This paper is aimed to validate the four-factor asset pricing model as an improvement towards the standard Fama-French three-factor model. Using U.S. monthly stock returns data from period January 1963 to December 2010, we construct 25 portfolios and the four-factor model includes the market factor (beta), the size factor (SMB), the book-to-market factor (HML), and the ‘momentum' factor (MOM). Similar time series method as in Fama and French (1993) are employed to elaborate the three-factor model and the four-factor model regression. Our findings show that the four-factor model to some extent has significant capability in explaining the variations in average excess stock returns. Although the R2 extracted from the four-factor model is just slightly higher than the three-factor model, yet it provides suggestive for the robustness of the four-factor model. In addition, our robustness test shows that January seasonal effect is absorbed by the risk factors including the market factors, SMB, HML, and MOM factor. The consistency of the four-factor model in explaining the U.S stock market return variations for the newest data, provide relevance to apply this model in emerging markets data in order to give guidance for investor in understanding the market condition.
|Journal||Indonesian Capital Market Review|
|Publication status||Published - 2018|