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Optimisation of Technical Rules by Genetic Algorithms: Evidence from the Madrid Stock Market

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  • Fernando Fernández-Rodríguez
  • Christian González-Martel
  • Simón Sosvilla-Rivero

Abstract

This paper investigates the profitability of a simple and very common technical trading rule applied to the General Index of the Madrid Stock Market. The optimal trading rule parameter values are found using a genetic algorithm. The results suggest that, for reasonable trading costs, the technical trading rule is always superior to a risk-adjusted buy-and-hold strategy.

Suggested Citation

  • Fernando Fernández-Rodríguez & Christian González-Martel & Simón Sosvilla-Rivero, "undated". "Optimisation of Technical Rules by Genetic Algorithms: Evidence from the Madrid Stock Market," Working Papers 2001-14, FEDEA.
  • Handle: RePEc:fda:fdaddt:2001-14
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    References listed on IDEAS

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    1. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical analysis in the Madrid stock exchange," Working Papers 99-05, FEDEA.
    2. Bessembinder, Hendrik & Chan, Kalok, 1995. "The profitability of technical trading rules in the Asian stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 3(2-3), pages 257-284, July.
    3. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
    4. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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    Cited by:

    1. Kaucic, Massimiliano, 2010. "Investment using evolutionary learning methods and technical rules," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1717-1727, December.
    2. Stephan Schulmeister, 2007. "The Interaction Between the Aggregate Behaviour of Technical Trading Systems and Stock Price Dynamics," WIFO Working Papers 290, WIFO.

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