Behavioral finance and market efficiency in the time of the COVID-19 pandemic: does fear drive the market?

In this study, we examine the efficiency of the US stock markets during the COVID-19 outbreak using a fundamental financial analysis approach, the constant growth model and a behavioral model including a Google-based Index. We juxtapose the released news and the performance of the US stock market during the COVID-19 outbreak and we show that during some periods the health risk was significantly underestimated and/or ignored. The Efficient Market Hypothesis (EMH) suggests that prices incorporate all the available information at any point in time, yet as we show a systemic factor, the health risk, was not always rationally incorporated in stock prices. The Runs-tests confirm our assumption that the market was not efficient during the examined period. The reason for this inefficiency could be that something is missing from traditional finance models, such as the impact of fear of COVID-19. For this reason we employ a Coronavirus Fear Index (CFI) based on Google searches and using Granger causality we provide empirical evidence that the fear drives the S&P500 performance, and using a GARCH model we show that the fear negatively influences the performance of the US stock market.