Investments, 8 th edition Bodie, Kane and Marcus Slides by Susan Hine McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved. CHAPTER 13 Empirical Evidence on Security Returns

13-2 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 The Index Model and the Single-Factor APT Expected Return-Beta Relationship Estimating the SCL

13-4 Tests of the CAPM 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

13-5 Single Factor Test Results Return % Beta Predicted Actual

13-6 Roll’s Criticism The only testable hypothesis is on the efficiency of the market portfolio In any sample of observations of individual returns –Infinite number of ex post mean-variance efficient portfolios using the sample-period returns and covariances CAPM is not testable unless we know the exact composition of the true market portfolio and use it in the tests Benchmark error

13-7 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 Table 13.1 Summary of Fama and MacBeth (1973) Study (All Rates in Basis Points per Month)

13-9 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

13-10 Table 13.2 Evaluation of Various CAPM Specifications

13-11 Table 13.3 Portfolio Shares Relative to Total Assets by Age and Net Worth

13-12 Table 13.4 Determinants of Stockholdings

13-13 Tests of the Multifactor Model Chen, Roll and Ross 1986 Study Factors Growth rate in industrial production Changes in expected inflation Unexpected inflation Unexpected Changes in risk premiums on bonds Unexpected changes in term premium on bonds

13-14 Study Structure & Results Method: Two -stage regression with portfolios constructed by size based on market value of equity Fidings Significant factors: industrial production, risk premium on bonds and unanticipated inflation Market index returns were not statistically significant in the multifactor model

13-15 Table 13.5 Economic Variables and Pricing (Percent per Month x 10), Multivariate Approach

13-16 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

13-17 Table 13.6 Three Factor Regressions for Portfolios Formed from Sorts on Size and Book-to-Market Ratios (B/M)

13-18 Interpretation of Three-Factor Model Size is a proxy for risk that is not captured in CAPM Beta Premiums are due to investor irrationality or behavioral biases

13-19 Risk-Based Interpretations Liew and Vassalou Petkova and Zhang

13-20 Figure 13.1 Difference in Return to Factor Portfolios in Year Prior to Above- Average versus Below-Average GDP Growth

13-21 Figure 13.2 HML Beta in Different Economic States

13-22 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

13-23 Figure 13.3 The Book-to-Market Ratio Reflects Past Growth, but Not Future Growth Prospects

13-24 Figure 13.4 Value minus Glamour Returns Surrounding Earnings Announcements,

13-25 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

13-26 Table 13.7 Properties of Liquidity Portfolios

13-27 Table 13.8 Estimates of the CAPM With and Without Liquidity Factors

13-28 Time-Varying Volatility Stock prices change primarily in reaction to information New information arrival is time varying Volatility is therefore not constant through time

13-29 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

13-30 Figure 13.5 Estimates of the Monthly Stock Return Variance

13-31 Figure 13.6 Implied Versus Estimated Volatility

13-32 Equity Premium Puzzle Rewards for bearing risk appear to be 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

13-33 Table 13.9 Annual Consumption Growth, (%)

13-34 Table Annual Excess Returns and Consumption Betas

13-35 Figure 13.7 Cross-Section of Stock Returns: Fama-French 25 Portfolios,