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Technical analysis in the Madrid stock exchange

Author

Listed:
  • Fernando Fernández-Rodríguez
  • Simón Sosvilla-Rivero
  • Julián Andrada-Félix

Abstract

In this paper we assesss whether some simple forms of technical analysis can predict stock price movements in the Madrid Stock Exchange. To that end, we use daily data for General Index of the Madrid Stock Exchange, covering the thirty-one-year period from January 1966-October 1997. Our results provide strong support for profitability of these technical trading rules. By making use of bootstrap techniques, we show that returns obtained from these trading rules are not consistent with several null models frequently used in finance, such as AR(1). GARCH and GARCH-M.

Suggested Citation

  • Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical analysis in the Madrid stock exchange," Working Papers 99-05, FEDEA.
    • Handle: RePEc:fda:fdaddt:99-05
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    References listed on IDEAS

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    1. 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.
    2. Ignacio Olmeda & Joaquin Pérez, 1995. "Non-linear dynamics and chaos in the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 19(2), pages 217-248, May.
    3. Levich, Richard M. & Thomas, Lee III, 1993. "The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach," Journal of International Money and Finance, Elsevier, vol. 12(5), pages 451-474, October.
    4. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, vol. 64(4), pages 549-571, October.
    5. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    6. 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. 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.
    2. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    3. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
    4. Nikolaos Eriotis & Dimitrios Vasiliou & Spyros Papathanasiou, 2006. "Testing Technical Anomalies in Athens Stock Exchange (ASE)," European Research Studies Journal, European Research Studies Journal, vol. 0(3-4), pages 75-90.
    5. BEN OMRANE, Walid & VAN OPPEN, Hervé, 2004. "The predictive success and profitability of chart patterns in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2004035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Ahmad, Mashood & Ali, Syed Babar, 2008. "Technical Analysis in the Stock Markets of Pakistan: A Case of Commercial Banks," MPRA Paper 64521, University Library of Munich, Germany.

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    More about this item

    Keywords

    Stock market; Technical trading rules;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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