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A hybrid approach based on neural networks and genetic algorithms to the study of profitability in the Spanish Stock Market


  • Mariano Matilla-Garcia
  • Carlos Arguello


This paper studies predictability and profitability of using neural networks (NN) in the Spanish security market. This is carried out through a hybrid approximation which entails evolving a genetic algorithm in order to obtain an optimal NN's architecture. To that end, (NNs) forecasts are transformed into a simple trading strategy, whose profitability is evaluated against a simple buy-and-hold strategy.

Suggested Citation

  • Mariano Matilla-Garcia & Carlos Arguello, 2005. "A hybrid approach based on neural networks and genetic algorithms to the study of profitability in the Spanish Stock Market," Applied Economics Letters, Taylor & Francis Journals, vol. 12(5), pages 303-308.
  • Handle: RePEc:taf:apeclt:v:12:y:2005:i:5:p:303-308 DOI: 10.1080/1350485042000329103

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    References listed on IDEAS

    1. Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    2. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
    3. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
    4. Gencay Ramazan & Stengos Thanasis, 1997. "Technical Trading Rules and the Size of the Risk Premium in Security Returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(2), pages 1-14, July.
    5. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    6. Fernandez-Rodriguez, Fernando & Gonzalez-Martel, Christian & Sosvilla-Rivero, Simon, 2000. "On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market," Economics Letters, Elsevier, vol. 69(1), pages 89-94, October.
    7. McAdam, Peter & McNelis, Paul, 2005. "Forecasting inflation with thick models and neural networks," Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September.
    8. 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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