Firm-level stock returns differ enormously in reaction to COVID-19 news. In this keynote, Professor Steve Davis will discuss on how he characterizes these reactions using pre-pandemic 10-K filings and two text-analytic approaches: expert-curated dictionaries and supervised machine learning (ML). By integrating elements of both approaches, Steve uncovers new shock exposures and sharpen our explanations for firm-level returns. 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. His text-based models of firm-level returns also predict future corporate earnings surprises.