CHAPTER 13 Investments Empirical Evidence on Security Returns Slides by Richard D. Johnson Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved McGraw-Hill/Irwin Cover image

13- 2 Cover image Overview of Investigation  Tests of the single factor CAPM or APT Model  Tests of the Multifactor APT Model –Results are difficult to interpret  Studies on volatility of returns over time

13- 3 Cover image Tests of the Single Factor Model Tests of the expected return beta relationship:  First Pass Regression –Estimate beta, average risk premiums and unsystematic risk.  Second Pass: Using estimates from the first pass to determine if model is supported by the data.  Most tests do not generally support the single factor model.

13- 4 Cover image Single Factor Test Results Return % Beta Predicted Actual

13- 5 Cover image Roll’s Criticism  The only testable hypothesis is on the efficiency of the market portfolio.  Benchmark error

13- 6 Cover image Table 13.1 Summary of Fama and MacBeth (1973) Study (All Rates in Basis Points per Month)

13- 7 Cover image Measurement Error in Beta  Statistical property  If beta is measured with error in the first stage, second stage results will be biased in the direction the tests have supported.  Test results could result from measurement error.

13- 8 Cover image Jaganathan and Wang Study  Included factors for cyclical behavior of betas and human capital.  When these factors were included the results showed returns were a function of beta.  Size is not an important factor when cyclical behavior and human capital are included.

13- 9 Cover image Table 13.2 Evaluation of Various CAPM Specifications

Cover image Table 13.3 Portfolio Shares Relative to Total Assets by Age and Net Worth

Cover image Table 13.4 Determinants of Stockholdings

Cover image Tests of the Multifactor Model  Chen, Roll and Ross 1986 Study Factors Growth rate in industrial production Changes in expected inflation Unexpected inflation Changes in risk premiums on bonds Unexpected changes in term premium on bonds

Cover image Study Structure & Results  Method: Two -stage regression with portfolios constructed by size based on market value of equity. Findings  Significant factors: industrial production, risk premium on bonds and unanticipated inflation.  Market index returns were not statistically significant in the multifactor model.

Cover image Table 13.5 Economic Variables and Pricing (Percentage per Month 3, 10), Multivariate Approach

Cover image Fama-French Three Factor Model  Size and book-to-market ratios explain returns on securities  Smaller firms experience higher returns  High book to market firms experience higher returns  Returns are explained by size, book to market and by beta

Cover image Table 13.6 Three Factor Regressions for Portfolios Formed from Sorts on Size and Book-to-Market Ratios (B/M)

Cover image Interpretation of Three-Factor Model  Size is a proxy for risk that is not captured CAPM Beta  Premiums are due to investor irrationality or behavioral biases

Cover image Risk-Based Interpretations  Liew and Vassalou  Petkova and Zhang

Cover image Figure 13.1 Difference in Return to Factor Portfolios in Year Prior to Above-Average versus Below-Average GDP Growth

Cover image Figure 13.2 HML Beta in Different Economic States

Cover image Behavioral Explanations  Market participants are overly optimistic –Analysts extrapolate recent performance too far into the future –Prices on these glamour stocks are overly optimistic –Lower book-to-market on these glamour firms leads to underperformance compared to value stocks  Chan, Karceski and Lakonishok  LaPort, Lakonishok, Shleifer and Vishny

Cover image Figure 13.3 The Book-to-Market Ratio Reflects Past Growth, but Not Future Growth Prospects

Cover image Figure 13.4 Value minus Glamour Returns Surrounding Earnings Announcements

Cover image Liquidity and Asset Pricing  Acharya and Pedersen –Premiums observed in the three-factor model may be illiquidity premiums –Liquidity may explain the size premium but not the book-to-market premium

Cover image Table 13.7 Characteristics of Portfolios Sorted by Liquidity

Cover image Time-Varying Volatility  Stock prices change primarily in reaction to information.  New information arrival is time varying.  Volatility is therefore not constant through time.

Cover image Stock Volatility Studies and Techniques  Volatility is not constant through time.  Improved modeling techniques should improve results of tests of the risk-return relationship.  ARCH and GARCH models incorporate time varying volatility.

Cover image Figure 13.5 Estimates of the Monthly Stock Return Variance

Cover image Figure 13.6 Implied Volatility versus Estimated Volatility

Cover image Figure 13.7A Implied Volatility of the Nasdaq 100 Portfolio (VXN) and Historical Volatility of the Nasdaq Composite Portfolio

Cover image Figure 13.7B Implied Volatility of the Standard and Poor’s 100 Portfolio (VIX) and the Nasdaq 100 Portfolio (VXN)

Cover image Figure 13.8A Historical Volatility of the CRSP Nasdaq Large Capitalization (Decile 10) and Small Capitalization (Decile 1) Portfolios

Cover image Figure 13.8B Historical Volatility of the CRSP NYSE Large Capitalization (Decile 10) and Small Capitalization (Decile 1) Portfolios

Cover image Equity Premium Puzzle  Rewards for bearing risk appear to excessive.  Possible Causes –CAPM doesn’t consider the impact of consumption –Predicting returns from realized returns  Survivorship bias also creates the appearance of abnormal returns in market efficiency studies.

Cover image Figure 13.9 Real Returns on Global Stock Markets