流行病期间的实时总体和公司级股票回报

Laura Alfaro, Anusha Chari, Andrew Greenland, Peter K. Schott
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引用次数: 388

摘要

我们的研究表明,COVID-19感染轨迹的意外变化可以实时预测美国股市的回报。参数估计表明,如果第二天预计感染人数意外增加一倍(减半),美国总市值将减少(增加)4%至11%,这表明,如果疾病的发展轨迹没有最初预期的那么严重,即使感染人数继续上升,股票市场也可能开始反弹。利用非预期预测病例的相同变化,我们发现企业层面与covid -19相关的市值损失随着资本密集度和杠杆率的上升而上升,并且在更有利于疾病传播的行业中更深。这些关系为了解当前创纪录的失业状况提供了重要线索。衡量美国各州市场价值随着其所生产行业就业加权平均下降而下降的情况,我们发现,市场价值下降幅度较小的州,人均首次申请失业救济人数更高。这个最初违反直觉的结果表明,投资者看重的是在收入下降时相对容易地削减劳动力成本和资本成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Aggregate and Firm-Level Stock Returns During Pandemics, in Real Time
We show that unexpected changes in the trajectory of COVID-19 infections predict US stock returns, in real time. Parameter estimates indicate that an unanticipated doubling (halving) of projected infections forecasts next-day decreases (increases) in aggregate US market value of 4 to 11 percent, indicating that equity markets may begin to rebound even as infections continue to rise, if the trajectory of the disease becomes less severe than initially anticipated. Using the same variation in unanticipated projected cases, we find that COVID-19-related losses in market value at the firm level rise with capital intensity and leverage, and are deeper in industries more conducive to disease transmission. These relationships provide important insight into current record job losses. Measuring US states' drops in market value as the employment weighted average declines of the industries they produce, we find that states with milder drops in market value exhibit larger initial jobless claims per worker. This initially counter-intuitive result suggests that investors value the relative ease with which labor versus capital costs can be shed as revenues decline.
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