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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. Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-37, July.
  2. 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.
  3. 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.
  4. repec:fth:pennfi:70 is not listed on IDEAS
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Cited by:
  1. Lunde A. & Timmermann A., 2004. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 253-273, July.
  2. 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.
  3. 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.
  4. Li, Wei & Lam, Kin, 2002. "Optimal market timing strategies under transaction costs," Omega, Elsevier, vol. 30(2), pages 97-108, April.
  5. Robert Pereira, 1999. "Forecasting Ability but No Profitability: an Empirical Evaluation of Genetic Algorithm-Optimized Technical Trading Rules," Working Papers 1999.06, School of Economics, La Trobe University.
  6. Thomas Schuster, 2003. "Fifty-Fifty. Stock Recommendations and Stock Prices. Effects and Benefits of Investment Advice in the Business Media," Finance 0303002, EconWPA.
  7. 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.
  8. Pu Shen, 2002. "Market timing strategies that worked," Research Working Paper RWP 02-01, Federal Reserve Bank of Kansas City.
  9. 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.
  10. 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.
  11. 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.
  12. Pierre Bajgrowicz & Olivier Scaillet, 2007. "Technical Trading Revisited: False Discoveries, Persistence Tests, and Transaction Costs," Swiss Finance Institute Research Paper Series 08-05, Swiss Finance Institute, revised Jul 2009.
  13. 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.
  14. 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).
  15. 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.
  16. 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.
  17. 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.

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