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On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market

  • Fernandez-Rodriguez, Fernando
  • Gonzalez-Martel, Christian
  • Sosvilla-Rivero, Simon

In this paper we investigate the profitability of a simple technical trading rule based on Artificial Neural Networks (ANNs). Our results, based on applying this investment strategy to the General Index of the Madrid Stock Market, suggest that, in absence of trading costs, the technical trading rule is always superior to a buy-and-hold strategy for both "bear" market and "stable" market episodes. On the other hand, we find that the buy-and-hold strategy generates higher returns than the trading rule based on ANN only for a "bull" market subperiod.

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File URL: http://www.sciencedirect.com/science/article/B6V84-412RYMV-D/2/23eba06fa72c8dadf1b65b87824e93f6
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Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 69 (2000)
Issue (Month): 1 (October)
Pages: 89-94

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Handle: RePEc:eee:ecolet:v:69:y:2000:i:1:p:89-94
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  1. LeBaron, B., 1992. "Do Moving Average Trading Rule Results Imply Nonlinearites in Foreign Exchange Markets?," Working papers 9222, Wisconsin Madison - Social Systems.
  2. LeBaron, B., 1996. "Technical Trading Rule Profitability and Foreing Exchange Intervention," Working papers 9445r, Wisconsin Madison - Social Systems.
  3. Pesaran, M.H. & Timmermann, A., 1990. "A Simple, Non-Parametric Test Of Predictive Performance," Cambridge Working Papers in Economics 9021, Faculty of Economics, University of Cambridge.
  4. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
  5. Gencay, R & Stengos, T, 1996. "Technical Trading Rules and the Size of the Risk Premium in Security Returns," Working Papers 1996-11, University of Guelph, Department of Economics and Finance.
  6. Brock, W. & Lakonishok, J. & Lebaron, B., 1991. "Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns," Working papers 90-22, Wisconsin Madison - Social Systems.
  7. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero & Maria Dolores Garcia-Artiles, 1997. "Using nearest neighbour predictors to forecast the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 21(1), pages 75-91, January.
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