Firm-Level Risk Exposures and Stock Returns in the Wake of COVID-19

83 Pages Posted: 9 Oct 2020

See all articles by Steven J. Davis

Steven J. Davis

University of Chicago; National Bureau of Economic Research (NBER); Hoover Institution

Stephen Hansen

University College London - Department of Economics

Cristhian Seminario-Amez

University of Chicago - Department of Economics

Multiple version iconThere are 4 versions of this paper

Date Written: 2020

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.

Suggested Citation

Davis, Steven J. and Hansen, Stephen and Seminario-Amez, Cristhian, Firm-Level Risk Exposures and Stock Returns in the Wake of COVID-19 (2020). CESifo Working Paper No. 8594, Available at SSRN: https://ssrn.com/abstract=3707934 or http://dx.doi.org/10.2139/ssrn.3707934

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Cristhian Seminario-Amez

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