经济意外可以解释股票回报吗:以COVID-19大流行为例

Amine Ben Amar, Héla Mzoughi, K. Guesmi
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摘要

本文提出了一种新的流行病不确定性测量方法,结合了与SARS-CoV-2疾病相关的三个维度,即(i) COVID-19确诊病例总数,(ii) COVID-19确诊死亡总数和(iii) COVID-19康复病例总数,以显示金融和宏观经济变量如何应对流行病风险。利用交叉小波相干性,我们研究了美国和欧洲股票市场与时频域三种不确定性指标(金融、经济和流行病)之间的关系。我们的实证分析证实,金融不确定性与市场之间存在密切的非相位联系,并表明疫情不确定性对美国和欧洲股市的影响,随着时间和频率的变化,呈现出不同的模式。
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Do Economic Surprises Explain Returns of Stocks: The Case of COVID-19 Pandemic
This paper proposes a new measure of epidemic uncertainty combining three dimensions related to the SARS-CoV-2 disease ‒ (i) the total COVID-19 confirmed cases, (ii) the total COVID-19 confirmed deaths and (iii) the total COVID-19 recovered cases ‒ to show how financial and macroeconomic variables respond to epidemic risk. Using the cross-wavelet coherence, we investigate the relationship between the American and European stock markets and three measures of uncertainty (financial, economic, and epidemic) in the time-frequency domain. Our empirical analysis confirms the close out-of-phase link between financial uncertainty and markets, and suggests that the impact of the epidemic uncertainty, on both the U.S. and European stock markets, exhibit different patterns over time and across frequencies.
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