Capital Asset Pricing Model is a hotly debated concept for stock valuation, espe

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The capital asset pricing model (CAPM) has been the model that is most widely used by the market for calculating expected rates of return on risky assets. Although the CAPM calculates expected excess return on risky assets as the only function of their systematic risk, subsequent empirical studies indicate the existence of other factors that influence achieved historic returns. It is known that the average return on US shares is greater for value companies, or rather, those with a high book value of net equity to market value ratio. Based on these market anomalies, it was proposed that they identified three risk factors that would determine expected return on shares: the market factor, the factor related to the size of the firm, and another to the BM index. Subsequently,someone added a fourth factor, related to momentum, regarding significantly positive historic returns from adopting a strategy of buying winning shares funded by the sale of losing shares.

Wall Street analysts did an analysis to study if CAPM is the correct method for stock valuation. Analyzing the CAPM intercept, it was verified that for three out of 12 portfolios before the crisis, and five out of 12 portfolios after the crisis, coefficient was different from zero, with 95% confidence, which would contradict the CAPM hypotheses. This indicated that the market risk factor was not enough to capture all of the risk premiums in the market. Thus, the multifactor models would be better, since for only one portfolio the intercept was statistically relevant to 5% significance before the crisis, and this was the case for none of them after the crisis, which led to the conclusion that the multifactor models used managed to capture the anomalies existing in the market. In accordance with what was expected, the coefficient, which measures sensitivity to the market risk factor, presented a positive sign and statistical significance to 5% for all of the portfolios and models, that is, even after considering the other factors. Despite the importance of the market risk factor, it was not enough to capture all of the risk premiums in the market. The results from the time series regressions reveal that the market risk factor is the most important for explaining portfolio returns, however it is not the only one with statistical significance. For most of the portfolios, the three and four factor models obtain a significant improvement in the adjusted R2, confirming the existence of anomalies in the equities market. Analyzing the sub-periods, it is important to highlight that the market risk premium is positive and significant only for the pre-crisis period, being negative in the crisis period and close to zero in the post-crisis period, but without statistical relevance in these last two sub-periods. It can also be noted that, in using the total sample in the time regression, the pre-crisis period predominates due to it having more observations, influencing the regression coefficients.

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