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Title: Firm-level Risk Exposures and Stock Returns in the Wake of COVID-19

Author(s): Steven J Davis, Stephen Hansen and Cristhian Seminario-Amez

Publication Date: September 2020

Keyword(s):

Programme Area(s): Financial Economics and Industrial Organization

Abstract: Firm-level stock returns differ enormously in reaction to COVID-19 news. We characterize these reactions using the Risk Factors discussions in pre-pandemic 10-K filings and two text-analytic approaches: expert-curated dictionaries and supervised machine learning (ML). Bad COVID-19 news lowers returns for firms with high exposures to travel, traditional retail, aircraft production and energy supply -- directly and via downstream demand linkages -- and raises them for firms with high exposures to healthcare policy, e-commerce, web services, drug trials and materials that feed into supply chains for semiconductors, cloud computing and telecommunications. Monetary and fiscal policy responses to the pandemic strongly impact firm-level returns as well, but differently than pandemic news. Despite methodological differences, dictionary and ML approaches yield remarkably congruent return predictions. Importantly though, ML operates on a vastly larger feature space, yielding richer characterizations of risk exposures and outperforming the dictionary approach in goodness-of-fit. By integrating elements of both approaches, we uncover new risk factors and sharpen our explanations for firm-level returns. To illustrate the broader utility of our methods, we also apply them to explain firm-level returns in reaction to the March 2020 Super Tuesday election results.

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Bibliographic Reference

Davis, S, Hansen, S and Seminario-Amez, C. 2020. 'Firm-level Risk Exposures and Stock Returns in the Wake of COVID-19'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=15314