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Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability

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  • Isakov, Dusan
  • Marti, Didier

Abstract

This paper extends the literature on the profitability of technical analysis in three directions. First, we investigate the performance of complex trading rules based on moving averages computed over longer periods than those usually considered. Different trading rules are simulated on daily prices of the Standard & Poor’s 500 index and we find that trading rules are more profitable when signals are generated over long horizons. Second, we analyse whether financial leverage can improve the profitability of different strategies, which appears to be the case when leverage is achieved with debt. Third, we propose a new market timing test that assesses whether a trading strategy can generate signals corresponding to bull and bear markets. The results of this test show that complex rules produce high proportions of accurate signals.

Suggested Citation

  • Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    • Handle: RePEc:fri:fribow:fribow00421
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    File URL: http://doc.rero.ch/record/24769/files/WP_SES_421.pdf
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    References listed on IDEAS

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    1. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    2. Hudson, Robert & Dempsey, Michael & Keasey, Kevin, 1996. "A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 1121-1132, July.
    3. Blanchet-Scalliet, Christophette & Diop, Awa & Gibson, Rajna & Talay, Denis & Tanre, Etienne, 2007. "Technical analysis compared to mathematical models based methods under parameters mis-specification," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1351-1373, May.
    4. Kidd, Willis V. & Brorsen, B. Wade, 2004. "Why have the returns to technical analysis decreased?," Journal of Economics and Business, Elsevier, vol. 56(3), pages 159-176.
    5. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    6. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
    7. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    8. 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.
    9. Dueker, Michael & Neely, Christopher J., 2007. "Can Markov switching models predict excess foreign exchange returns?," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 279-296, February.
    10. Hans Dewachter & Marco Lyrio, 2005. "The economic value of technical trading rules: a nonparametric utility-based approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(1), pages 41-62.
    11. Alan Goodacre & Jacqueline Bosher & Andrew Dove, 1999. "Testing the CRISMA trading system: evidence from the UK market," Applied Financial Economics, Taylor & Francis Journals, vol. 9(5), pages 455-468.
    12. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    13. Hsu, Po-Hsuan & Hsu, Yu-Chin & Kuan, Chung-Ming, 2010. "Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 471-484, June.
    14. Po-Hsuan Hsu & Chung-Ming Kuan, 2005. "Reexamining the Profitability of Technical Analysis with Data Snooping Checks," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 606-628.
    15. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    16. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    17. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    18. Skouras, Spyros, 2001. "Financial returns and efficiency as seen by an artificial technical analyst," Journal of Economic Dynamics and Control, Elsevier, vol. 25(1-2), pages 213-244, January.
    19. Fung, William & Hsieh, David A, 2001. "The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 313-341.
    20. 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.
    21. repec:pri:cepsud:91malkiel is not listed on IDEAS
    22. Thomas Gehrig & Lukas Menkhoff, 2006. "Extended evidence on the use of technical analysis in foreign exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 327-338.
    23. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.
    24. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    25. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    26. 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.
    27. 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.
    28. Dewachter, Hans, 2001. "Can Markov switching models replicate chartist profits in the foreign exchange market?," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 25-41, February.
    29. Fong, Wai Mun & Yong, Lawrence H. M., 2005. "Chasing trends: recursive moving average trading rules and internet stocks," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 43-76, January.
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    Cited by:

    1. Osama El Ansary & Mona Atuea, 2017. "Testing the Effect of Technical Analysis Strategies on Achieving Abnormal Return: Evidence from Egyptian Stock Market," Accounting and Finance Research, Sciedu Press, vol. 6(2), pages 1-26, May.

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    More about this item

    Keywords

    Technical trading ; Moving average ; Forecasting ; Leverage ; Market timing;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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