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Further Insights on the Puzzle of Technical Analysis Profitability

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  • Bertrand Maillet

    (TEAM - Théories et Applications en Microéconomie et Macroéconomie - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Thierry Michel

Abstract

This paper extends current results concerning technical analysis efficiency on the foreign exchange market and attempts to determine whether filtering the raw exchange rate series with some trading rule significantly changes its characteristics. Because of the non-normality of exchange rate series, bootstrap methods are used on the main daily exchange rates since 1974 to show technical analysis performance. The technical analysis strategy tested generates returns whose distribution is significantly different from the basic series. The robustness of the results is tested in and out-of-sample and an explanation of the technical analysis performance based on its filtering properties is suggested.
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Suggested Citation

  • Bertrand Maillet & Thierry Michel, 2000. "Further Insights on the Puzzle of Technical Analysis Profitability," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00308986, HAL.
    • Handle: RePEc:hal:cesptp:hal-00308986
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    Cited by:

    1. Stefanescu, Răzvan & Dumitriu, Ramona, 2015. "Buy and sell signals on Bucharest Stock Exchange," MPRA Paper 89014, University Library of Munich, Germany, revised 05 Jan 2016.
    2. Schulmeister, Stephan, 2006. "The interaction between technical currency trading and exchange rate fluctuations," Finance Research Letters, Elsevier, vol. 3(3), pages 212-233, September.
    3. Schulmeister, Stephan, 2009. "Profitability of technical stock trading: Has it moved from daily to intraday data?," Review of Financial Economics, Elsevier, vol. 18(4), pages 190-201, October.
    4. Neely, Christopher J. & Weller, Paul A. & Ulrich, Joshua M., 2009. "The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(2), pages 467-488, April.
    5. Todea, Alexandru & Zoicas Ienciu, Adrian, 2011. "Technical Analysis and Stochastic Properties of Exchange Rate Movements: Empirical Evidence from the Romanian Currency Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 175-192, March.
    6. Bertrand Maillet & Thierry Michel, 2005. "Technical analysis profitability when exchange rates are pegged: A note," The European Journal of Finance, Taylor & Francis Journals, vol. 11(6), pages 463-470.
    7. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    8. Enoch Cheng & Clemens C. Struck, 2019. "Time-Series Momentum: A Monte-Carlo Approach," Working Papers 201906, School of Economics, University College Dublin.
    9. Stephan Schulmeister, 2007. "The Interaction Between the Aggregate Behaviour of Technical Trading Systems and Stock Price Dynamics," WIFO Working Papers 290, WIFO.
    10. Stephan Schulmeister, 2009. "Technical Trading and Trends in the Dollar-Euro Exchange Rate," WIFO Studies, WIFO, number 37582, April.
    11. Afiruddin Tapa* & Mohd Hasimi Yaacob & Ahmad Husni Hamzah & Yean Soh Chuen, 2018. "Trading Performance Analysis: A Comparisons Between the Original MA Crossover and Modified MA Crossover Strategy," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 933-941:6.
    12. Stephan Schulmeister, 2007. "Performance of Technical Trading Systems in the Yen/Dollar Market," WIFO Working Papers 291, WIFO.
    13. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.

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