Aggregate and Firm-Level Stock Returns During Pandemics, in Real Time

We show that unanticipated changes in predicted infections during the SARS and COVID-19 pandemics forecast aggregate equity market returns. We model cumulative infections as either exponential or logistic, and re-estimate the parameters of these models each day of the outbreak using information reported up to that day. For each trading day t we compute the change in predicted infections using day t − 1 versus day t − 2 information. Regression results imply that a doubling of such predictions is associated with a 4 to 11 percent decline in aggregate market value. This result implies a decline in returns’ volatility as the trajectory of the pandemic becomes clearer.

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