摘要：According to the CNN news, until the first day of year 2021, the total number of COVID-19 infections in the U.S. has exceeded 20 million and resulted in 350, 000 deaths. A review of the literature shows that COVID-19 has created a huge crisis in various industries such as offline department stores, tourism, airlines, and restaurants, but also contributes to the online service industry, medical and biopharmaceuticals. The quantitative assessment of the social impact of COVID-19 is based on various types of data. In this paper, stock prices of listed companies are used as indicators to explore the impact of the epidemic on stock prices, which further reflects the impact on different industries. Since the infection information and stock price data of listed companies are easily accessible, this article combines these data and conduct two analyses: correlation analysis and performance analysis, taking 468 listed companies in the U.S. stock market. In the correlation analysis, it is confirmed that the impact of COVID-19 on different industries or companies is different. In the performance analysis, this article predicts the performance of company stock prices before and after the outbreak by using different companies’ basic information and find that the XGBoost model works best in the 2-classes case and the random forest model works best in the 5-classes case.
