Examining the Adaptation of the Fama-French Three-Factor and Five-Factor Models in the US Market

Abstract

The adaptability of the Fama-French three-factor and five-factor models in distinct markets is currently a key research topic. Some researchers are investigating whether the FF3FM and FF5FM are reasonable frameworks for explaining excess returns in stock markets by testing them with data from different markets. This paper mainly explores the adaptability of FF3FM and FF5FM in the US stock market, and adds CAPM to the comparison. This article uses the daily factors’ data and the daily average value weighted returns in 6 portfolios formed on size and book-to-market in the Kenneth French database website to construct a linear regression model to study the explanatory power of FF3FM and FF5FM in the US stock market. In order to determine whether these factors are parts of an effective asset pricing model, this paper assesses the efficacy, robustness, and reliability of factors in explaining asset returns using the Durbin-Watson test, the correlation matrix, and the sub-period analysis, which also confirm whether these factors have statistical significance, economic significance, and stability. It is found that the explanatory power of FF5FM is stronger than that of FF3FM in the US stock market. While both profitability and investment factors have relatively modest explanatory power, size and value factors offer significant explanatory power for stock returns.