In this study, we propose a wavelet-copula-GARCH procedure to investigate the occurrence of cross-market linkages during the COVID-19 pandemic. To explore cross-market linkages, we distinguish between regular interdependence and pure contagion, and associate changes in the correlation between stock market returns at higher frequencies with contagion, whereas changes at lower frequencies are associated with interdependence that relates to spillovers of shocks resulting from the normal interdependence between markets. An empirical analysis undertaken on six major stock markets reveals evidence of long-run interdependence between the markets under consideration before the start of the COVID-19 pandemic in December 2019. However, after the health crisis began, strong evidence of pure contagion among stock markets was detected.

中文翻译：

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COVID-19 大流行期间股市传染的证据：小波-Copula-GARCH 方法

在这项研究中，我们提出了一个小波-copula-GARCH 程序来调查 COVID-19 大流行期间跨市场联系的发生。为了探索跨市场的联系，我们区分了常规的相互依赖和纯粹的传染，并将较高频率的股票市场回报之间相关性的变化与传染相关联，而较低频率的变化与相互依赖相关市场之间正常的相互依存关系。对六个主要股票市场进行的实证分析揭示了在 2019 年 12 月 COVID-19 大流行开始之前所考虑的市场之间长期相互依存的证据。然而，在健康危机开始之后，股票市场之间纯粹传染的有力证据被检测到。