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Re-Examining the Profitability of Technical Analysis with White’s Reality Check

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Abstract

In this paper, we re-examine the profitability of technical analysis using the Reality Check of White (2000, Econometrica) that corrects the data snooping bias. Comparing to previous studies, we study a more complete “universe” of trading techniques, including not only simple trading rules but also investor’s strategies, and we test the profitability of these rules and strategies with four main indices from both relatively mature and young markets. It is found that profitable simple rules and investor’s strategies do exist with statistical significance for NASDAQ Composite and Russell 2000 but not for DJIA and S&P 500. Moreover, the best rules for NASDAQ Composite and Russell 2000 outperform the buy-and-hold strategy in most in- and out-of-sample periods, even when transaction costs are taken into account. We also find that investor’s strategies are able to improve on the profits of simple rules and may even generate significant profits from unprofitable simple rules.

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Bibliographic Info

Paper provided by Institute of Economics, Academia Sinica, Taipei, Taiwan in its series IEAS Working Paper : academic research with number 04-A003.

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Length: 26 pages
Date of creation: Feb 2004
Date of revision:
Handle: RePEc:sin:wpaper:04-a003

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Keywords: data snooping; investor’s strategies; stationary bootstrap; technical analysis; trading rules; White’s Reality Check.;

References

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  1. Stephen Brown & William Goetzmann & Alok Kumar, 1998. "The Dow Theory: William Peter Hamilton's Track Record Re-Considered," Yale School of Management Working Papers, Yale School of Management ysm85, Yale School of Management, revised 01 Apr 2008.
  2. Knez, Peter J & Ready, Mark J, 1996. "Estimating the Profits from Trading Strategies," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 9(4), pages 1121-63.
  3. Allan Timmermann & Halbert White & Ryan Sullivan, 1998. "Data-Snooping, Technical Trading, Rule Performance and the Bootstrap," FMG Discussion Papers, Financial Markets Group dp303, Financial Markets Group.
  4. Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, American Finance Association, vol. 25(2), pages 469-82, May.
  5. Josef Lakonishok & Robert W. Vishny & Andrei Shleifer, 1993. "Contrarian Investment, Extrapolation, and Risk," NBER Working Papers 4360, National Bureau of Economic Research, Inc.
  6. Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, Elsevier, vol. 5(4), pages 347-359, October.
  7. Christopher Neely & Paul Weller, 1998. "Technical trading rules in the European Monetary System," Working Papers, Federal Reserve Bank of St. Louis 1997-015, Federal Reserve Bank of St. Louis.
  8. K. Geert Rouwenhorst, 1998. "International Momentum Strategies," Journal of Finance, American Finance Association, American Finance Association, vol. 53(1), pages 267-284, 02.
  9. Chan, Louis K. C. & Karceski, Jason & Lakonishok, Josef, 1998. "The Risk and Return from Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, Cambridge University Press, vol. 33(02), pages 159-188, June.
  10. Mark J Ready, 2002. "Profits from Technical Trading Rules," Financial Management, Financial Management Association, Financial Management Association, vol. 31(3), Fall.
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Cited by:
  1. Pereira, Pedro Luiz Valls, 2009. "Predictability of equity models," Textos para discussão 176, Escola de Economia de São Paulo, Getulio Vargas Foundation (Brazil).

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