1. Eric Falkenstein

3. James H. Lorie and Lawrence Fisher created dataset of stocks from 1926-1964 in US Theory and data would now show us something new, true, and important “If I had to rank events, I would say this one (the original CRSP Master File) is probably slightly more significant than the creation of the universe“ Rex Sinquefeld

4. Sharpe (1965) Sharpe (1966) Treynor and Mazuy (1966) Jensen (1968)

5. Find variance more important than beta Miller and Scholes (1972) Check for Beta measurement errors Market proxy Nonnormality Skewness, Heteroskedasticity Changing interest rates No size, delisting issues

6. 1971 Institutional Investor :“The Beta Cult: The New Way to Measure Risk.” Contrast with Efficient Markets Hypothesis

7. High beta stocks will have positive beta bias Sort by beta from 1929-1933 Form 20 portfolios Estimate beta of portfolio from 1933-39 using monthly data Use beta to examine month-ahead returns

8. First pass Second pass

9. Black, Jensen and Scholes (1972), Blume and Friend (1973), Fama and MacBeth (1973),

10. Real testable hypothesis of the CAPM that the market is mean-variance efficient Given investor preferences, CAPM must hold if true Market includes real estate, human capital, so S&P500 not ‘the market’ Untestable

11. Basu (1977), Statman (1980)

12. Note relation to Beta

13. the January effect September effect Monday effect Friday effect days before holidays Returns only positive if use first half of each month

14. Low-price effect 3 year over-reaction (DeBondt and Thaler) Accruals (noncash earnings) Capital issuance R&D expenditures Momentum Earnings announcement drift Index additions Dividend effects Momentum (past 12 month’s return)

15. Chen, Roll, and Ross (1986) 1. Industrial Production change 2. BBB and AAA yield spread 3. Long term-short term yield spread 4. Unanticipated inflation 5. Anticipated inflation, 6. The market

16. Connor and Korajczyk Find factors using factor analysis First Factor looks like the Equal Weighted Equity Index Second factor ??? Third factor ???

17. Zero-beta, not risk free, asset Jointly estimating parameters Exact finite sample distributions Gibbons (1982),Shanken (1985), Gibbons, Ross, and Shanken (1989) reject CAPM at p-value 0.001

18. Big deal No big deal

19. Maximum Likelihood, Lagrange Multiplier, Wald Tests Has it ever mattered? Discriminate Analysis, Logit, Probit continuous time vs discrete time finance ‘ordinary’ Least Squares, 2-stage LS, 3-stage SLS

20. 1950 Cowles Group: Simultaneity, FIML 1950 Durbin & Watson serial correlation 1953 Theil: 2 Stage Least Squares 1960 Chow Test for Structural Change 1974 Heckman: self-selection 1974 McFadden et al: discreet choice 1978 Hausman: exogeneity test 1979 Godfrey-Breusch-Pagan-Bera: LM test 1981: non-stationarity and cointegration 1982 Engle: ARCH 1982 Hansen: GMM

21. Bad wine fancy wine $7 bottle $200 bottle Secrets to good wine: sanitation, harvest time Irrelevancies: fine terroir distinctions, charred French oak barrels Bad statistics fancy statistics Univariate correlations 2SLS Good Stats: control for omitted variables, clean data of mistakes Irrelevancies: asymptotics, GMM, joint estimations Abominations: back-fitting VARs, interaction terms,

22. Synthesize anomalies and failure of CAPM Show beta is just a size effect Founding father (Fama) admits CAPM wrong

24. From Ken French’s website SMB: Small minus Big Size HML: High minus Low Book/Market UMD: Up minus Down Stocks (Past 12 Month Return) MarketSizeValueMo Mkt-RfSMBHMLUMD 1927-2008AnnRet7.643.565.167.50 AnnStdev21.0114.3714.0515.82 Beta0.280.08-0.07 1983-2008AnnRet6.480.585.775.31 AnnStdev17.7811.6614.9313.71 Beta0.07-0.23-0.22

25. Arithmetic Averaging of daily returns: 1, 1.5, 1  +50%, -33% Arithmetic avg=8%, Geometric avg=0% Delistings Shumway finds delisted firm monthly returns -55% on Nasdaq Size Index: 1% increase from 1993 through 2009 Value Index: 4% premium from 1975 through 2009

26. Jagannathan and Wang (1993): per capita labor income (year-over-year) Lettau-Ludvigson (2000): consumption, assets, and income, Vector Auto Regression Campbell and Vuolteenaho (2002): Beta from CF and discount factor, VAR from size, yield curve, P/E ratio ‘good beta/bad beta’

27. Size, Value, Momentum related to returns Not clear why, or if real Beta not related to returns Delistings, daily returns, bias annual returns Most Anomalies—e.g., calendar effects---ephemeral or spurious Sophisticated tests have been distractions (e.g., GMM)