The Dow Theory

1. The Dow Theory William Peter Hamilton’s Track Record Re-Considered Stephen J. Brown (NYU Stern School) William N. Goetzmann (Yale School of Management)

2. Background on the Dow Theory • Charles Henry Dow • Dow indices developed for timing studies • William Peter Hamilton • Editorialist applied “Dow Theory” 1902-1929 • Principles • market follows trends • Industrial and transportation sectors confirm • high volume indicates move

3. Testing the Theory • Alfred Cowles III • “Can Stock Market Forecasters Forecast?” E’trica 1934 • Coded editorials “Bull” “Bear” or “Neutral” • “Bull” = all stocks “Bear” = short stocks “Neut” = t-bills • Dow Portfolio, 1902 - 1929 vs. 100% stocks • Dow: 12% return per year • 1/2 DJIA & 1/2 DJTA: 15.5% return per year • Conclusion: no timing skill!

4. Testing the Theory II • Bull & bear forecasts • Sorted the 90 times Hamilton changed his forecast • Half proved profitable, half did not • Conclusion: no timing skill!

5. Problems in Cowles Analysis • 100% stocks a correct benchmark? • “Hamilton was long of stocks 55%, short of stocks 16% and out of the market 29% out of the 26 years under review.” • He made 255 forecasts, not 90 • Are two successive bear calls informative?

6. Revisiting Hamilton’s Calls • Re-coding • 46% bull calls • 16% bear calls • 38% neutral calls • Created contingency table • call vs. capital appreciation return of DJIA until next editorial

7. The Dow Theory 1903 to 1929

8. Trading Strategy Considered • Back-test of Hamilton portfolio • Assume investment in S&P with dividends & commercial paper as riskless asset. • S&P index created by Cowles as capital weighted measure of stock investment. • Monthly re-balancing

9. Hamilton’s Portfolio Vs. S&P

10. 100% S&P vs. Hamilton

11. Event Study • What happened to the DJIA after a call? • Line up returns in event-time • average across call of same direction

12. Bull vs. Bear Calls

13. Recovering The Dow Theory • Hamilton’s calls contain the essence of the Dow Theory. • Can we create a model of the theory? • Does it correspond to the writings about it?

14. Predicting Hamilton’s Signals • Use information available on the editorial date (and to us now) • See if we can forecast Hamilton’s signals • Perform out-of-sample test to see if our recovered Dow Theory worked.

15. Methodology • Step-wise regression • A linear model of Hamilton “bear” signal • Use AIC-like criterion to add and prune variables • Neural network • A non-linear model of Hamilton’s signals • Uses a broad range of variable transformations • No “coefficients” reported

16. Stepwise Regression

17. Neural Network Approach • Feature Vector Analysis • A. Kumar and V.E. McGee “FEVA: Feature vector analysis: explicitly looking for structure and forecastability in time series data,” Economics and Financial Computing, Winter, 1996

18. Neural Net Events 1902-1929

19. Neural Net Events 1930-1996

20. Conclusions • The Dow Theory reputation was deserved • Hamilton followed a momentum strategy • The spread between bull and bear calls has continued out of sample, albeit diminished