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

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  • Stephen J. Brown

    ()
    (NYU Stern School of Business)

  • William N. Goetzmann

    ()
    (Yale School of Management, International Center for Finance)

  • Alok Kumar

    ()
    (University of Notre Dame - Mendoza College of Business)

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, yielded positive risk-adjusted returns. A re-analysis of the Hamilton editorials suggests that his timing strategies yield high Sharpe ratios and positive alphas. Neural net modeling to replicate Hamilton's market calls provides interesting insight into the nature and content of the Dow Theory. This allows us to examine the properties of the Dow Theory itself out-of-sample.

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Paper provided by Yale School of Management in its series Yale School of Management Working Papers with number ysm30.

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Date of creation: 05 Mar 2004
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Handle: RePEc:ysm:somwrk:ysm30

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Web page: http://icf.som.yale.edu/
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  1. repec:fth:pennfi:70 is not listed on IDEAS
  2. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-77, December.
  3. 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 1731-64, December.
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Cited by:
  1. Ravi Dhar & William Goetzmann, 2005. "Bubble Investors: What Were They Thinking?," Yale School of Management Working Papers ysm446, Yale School of Management, revised 01 Aug 2006.
  2. repec:ltr:wpaper:1999.06 is not listed on IDEAS
  3. Li, Wei & Lam, Kin, 2002. "Optimal market timing strategies under transaction costs," Omega, Elsevier, vol. 30(2), pages 97-108, April.
  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. Colin Fyfe & John Paul Marney & Heather Tarbert, 2005. "Risk adjusted returns from technical trading: a genetic programming approach," Applied Financial Economics, Taylor & Francis Journals, vol. 15(15), pages 1073-1077.
  6. GIOT, Pierre & PETITJEAN, Mikael, 2006. "Short-term market timing using the Bond-Equity Yield Ratio," CORE Discussion Papers 2006090, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. 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.
  8. 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.
  9. 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.
  10. Thomas Schuster, 2003. "Fifty-Fifty. Stock Recommendations and Stock Prices. Effects and Benefits of Investment Advice in the Business Media," Finance 0303002, EconWPA.
  11. Ülkü, Numan & Prodan, Eugeniu, 2013. "Drivers of technical trend-following rules' profitability in world stock markets," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 214-229.
  12. 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.
  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. Pu Shen, 2002. "Market timing strategies that worked," Research Working Paper RWP 02-01, Federal Reserve Bank of Kansas City.
  15. 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.
  16. Asger Lunde & Allan Timmermann, 2000. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Econometric Society World Congress 2000 Contributed Papers 1216, Econometric Society.
  17. 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.
  18. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
  19. 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.

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