portfolio Optimization. In: Brabazon, A., O’Neill, M. (eds) Natural Computing in Computational Finance. Studies in Computational Intelligence, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77477-8_15

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  • DOI: https://doi.org/10.1007/978-3-540-77477-8_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77476-1

  • Online ISBN: 978-3-540-77477-8

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