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The predictive power of price patterns

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  • G. Caginalp
  • H. Laurent
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    Abstract

    Using two sets of data, including daily prices (open, close, high and low) of all S&P 500 stocks between 1992 and 1996, we perform a satistical test of the predictive capability of candlestick patterns. Out-of-sample tests indicate statistical significance at the level of 36 standard deviations from the null hypothesis, and indicate a profit of almost 1% during a two-day holding period. An essentially non-parametric test utilizes standard definitions of three-day candlestick patterns and removes conditions on magnitudes. The results provide evidence that traders are influenced by price behaviour. To the best of our knowledge, this is the first scientific test to provide strong evidence in favour of any trading rule or pattern on a large unrestricted scale.

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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Mathematical Finance.

    Volume (Year): 5 (1998)
    Issue (Month): 3-4 ()
    Pages: 181-205

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    Handle: RePEc:taf:apmtfi:v:5:y:1998:i:3-4:p:181-205

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    Web page: http://www.tandfonline.com/RAMF20

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    Related research

    Keywords: Candlestick Patterns; Statistical Price Prediction; Price Pattern; Technical Analysis;

    References

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    1. T. Randolph Beard & Richard O. Beil, 1994. "Do People Rely on the Self-Interested Maximization of Others? An Experimental Test," Management Science, INFORMS, vol. 40(2), pages 252-262, February.
    2. Robert J. Shiller, 1980. "The Use of Volatility Measures in Assessing Market Efficiency," NBER Working Papers 0565, National Bureau of Economic Research, Inc.
    3. Rosenthal, Robert W., 1981. "Games of perfect information, predatory pricing and the chain-store paradox," Journal of Economic Theory, Elsevier, vol. 25(1), pages 92-100, August.
    4. Andrew W. Lo & A. Craig MacKinlay, 1987. "Stock Market Prices Do Not Follow Random Walks: Evidence From a Simple Specification Test," NBER Working Papers 2168, National Bureau of Economic Research, Inc.
    5. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. " Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-81, March.
    6. David Porter & Vernon Smith, 1994. "Stock market bubbles in the laboratory," Applied Mathematical Finance, Taylor & Francis Journals, vol. 1(2), pages 111-128.
    7. 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.
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