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Genetic Algorithms and Genetic Programming in Computational Finance: An Overview of the Book

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Genetic Algorithms and Genetic Programming in Computational Finance

Abstract

This chapter reviews some recent advancements in financial applications of genetic algorithms and genetic programming. We start with the more familiar applications, such as forecasting, trading, and portfolio management. We then trace the recent extensions to cash flow management, option pricing, volatility forecasting, and arbitrage. The direction then turns to agent-based computational finance, a bottom-up approach to the study of financial markets. The review also sheds light on a few technical aspects of GAs and GP, which may play a vital role in financial applications.

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Authors and Affiliations

  1. AI-ECON Research Center, Department of Economics, National Chengchi University, Taipei, Taiwan, 11623

    Shu-Heng Chen

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  1. Shu-Heng Chen
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Editors and Affiliations

  1. Department of Economics, National Chengchi University, Taiwan

    Shu-Heng Chen

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© 2002 Springer Science+Business Media New York

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Chen, SH. (2002). Genetic Algorithms and Genetic Programming in Computational Finance: An Overview of the Book. In: Chen, SH. (eds) Genetic Algorithms and Genetic Programming in Computational Finance. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0835-9_1

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  • DOI: https://doi.org/10.1007/978-1-4615-0835-9_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-5262-4

  • Online ISBN: 978-1-4615-0835-9

  • eBook Packages: Springer Book Archive

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