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The Dow Theory: William Peter Hamilton's Track Record Reconsidered

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  • Stephen J. Brown

    (New York University Stern School of Business,)

  • William N. Goetzmann

    (Yale School of Management)

  • Alok Kumar

    (Yale School of Management)

Abstract

Alfred Cowles' test of the Dow Theory apparently provides strong evidence against the ability of Wall Street's most famous chartist to forecast the stock market. Cowles (1934) analyzes editorials published by the chief exponent of the Dow Theory, William Peter Hamilton. We review Cowles' evidence and find that it supports the contrary conclusion. Hamilton's timing strategies actually yield high Sharpe ratios and positive alphas for the period 1902 to 1929. Neural net modeling to replicate Hamilton's market calls provides interesting insight into the Dow Theory and allows us to examine the properties of the theory itself out of sample. Copyright The American Finance Association 1998.

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Bibliographic Info

Article provided by American Finance Association in its journal The Journal of Finance.

Volume (Year): 53 (1998)
Issue (Month): 4 (08)
Pages: 1311-1333

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Handle: RePEc:bla:jfinan:v:53:y:1998:i:4:p:1311-1333

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  1. repec:fth:pennfi:70 is not listed on IDEAS
  2. 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.
  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. 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.
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Cited by:
  1. 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).
  2. 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.
  3. 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.
  4. 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.
  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. Li, Wei & Lam, Kin, 2002. "Optimal market timing strategies under transaction costs," Omega, Elsevier, vol. 30(2), pages 97-108, April.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. Thomas Schuster, 2003. "Fifty-Fifty. Stock Recommendations and Stock Prices. Effects and Benefits of Investment Advice in the Business Media," Finance 0303002, EconWPA.
  13. 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.
  14. Pu Shen, 2002. "Market timing strategies that worked," Research Working Paper RWP 02-01, Federal Reserve Bank of Kansas City.
  15. 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.
  16. 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.
  17. 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).

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