Challenges to the CAPM


CAPM- Capital assets pricing Models

The CAPM has not gone unchallenged. The key ingredient in the model is the use of beta as a measure of risk. Early, empirical studies showed beta to have reasonable predictive power about return, particularly the return on a portfolio of common stocks. No one claimed the model was perfect; as if anything were! However, it is fairly easy to understand and apply. Such market imperfections as bankruptcy costs, taxes, and institutional restraints have been recognized, and refinements can be made to account for their effects.


When scholars have tried to explain actual security returns, several anomalies have become evident. One is a small-firm, or size, effect. It has been found that common stocks of firms with small market capitalizations (price per share times the number of shares outstanding) provide higher returns than common stocks of firms with high capitalizations, holding other things constant. Another irregularity is that common stocks with low price/earnings and market-to-value ratios do better than common stocks with high ratios. Still other anomalies exist. For examples, holding a common stock from December to January often produces a higher return than is possible for other similar-length periods. This anomaly is known as the January effect. Although these January effects have been found for many years, they do not occur every year.

Fama and French Study:

In a provocative article, Eugene Fama and Kenneth French looked empirically at the relationship among common stock returns and are firm’s market capitalization (size), market-to-book-value ratio, and beta. Testing stock returns over the period 1963 – 90, they found that the size and market–to-book-value variables are powerful predictors of average stock returns. When these variables were used first in a regression analysis, the added beta variable was found to have little additional explanatory power. This led Professor Fama, a highly respected researcher, to claim that beta—as sole variable explaining returns—is “dead�. Thus, Fama and French launched a powerful attack on the ability of the CAPM to explain common stock returns, suggesting that a firm’s market value (size) and market–to-book-value ratio are the appropriate proxies for risk.

However, the authors tried to explain market value returns with two variables that are based on market value. The fact that the correlation between the explained variable and the explaining variables is high is not surprising. Fama and French did not focus on risk, but rather on realized returns. No theoretical foundation is offered for the finding they discovered. Though beta may not be a good indicator of the returns to be realized from investing in common stocks, beta remains a reasonable measure of risk. To the extent that investors are risk averse, beta gives information about the underlying minimum return that one should expect to earn. This return may or may not be realized by investors. However, for purposes of corporate finance it is a helpful guide for allocating capital to investment projects.

The CAPM and Multifactor Models:

Although the CAPM remains useful for our purposes, it does not give a precise measurement of the market equilibration process or of the required return for a particular stock. Multifactor models- that is, models which claim that the return on a security is sensitive to movements of multiple factors, or indices, and not just to overall market movements give added dimension to risk and certainly have more explanatory power than a single factor model like the CAPM. Our view is that the CAPM remains a practical way to look at risk and returns that might be required in capital markets. It also serves as a general framework for understanding unavoidable (systematic) risk, diversification, and the risk premium above the risk-free rate that is necessary I order to attract capital. This framework is applicable to all valuation models in finance.

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