Predicting stock returns in the presence of COVID-19 pandemic: The role of health news

Salisu, Afees A.; Vo, Xuan Vinh

Abstract This study derives its motivation from the current global pandemic, COVID-19, to evaluate the relevance of health-news trends in the predictability of stock returns. We demonstrate this using data for of top-20 affected countries, separately in terms of most cases and most deaths reporting countries. The results reveal that the model that incorporates health-news index outperforms the benchmark historical average model, indicating the significance of health news searches as a good predictor of stock returns since the emergence of the pandemic. We also find that accounting for “asymmetry” effect, adjusting for macroeconomic factors and incorporating financial news improves the forecast performance. These results are consistently robust to data sample, both in the in-sample and out-of-sample forecast periods, outliers and heterogeneity.