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The Dow Theory: William Peter Hamilton's Track Record Re-Considered

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Listed:
  • Stephen Brown
  • William Goetzmann
  • Alok Kumar

Abstract

Alfred Cowles' (1934) test of the Dow Theory apparently provided strong evidence against the ability of Wall Street's most famous chartist to forecast the stock market. In this paper, we review Cowles' evidence and find that it supports the contrary conclusion -- that the Dow Theory, as applied by its major practitioner, William Peter Hamilton over the period 1902 to 1929, yielde

Suggested Citation

  • Stephen Brown & William Goetzmann & Alok Kumar, 1998. "The Dow Theory: William Peter Hamilton's Track Record Re-Considered," Yale School of Management Working Papers ysm85, Yale School of Management, revised 01 Apr 2008.
  • Handle: RePEc:ysm:somwrk:ysm85
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    File URL: http://icfpub.som.yale.edu/publications/2439
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    References listed on IDEAS

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    1. 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(4), pages 405-426, December.
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    3. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    4. 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.
    5. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-337, July.
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    Cited by:

    1. K. J. Hong & S. Satchell, 2015. "Time series momentum trading strategy and autocorrelation amplification," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1471-1487, September.
    2. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    3. Neely, Christopher J., 2003. "Risk-adjusted, ex ante, optimal technical trading rules in equity markets," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 69-87.
    4. Pereira, Robert, 1999. "Forecasting Ability But No Profitability: An Empirical Evaluation of Genetic Algorithm-optimised Technical Trading Rules," MPRA Paper 9055, University Library of Munich, Germany.
    5. Pu Shen, 2002. "Market timing strategies that worked," Research Working Paper RWP 02-01, Federal Reserve Bank of Kansas City, revised 2002.
    6. repec:rbs:ijfbss:v:5:y:2016:i:3:p:85-102 is not listed on IDEAS
    7. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    8. Eero Pätäri & Mika Vilska, 2014. "Performance of moving average trading strategies over varying stock market conditions: the Finnish evidence," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2851-2872, August.
    9. Michael Cooper & Huseyin Gulen, 2006. "Is Time-Series-Based Predictability Evident in Real Time?," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1263-1292, May.
    10. Pierre Giot & Mikael Petitjean, 2009. "Short-term market timing using the bond-equity yield ratio," The European Journal of Finance, Taylor & Francis Journals, vol. 15(4), pages 365-384.
    11. Esteban Pérez Caldentey & Matías Vernengo, 2010. "Modern Finance, Methodology and the Global Crisis," Working Paper Series, Department of Economics, University of Utah 2010_04, University of Utah, Department of Economics.
    12. K. J. Hong & S. Satchell, 2013. "Time Series Momentum Trading Strategy and Autocorrelation Amplification," Cambridge Working Papers in Economics 1322, Faculty of Economics, University of Cambridge.
    13. GIOT, Pierre & PETITJEAN, Mikael, 2006. "International stock return predictability: statistical evidence and economic significance," CORE Discussion Papers 2006088, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. 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.
    15. Po-Hsuan Hsu & Chung-Ming Kuan, 2004. "Re-Examining the Profitability of Technical Analysis with White’s Reality Check," IEAS Working Paper : academic research 04-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    16. Suzuki, Tomoya & Ohkura, Yuushi, 2016. "Financial technical indicator based on chaotic bagging predictors for adaptive stock selection in Japanese and American markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 50-66.
    17. Li, Wei & Lam, Kin, 2002. "Optimal market timing strategies under transaction costs," Omega, Elsevier, vol. 30(2), pages 97-108, April.
    18. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    19. Woodward, George & Marisetty, Vijaya B., 2005. "Introducing non-linear dynamics to the two-regime market model: Evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 559-581, September.
    20. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    21. Gerritsen, Dirk F., 2016. "Are chartists artists? The determinants and profitability of recommendations based on technical analysis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 179-196.
    22. Alessandro Beber, 1999. "Il dibattito su dignità ed efficacia dell'analisi tecnica nell'economia finanziaria," Alea Tech Reports 003, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.

    More about this item

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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