The CAPM Debate

The CAPM Debate

Author: Jagannathan, McGrattan

By Maia

This article describes the academic debate about the usefulness of the capital asset pricing model.

The studies that support CAPM- Black; Black, Jensen and Scholes; Fama and McBeth

Studies that challenge CAPM- Banz; Fama and French

Studies that challenge challenges- Jagannathan and Wang

The article concludes that while the academic debate continues, CAPM may still be useful in LR (Straight line relationship between risk and return breaks down in shorter time periods).

Theory of CAPM

During the horizon from 1926 to 1991 the performance of the stocks of small firms was even more impressive; they earned the average of 16.1%. The assets with higher average returns had also more variable returns. Though across subperiods, the time series of realized returns are different in both average and volatility. A portfolio is said to be on the mean-variance frontier of the return/ variance relationship if no other choice of weights yields a lower variance for the same expected return. The portfolio is said to be on the efficient part of the frontier if no other portfolio has a higher expected return. Blacks shows that without a risk-free asset the returns satisfy CAPM equation if we include asset with zero-variance on the place of risk-free asset. The CAPM predicts that the ratio of the risk premium to the beta of every asset is the same. That is every investment opportunity provides the same aount of compensation for any given level of risk, when Beta is used as a measure of risk.Cost of capital- the expected rate of return that the investors will require for investing in a specific project of financial asset.

Classic Support

Studies support that high Beta leads to high returns. The relationship is linear.

Challenges

Banz tests the CAPM by checking whether the size of the firms involved can explain the variation in returns that is not explained by beta. Banz shows that size explains variation. He finds that during 1936- 1975 the average returns to stocks of small firms was substantially higher than the average return to stocks of large firms. This observation is now known as a size effect. Banz finds an evidence that the size effect is large and statistically significant. The coefficient is negative ( the bigger the firm, the smaller returns).

In another important study Fama and French cannot find any relation between return and risk at all. They conclude that over shorter horizons there is not relation between risk and return (the relation is flat).

Also Fama and French find that book-to-market ratio is an important determinant of return and can be even more important than size.

Responses to challenges

·  The data used for Fama and French’s findings was too noisy. When a more efficient statistical method is used, the estimated relation between average return and beta is positive.

·  Black suggests that the size effect noted by Banz could simply be a sample period effect.

·  Even if there is a size effect , there is still a question about its importance given the relatively small value of small firms.

·  There was a bias in study of Fama and French, because only firms that survived with higher ratio of book-to-market value were added in the study.

Modifications for CAPM

Jagannathan and Wang include growth of labor income as a proxy for human capital. Several studies have pointed out that betas of assets vary over business cycles in a systematic way.