1. Multifactor Models and Market Efficiency (BKM 11, 12, 13) BUFN 741: Advanced Capital Markets Topic 4

2. Multifactor Asset Pricing Models u CAPM is a model that can be used to (1) explain why certain firms have certain returns; and (2) estimate expected return (discount rate). But it does not work. u The empirical failure of CAPM leaves room for improvement u Maybe we should not use the market portfolio return as the only systematic factor –The market portfolio might not be representative –We can just regard those pervasive “anomalies” as additional factors 2BUFN 741: Advanced Capital Markets Topic 4

3. Fama and French (1993): Three Factor Model u The factors in the Fama and French (1993, JFE) three-factor model: –MKT(t): The return on the market (value-weighted) in excess of the T-bill rate –SMB(t) (Small minus Big): The return on small-cap stocks (bottom 50%) minus the return on large-cap stocks (top 50%) –HML(t) (High minus Low): The returns on high book-to- market stocks (top 30%) minus those on low book-to-market stocks (bottom 30%) 3BUFN 741: Advanced Capital Markets Topic 4

4. The Value Premium u Growth stock: High market value relative to accounting measures of value –Growth: high stock price reflects capitalized growth opportunities u Value stock: Low market value relative to accounting measures –Value: physical assets-in-place can be acquired at low prices u Value stocks earn higher returns than growth stocks on average (e.g., Fama and French 1992, 1993), the difference is called the value premium u The value premium reliable around the globe: Fama and French (1998) 4BUFN 741: Advanced Capital Markets Topic 4

5. Lakonishok, Shleifer, and Vishny (1994): Behavioral Overreaction u Fama and French (1992) believe that the value premium exists because value firms are more risky, probably reflecting distress risk u Lakonishok, Shleifer, and Vishny (1994): Not a risk story, but due to behavioral overreaction –Growth stocks are priced too high because they are glamorous –Value stocks are priced too low because they are out of favor –Naive investors extrapolate past performance too far into the future –Value strategies bet against naive investors, outperform the market 5BUFN 741: Advanced Capital Markets Topic 4

6. Momentum: A Fourth Factor u The original Fama-French model augmented with a momentum factor has become a common four-factor model used to evaluate abnormal performance of a stock portfolio. u Momentum may be related to liquidity. 6BUFN 741: Advanced Capital Markets Topic 4

7. Efficient Market Hypothesis (EMH) u Do security prices reflect information? u EMH and Competition –Stock prices fully and accurately reflect publicly available information. –Once information becomes available, market participants analyze it. –Competition assures prices reflect information. u Why look at market efficiency? –Implications for business and corporate finance –Implications for investment 7BUFN 741: Advanced Capital Markets Topic 4

8. Figure 11.1 Cumulative Abnormal Returns Before Takeover Attempts: Target Companies 8BUFN 741: Advanced Capital Markets Topic 4

9. Figure 11.2 Stock Price Reaction to CNBC Reports 9BUFN 741: Advanced Capital Markets Topic 4

10. Efficient Market Hypothesis u Forms of the EMH –Weak –Semi-strong –Strong u Types of stock analysis –Technical Analysis - using prices and volume information to predict future prices. »Weak form efficiency & technical analysis –Fundamental Analysis - using economic and accounting information to predict stock prices. »Semi strong form efficiency & fundamental analysis 10BUFN 741: Advanced Capital Markets Topic 4

11. Active or Passive Management u Active Management: against EMH –Security analysis –Timing u Passive Management: consistent with EMH –Buy and Hold –Index Funds u Even if the market is efficient a role exists for portfolio management: –Appropriate risk level –Tax considerations –Other considerations such as investment horizon 11BUFN 741: Advanced Capital Markets Topic 4

12. Empirical Tests of Market Efficiency u Event studies u Assessing performance of professional managers u Testing some trading rule u How to test? – Examine prices and returns over time 12BUFN 741: Advanced Capital Markets Topic 4

13. Return Over Time 0+t-t Announcement Date 13BUFN 741: Advanced Capital Markets Topic 4

14. How Tests Are Structured u Returns are adjusted to determine if they are abnormal. –Market Model approach »a. R t = a t + b t R mt + e t »(Expected Return) »b. Excess Return = (Actual - Expected) »e t = Actual - (a t + b t R mt ) »c. Cumulate the excess returns over time: –Or use Fama-French three factors 14BUFN 741: Advanced Capital Markets Topic 4

