The Impact of Factors in Capital Assets Pricing Model and Fama-French Models

Abstract

Despite the fact that other researchers have looked into hundreds of potential factors that could affect equity returns, Fama and French initially proposed three and have since allowed for five, with the sporadic appearance of a sixth factor. By using regression which is a statistical technique that is used to isolate and quantify the significance of a variable. It works as a test to ascertain whether a stock's average returns may be influenced by factors like leverage or sector performance. This study uses R programming language and the “lm” function to research the impacts of factors in CAPM and different factors of Fama-French Models. To conclude, more factors included in the Fama-French model are not better than those with fewer factors, and there is a multicollinearity problem for different portfolios. This study aims to help other researchers have a brief consideration before using the model.