Empirical Financial Economics

1. Empirical Financial Economics The Efficient Markets Hypothesis Stephen J. Brown NYU Stern School of Business 2009 Merton H. Miller Doctoral Seminar

2. Major developments over last 35 years • Portfolio theory

3. Major developments over last 35 years • Portfolio theory • Asset pricing theory

4. Major developments over last 35 years • Portfolio theory • Asset pricing theory • Efficient Markets Hypothesis

5. Major developments over last 35 years • Portfolio theory • Asset pricing theory • Efficient Markets Hypothesis • Corporate finance

6. Major developments over last 35 years • Portfolio theory • Asset pricing theory • Efficient Markets Hypothesis • Corporate finance • Derivative Securities, Fixed Income Analysis

7. Major developments over last 35 years • Portfolio theory • Asset pricing theory • Efficient Markets Hypothesis • Corporate finance • Derivative Securities, Fixed Income Analysis • Market Microstructure

8. Major developments over last 35 years • Portfolio theory • Asset pricing theory • Efficient Markets Hypothesis • Corporate finance • Derivative Securities, Fixed Income Analysis • Market Microstructure • Behavioral Finance

9. Efficient Markets Hypothesis which implies the testable hypothesis ... where is part of the agent’s information set In returns: where

10. Efficient Markets Hypothesis • Tests of Efficient Markets Hypothesis • What is information? • Does the market efficiently process information? • Estimation of parameters • What determines the cross section of expected returns? • Does the market efficiently price risk?

11. Tests of Efficient Markets Hypothesis • Weak form tests of Efficient Markets Hypothesis • Example: trading rule tests • Semi-strong form tests of EMH • Example: Event studies • Strong form tests of EMH • Example: Insider trading studies (careful about conditioning!)

12. Random Walk Hypothesis

13. Random Walk Hypothesis

14. Random Walk Hypothesis • Serial covariance tests

15. Random Walk Hypothesis • Serial covariance tests:

16. Random Walk Hypothesis • Serial covariance tests

17. Random Walk Hypothesis • Serial covariance tests • Variance Ratio tests

18. Random Walk Hypothesis • Serial covariance tests • Variance Ratio tests • Momentum literature

19. Random Walk Hypothesis • Serial covariance tests • Variance Ratio tests • Momentum literature

20. Random Walk Hypothesis • Serial covariance tests • Variance Ratio tests • Momentum literature Zero investment portfolio

21. Random Walk Hypothesis • Serial covariance tests • Variance Ratio tests • Momentum literature • Assumes stationarity

22. Random Walk Hypothesis • Serial covariance tests • Variance Ratio tests • Momentum literature • Assumes stationarity

23. Random Walk Hypothesis • Serial covariance tests • Variance Ratio tests • Momentum literature • Assumes stationarity • Neither necessary nor sufficient for EMH

24. Trading rule tests of EMH

25. Trading rule tests of EMH • Timmerman (2007) survey • Naïve models using past sample means hard to beat • Recent financial data is most relevant • Short lived episodes of limited predictability

26. Trading rule tests of EMH • Timmerman (2007) survey • Naïve models using past sample means hard to beat • Recent financial data is most relevant • Short lived episodes of limited predictability • Predictability is not profitability • Necessity: Do not consider all possible patterns of returns • Sufficiency: Cannot profit if all markets rise and fall together

27. Trading rule tests of EMH • Timmerman (2007) survey • Naïve models using past sample means hard to beat • Recent financial data is most relevant • Short lived episodes of limited predictability • Predictability is not profitability • Necessity: Do not consider all possible patterns of returns • Sufficiency: Cannot profit if all markets rise and fall together • How can we examine significance of trading profits?

28. An important seminal reference …

29. Trading Rules: Cowles 1933 • Cowles, A., 1933 Can stock market forecasters forecast? Econometrica 1 309-325 • William Peter Hamilton’s Track Record 1902-1929 • Classify editorials as Sell, Hold or Buy • Novel bootstrap in strategy space Return on DJI

30. Trading rule predicting sign of excess returnJanuary 1970 - December 2005 Trading rule value S&P500 value Factor-augmented AR logit based on prior 120 month rolling window

31. Cowles BootstrapJan 1970-Dec 2005

32. Standard Event Study approach EVENT rt1 u01 u11 u21 … EVENT rt2 u22 … u02 u12 EVENT rt3 u03 u13 u23 … EVENT EVENT rt4 u25 … u04 u14 u24 … u05 u15 30 10 15 20 25 0 5 t

33. Orthogonality condition Event studies measure the orthogonality condition using the average value of the residual across all events where is good news and is bad news If the residuals are uncorrelated, then the average residual will be asymptotically Normal with expected value equal to the orthogonality condition, provided that the eventzt has no market wide impact

34. Fama Fisher Jensen and Roll

35. FFJR Redux

36. Original FFJR results

37. Asset pricing models: GMM paradigm • Match moment conditions with sample moments • Test model by examining extent to which data matches moments • Estimate parameters

38. Example: Time varying risk premia Time varying risk premia imply a predictable component of excess returns where the asset pricing model imposes constraint

39. Estimating asset pricing models: GMM • Define residuals • Residuals should not be predictable using instruments zt-1 that include the predetermined variables Xt-1 • Choose parameters to minimize residual predictability

40. Estimating asset pricing models: Maximum likelihood • Define residuals • Choose parameters to minimize • Relationship to GMM: when instruments zt include the predetermined variables Xt-1

41. Conclusion • Efficient Market Hypothesis is alive and well • EMH central to recent developments in empirical Finance • EMH highlights importance of appropriate conditioning • in empirical financial research • in practical applications