15. Weak-Form Tests u Serial Correlation u Momentum u Returns over Long Horizons: reversal u Interpretations: –First overreaction and the correction 15BUFN 741: Advanced Capital Markets Topic 4

16. Cumulative Return Relative to Losers 16BUFN 741: Advanced Capital Markets Topic 4

17. Time Series Predictability u Time series predictability –Higher dividend ratios or earnings-price ratios predict higher returns in the future –Credit spread (corporate yield-Treasury yield) can predict market returns u Time series predictability is difficult: Many investors avoid macro bets BUFN 741: Advanced Capital Markets Topic 417

18. Cross-sectional Predictability: Anomalies u The value effect: firms with higher dividend-price ratios, book- to-market ratios, earnings-to-price ratios, or lower past long- term returns earn higher future returns u Size effect u Momentum effect u Post-earnings announcement drift u Cross-sectional predictability is easier than time-series 18BUFN 741: Advanced Capital Markets Topic 4

19. Figure 11.3 Average Annual Return for 10 Size-Based Portfolios, 1926 – 2008 19BUFN 741: Advanced Capital Markets Topic 4

20. Figure 11.4 Average Return as a Function of Book-To- Market Ratio, 1926–2008 20BUFN 741: Advanced Capital Markets Topic 4

21. Figure 11.5 Cumulative Abnormal Returns in Response to Earnings Announcements 21BUFN 741: Advanced Capital Markets Topic 4

22. Interpreting the Evidence u Risk Premiums or Inefficiencies –Disagreement here u Data Mining or Anomalies u Behavioral Explanations –Information Processing Errors –Behavioral Biases –Limits to Arbitrage 22BUFN 741: Advanced Capital Markets Topic 4

23. Information Processing u Forecasting Errors –Memory bias: ‘This time is different!” u Overconfidence –“Trading is hazardous to your health!” u Conservatism –Post earnings announcement drift u Sample Neglect and Representativeness –Earnings extrapolation 23BUFN 741: Advanced Capital Markets Topic 4

24. Behavioral Biases u Framing –You have been given 10,000. Now choose between A={10,000, 0.5} and B={5,000, 1}. –You have been given 20,000. Now choose between C={- 10,000, 0.5} and D={-5,000, 1}. u Mental Accounting –“House money effect” and “not dip into capital” u Regret Avoidance –Herding behavior of institutional investors 24BUFN 741: Advanced Capital Markets Topic 4

25. Prospect Theory u People are risk averse over gains, but risk-seeking over loses. u Sell winners too soon but hold on losers for too long BUFN 741: Advanced Capital Markets Topic 425

26. Limits to Arbitrage u Fundamental Risk –Royal Dutch Petroleum and Shell –LTCM u Implementation Costs u Model Risk –Am I stupid or the market is stupid? 26BUFN 741: Advanced Capital Markets Topic 4

27. Mutual Fund Performance u The conventional performance benchmark today is a four-factor model, which employs: –the three Fama-French factors (the return on the market index, and returns to portfolios based on size and book-to- market ratio) –plus a momentum factor (a portfolio constructed based on prior-year stock return). 27BUFN 741: Advanced Capital Markets Topic 4

28. Figure 11.7 Estimates of Individual Mutual Fund Alphas, 1993 - 2007 28BUFN 741: Advanced Capital Markets Topic 4

29. Table 11.1 Performance of Mutual Funds Based on Three-Index Model 29BUFN 741: Advanced Capital Markets Topic 4

30. u Consistency, the “hot hands” phenomenon –Carhart – weak evidence of persistency –Bollen and Busse – support for performance persistence over short time horizons –Berk and Green – skilled managers will attract new funds until the costs of managing those extra funds drive alphas down to zero. Mutual Fund Performance 30BUFN 741: Advanced Capital Markets Topic 4

31. Figure 11.8 Risk-adjusted Performance in Ranking Quarter and Following Quarter 31BUFN 741: Advanced Capital Markets Topic 4

32. So, Are Markets Efficient? u The performance of professional managers is broadly consistent with market efficiency. u Most managers do not do better than the passive strategy. u There are, however, some notable superstars: –Peter Lynch, Warren Buffett, John Templeton, George Soros 32BUFN 741: Advanced Capital Markets Topic 4