The Impact of Coronavirus Pandemic Severity on Financial Analyst Earnings Forecasts

Abstract

This thesis presents an assessment of analysts’ forecasting abilities when influenced by the Coronavirus pandemic. In the first study, I document an increase in both pessimism and accuracy of earning forecasts issued by analysts during the post-COVID pandemic. I then introduce the primary focus of the thesis, examining the effect of COVID severity levels on analysts’ performance, proxied by the key characteristics of earning forecasts: pessimism, accuracy, timeliness and frequency. In the final study, I examine the impact of working from home during the COVID pandemic and find it has no meaningful influence on analysts’ performance aside from their sentiment. My studies corroborate and extend the extant behavioural finance and psychology literature, highlighting the importance of understanding the severity of an exogenous shock and the influence of working environments on analysts’ performance.