IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v33y2009i6p1089-1100.html
   My bibliography  Save this article

Price trends and patterns in technical analysis: A theoretical and empirical examination

Author

Listed:
  • Friesen, Geoffrey C.
  • Weller, Paul A.
  • Dunham, Lee M.

Abstract

While many technical trading rules are based upon patterns in asset prices, we lack convincing explanations of how and why these patterns arise, and why trading rules based on technical analysis are profitable. This paper provides a model that explains the success of certain trading rules that are based on patterns in past prices. We point to the importance of confirmation bias, which has been shown to play a key role in other types of decision making. Traders who acquire information and trade on the basis of that information tend to bias their interpretation of subsequent information in the direction of their original view. This produces autocorrelations and patterns of price movement that can predict future prices, such as the "head-and-shoulders" and "double-top" patterns. The model also predicts that sequential price jumps for a particular stock will be positively autocorrelated. We test this prediction and find that jumps exhibit statistically and economically significant positive autocorrelations.

Suggested Citation

  • Friesen, Geoffrey C. & Weller, Paul A. & Dunham, Lee M., 2009. "Price trends and patterns in technical analysis: A theoretical and empirical examination," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1089-1100, June.
  • Handle: RePEc:eee:jbfina:v:33:y:2009:i:6:p:1089-1100
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378-4266(08)00295-1
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sweeney, Richard J, 1986. " Beating the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 41(1), pages 163-182, March.
    2. Chang, P H Kevin & Osler, Carol L, 1999. "Methodical Madness: Technical Analysis and the Irrationality of Exchange-Rate Forecasts," Economic Journal, Royal Economic Society, vol. 109(458), pages 636-661, October.
    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. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    5. Cooper, Michael, 1999. "Filter Rules Based on Price and Volume in Individual Security Overreaction," Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 901-935.
    6. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    7. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(04), pages 405-426, December.
    8. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, August.
    9. Ippolito, Richard A, 1992. "Consumer Reaction to Measures of Poor Quality: Evidence from the Mutual Fund Industry," Journal of Law and Economics, University of Chicago Press, vol. 35(1), pages 45-70, April.
    10. Kenneth A. Kavajecz, 2004. "Technical Analysis and Liquidity Provision," Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 1043-1071.
    11. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    12. Conrad, Jennifer & Kaul, Gautam & Nimalendran, M., 1991. "Components of short-horizon individual security returns," Journal of Financial Economics, Elsevier, vol. 29(2), pages 365-384, October.
    13. William N. Goetzmann & Nadav Peles, 1997. "Cognitive Dissonance And Mutual Fund Investors," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 20(2), pages 145-158, June.
    14. De Bondt, Werner F M & Thaler, Richard, 1985. " Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    15. Bruce N. Lehmann, 1990. "Fads, Martingales, and Market Efficiency," The Quarterly Journal of Economics, Oxford University Press, vol. 105(1), pages 1-28.
    16. Roberto C. Gutierrez & Eric K. Kelley, 2008. "The Long-Lasting Momentum in Weekly Returns," Journal of Finance, American Finance Association, vol. 63(1), pages 415-447, February.
    17. Avanidhar Subrahmanyam, 2005. "Distinguishing Between Rationales for Short-Horizon Predictability of Stock Returns," The Financial Review, Eastern Finance Association, vol. 40(1), pages 11-35, February.
    18. 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.
    19. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    20. Jonathan Lewellen & Jay Shanken, 2002. "Learning, Asset-Pricing Tests, and Market Efficiency," Journal of Finance, American Finance Association, vol. 57(3), pages 1113-1145, June.
    21. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    22. Chopra, Navin & Lakonishok, Josef & Ritter, Jay R., 1992. "Measuring abnormal performance : Do stocks overreact?," Journal of Financial Economics, Elsevier, vol. 31(2), pages 235-268, April.
    23. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    24. Chuang, Wen-I & Lee, Bong-Soo, 2006. "An empirical evaluation of the overconfidence hypothesis," Journal of Banking & Finance, Elsevier, vol. 30(9), pages 2489-2515, September.
    25. Thomas J. George & Chuan-Yang Hwang, 2007. "Long-Term Return Reversals: Overreaction or Taxes?," Journal of Finance, American Finance Association, vol. 62(6), pages 2865-2896, December.
    26. Lui, Yu-Hon & Mole, David, 1998. "The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 535-545, June.
    27. Edward R Dawson & James M. Steeley, 2003. "On the Existence of Visual Technical Patterns in the UK Stock Market," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(1-2), pages 263-293.
    28. Jegadeesh, Narasimhan, 1990. " Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    29. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    30. Carol L. Osler, 2003. "Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis," Journal of Finance, American Finance Association, vol. 58(5), pages 1791-1820, October.
    31. Marshall, Ben R. & Young, Martin R. & Rose, Lawrence C., 2006. "Candlestick technical trading strategies: Can they create value for investors?," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2303-2323, August.
    32. Jegadeesh, Narasimhan & Titman, Sheridan, 1995. "Overreaction, Delayed Reaction, and Contrarian Profits," Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 973-993.
    33. Tauchen, George & Zhou, Hao, 2011. "Realized jumps on financial markets and predicting credit spreads," Journal of Econometrics, Elsevier, vol. 160(1), pages 102-118, January.
    34. 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.
    35. Marshall, Ben R. & Cahan, Rochester H. & Cahan, Jared M., 2008. "Does intraday technical analysis in the U.S. equity market have value?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 199-210, March.
    36. Alon Brav & J.B. Heaton, 2002. "Competing Theories of Financial Anomalies," Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 575-606, March.
    37. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. " Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    38. 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.
    39. Bruce N. Lehmann, 1988. "Fads, Martingales, and Market Efficiency," NBER Working Papers 2533, National Bureau of Economic Research, Inc.
    40. Bates, David S., 2003. "Empirical option pricing: a retrospection," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 387-404.
    41. Friesen, Geoffrey & Weller, Paul A., 2006. "Quantifying cognitive biases in analyst earnings forecasts," Journal of Financial Markets, Elsevier, vol. 9(4), pages 333-365, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Serban, Alina F., 2010. "Combining mean reversion and momentum trading strategies in foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2720-2727, November.
    2. repec:wsi:rpbfmp:v:20:y:2017:i:02:n:s0219091517500102 is not listed on IDEAS
    3. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    4. Papailias, Fotis & Thomakos, Dimitrios D., 2015. "An improved moving average technical trading rule," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 458-469.
    5. repec:eee:quaeco:v:66:y:2017:i:c:p:115-126 is not listed on IDEAS
    6. Metghalchi, Massoud & Chen, Chien-Ping & Hayes, Linda A., 2015. "History of share prices and market efficiency of the Madrid general stock index," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 178-184.
    7. Clare, Andrew & Seaton, James & Smith, Peter N. & Thomas, Stephen, 2016. "The trend is our friend: Risk parity, momentum and trend following in global asset allocation," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 63-80.
    8. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
    9. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.
    10. Huang, Weihong & Zheng, Huanhuan, 2012. "Financial crises and regime-dependent dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 445-461.
    11. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 015-031, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:33:y:2009:i:6:p:1089-1100. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jbf .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.