全球智库信息集成服务系统(G2TT): DP15314 Firm-level Risk Exposures and Stock Returns in the Wake of COVID-19

G2TT

来源类型	Discussion paper
规范类型	论文
来源ID	DP15314
	DP15314 Firm-level Risk Exposures and Stock Returns in the Wake of COVID-19
	Steven Davis; Stephen Hansen; Cristhian Seminario-Amez
发表日期	2020-09-23
出版年	2020
语种	英语
摘要	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.
主题	Financial Economics ; Industrial Organization
URL	https://cepr.org/publications/dp15314
来源智库	Centre for Economic Policy Research (United Kingdom)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/544293
推荐引用方式 GB/T 7714	Steven Davis,Stephen Hansen,Cristhian Seminario-Amez. DP15314 Firm-level Risk Exposures and Stock Returns in the Wake of COVID-19. 2020.