Analysis of U.S. Game Industry Based on Fama-French Model under COVID-19

A large number of researchers have contributed much to asset pricing theory and continuously try to find the best model to capture stock average return. This paper aims to test the performances of Fama-French 3 factors and Fama-French 5 factors models on game industry in U.S market before and after the outbreak of COVID-19 and explore the possible reasons. The results show that both models demonstrate better performances in game industry after the beginning of epidemic than before and five-factor model could explain a little more. Market risk (MKT) and Small minus Big (SMB) always show significance in both models and the power in explanation becomes stronger in post-COVID-19 data. Influenced by the COVID-19, High minus Low (HML) begins to play a positive role. For five-factor model, Robust Minus Weak (RMW) and Conservative Minus Aggressive (CMA) exchange their position. After the outbreak, CMA factor's significance emerges with a negative power to the average return while a previous significant factor RMW becomes redundant. The study suggests 5-factor model and 3-factor model both are more suitable for U.S. game industry in post-COVID-19 time and the five-factor one slightly outperforms the 3-factor model even though factor RMW is redundant.