Finance Chapter 7 Scholes Examined The Risk And Return For Portfolios Stocks And Found Positive

CHAPTER 7

ASSET PRICING MODELS

7.1 The Capital Asset Pricing Model

7.1.1 A Conceptual Development of the CAPM

▪ Conceptual development of the model emphasizes its role in the natural progression that

began with the Markowitz portfolio theory.

7.1.2 The Security Market Line

1. Determining the Expected Rate of Return for a Risky Asset

▪ Determined by the risk-free rate plus a risk premium for the individual asset

▪ In equilibrium, all assets and all portfolios of assets should plot on the SML.

2. Identifying Undervalued and Overvalued Assets (Exhibits 7.2, 7.3, 7.4)

▪ Difference between estimated return and expected return is sometimes referred to as

3. Calculating Systematic Risk

a. The Impact of the Time Interval

▪ In practice, the number of observations and the time interval used in the calculation

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b. The Effect of the Market Proxy

▪ The choice of the indicator series used as the market proxy makes a difference.

5. Industry Characteristic Lines

7.2 Empirical Tests of the CAPM

▪ How stable is the measure of systematic risk (beta)?

7.2.1 Stability of Beta

▪ Beta was not stable for individual stocks but was stable for portfolios of stocks.

7.2.2 Relationship Between Systematic Risk and Return

1. Effect of a Zero-Beta Portfolio

2. Effect of Size, P/E, and Leverage

3. Effect of Book-to–Market Value

▪ Fama and French (1992) evaluated the joint roles of market beta, size, E/P, financial

7.2.3 Additional Issues

1. Effect of Transaction Costs

2. Effect of Taxes

7.2.4 Summary of Empirical Results for the CAPM

▪ There is now extensive evidence that size, the P/E ratio, financial leverage, and the book–to–

market value ratio have explanatory power regarding returns beyond beta.

▪ Kothari, Shanken, and Sloan (1995) measured beta with annual returns and found substantial

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compensation for beta risk. Suggested that the results obtained by Fama and French may have

been time-period specific.

▪ Jagannathan and Wang (1996) employed a conditional CAPM that allows for changes in

betas and in the market risk premium. This model performed well in explaining the cross

section of returns.

▪ Reilly and Wright (2004) examined the performance of 31 different asset classes with betas

computed using a broad market portfolio proxy; the risk–return relationship was significant

and as expected by theory.

7.3 The Market Portfolio: Theory versus Practice

▪ An incorrect market proxy will affect both the beta risk measure and the position and slope of

the SML that is used to evaluate portfolio performance.

7.4 Arbitrage Pricing Theory

▪ APT developed by Ross (1976, 1977) as an alternative to the Capital Asset Pricing Model

7.4.1 Using the APT

▪ The primary challenge with using the APT in security valuation is identifying the risk factors.

7.4.2 Security Valuation with the APT: An Example

▪ The idea of riskless arbitrage is to assemble a portfolio that:

7.4.3 Empirical Tests of the APT

1. Roll and Ross Study:

2. Extensions of the Roll-Ross Tests

– Cho, Elton, and Gruber (1984)

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– Harding (2008)

3. The APT and Stock Market Anomalies

4. Is the APT Even Testable?

7.5 Multifactor Models and Risk Estimation

▪ Primary practical problem in implementing the APT is that neither the identity nor the

7.5.1 Multifactor Models in Practice

1. Macroeconomic-Based Risk Factor Models (Exhibits 7.14, 7.15)

▪ Burmeister, Roll, and Ross (1994) defined the following risk exposures:

2. Microeconomic-Based Risk Factor Models (Exhibit 7.16)

7.5.2 Estimating Risk in a Multifactor Setting: Examples

1. Estimating Expected Returns for Individual Stocks (Exhibit 7.19)

▪ The following steps must be taken:

2. Comparing Mutual Fund Risk Exposures (Exhibits 7.20, 7.21, 7.22)

▪ Fidelity’s Contrafund versus T. Rowe Price’s Mid-Cap Value Fund

– Differ substantially in their systematic risk

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– Differ with in their sensitivity to the HML and SMB risk factors