论文标题
在COVID-19期间对网络过滤方法的分析，以主权债券产量的分析
An analysis of network filtering methods to sovereign bond yields during COVID-19
论文作者
论文摘要
在这项工作中，我们研究了Covid-19-19大流行对主权债券产量的影响。我们考虑使用网络过滤方法从财务相关性发生的时间变化。这些方法考虑了相关矩阵中链接的子集，这导致网络结构。我们在2010年至2020年期间使用了来自17个欧洲国家的主权债券收益数据。我们发现在Covid-19期间，所有过滤方法中的平均相关性降低。我们还观察到在多个网络中心度度量下的过滤方法之间的独特趋势。然后，我们将经济和健康变量在COVID-19期间内对被过滤网络的重要性联系起来。在指数的随机图模型下，我们能够确定经济群体之间不同过滤方法之间的关键关系。
In this work, we investigate the impact of the COVID-19 pandemic on sovereign bond yields. We consider the temporal changes from financial correlations using network filtering methods. These methods consider a subset of links within the correlation matrix, which gives rise to a network structure. We use sovereign bond yield data from 17 European countries between the 2010 and 2020 period. We find the mean correlation to decrease across all filtering methods during the COVID-19 period. We also observe a distinctive trend between filtering methods under multiple network centrality measures. We then relate the significance of economic and health variables towards filtered networks within the COVID-19 period. Under an exponential random graph model, we are able to identify key relations between economic groups across different filtering methods.
