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Applying genetic algorithms to Wall Street

Author

Listed:
  • Laura Nunez-Letamendia
  • Joaquin Pacheco
  • Silvia Casado

Abstract

Genetic algorithms (GAs) can be applied to a wide range of problems in the field of finance. The purpose of this paper is to make GAs accessible to practitioners, academicians and students who are interested in financial markets. By describing a simple application consisting in tuning a technical trading system for the Dow Jones we illustrate step by step how the reader can implement its own trading system with the help of the powerful tool, the GA. To show how this technique can easily be extended to other type of applications in the financial domain, some examples are brought up at the end of the paper.

Suggested Citation

  • Laura Nunez-Letamendia & Joaquin Pacheco & Silvia Casado, 2011. "Applying genetic algorithms to Wall Street," International Journal of Data Mining, Modelling and Management, Inderscience Enterprises Ltd, vol. 3(4), pages 319-340.
    • Handle: RePEc:ids:ijdmmm:v:3:y:2011:i:4:p:319-340
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    Cited by:

    1. Manolis Maragoudakis & Dimitrios Serpanos, 2016. "Exploiting Financial News and Social Media Opinions for Stock Market Analysis using MCMC Bayesian Inference," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 589-622, April.

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