  The paper focuses on econometrically justified robust analysis of the effects
of the COVID-19 pandemic on financial markets in different countries across the
World. It provides the results of robust estimation and inference on predictive
regressions for returns on major stock indexes in 23 countries in North and
South America, Europe, and Asia incorporating the time series of reported
infections and deaths from COVID-19. We also present a detailed study of
persistence, heavy-tailedness and tail risk properties of the time series of
the COVID-19 infections and death rates that motivate the necessity in
applications of robust inference methods in the analysis. Econometrically
justified analysis is based on heteroskedasticity and autocorrelation
consistent (HAC) inference methods, recently developed robust $t$-statistic
inference approaches and robust tail index estimation.
