An Empirical Study of NASDAQ Composite based on the Asset Pricing Models

Abstract

The Fama and French five-factor model (FF5 model) has been widely used in finance to explain the returns of stocks. This model posits that stock returns can be explained by five factors: market beta, size, value, profitability and investment pattern. Despite its wide use, there has been limited empirical research on whether FF5 model is the superior in the context of the NASDAQ composite index (IXIC). This paper aims to fill this gap by conducting empirical research on the validity of the FF5 model compared with other asset pricing models. The study uses seventy-five stocks listed on the NASDAQ composite from January 2002 to December 2021 to test the validity of the FF5 model. The data was analyzed using regression analysis, with stock returns as the dependent variable and the five factors as the independent variables. The results of the study provide evidence for the validity of the FF5 model compared with other asset pricing models. It suggests that the FF5 model can explain stocks on the NASDAQ composite and it is superior compared with other asset pricing models. Result also indicated that the market beta, size, value, profitability and investment factors can have significant impact to stock returns. Thus, results suggests that the FF5 model can be used to effectively predict rate of return of stocks on the NASDAQ composite.