Covid-19's Impact on the U.S. Stock Market based on Fama-Frech Multi-factors Model

Abstract

Since COVID-19 outbreak in 2019 has hugely impacted the global economy, influencing the U.S. stock market. Many industries went through the shutdown, heavy loss, and bankruptcy. During this challenging period, investors suffered from tremendous stresses of financial risk and sought to use the capital asset pricing model to evaluate different stock portfolios. This article is designed to help them find an effective investment method to gain more return in the U.S. stock market. The daily 49 Industry Portfolios datasets used in this research are from Kenneth R. French Data Library and were selected the date from 2000, January 1st to 2021, December 31st, and equally divided into three periods, before the COVID-19 period, during the COVID-19 period, and after the first Pfizer vaccine authorized. Based on the CAPM model, the Fama-French Five-Factor model can better explain the excess return in the U.S. stock market. This article uses the method of multiple linear regression to process the dataset and adopt the Fama-French Five-Factor model to analyze the change in significance and coefficient of five factors. By analyzing the number of anomalies in 49 industries, the result shows that anomalies decreased from 26 to 6 industries, indicating that the Fama-French Five-Factor model has a good explanation for excess return. As for the coefficient change of five factors, the coefficient of market portfolio return (MKT) is close to 1, which means the power of explanation becomes stronger. The coefficient of Small Minus Big Size (SMB) slightly changed but is larger than 0, indicating small-cap firms have better performance than large-cap ones. High Minus Low B/M (HML), Robust Minus Weak Operating Profitability (RMW), and Conservative Minus Aggressive investment (CMA)becomes an insignificant factor. Therefore, the factors HML, RMW, and CMA would not be appropriate to consider as practical investment methods for investors.