An analysis of network filtering methods to sovereign bond yields during COVID-19

TL;DR

This paper examines how COVID-19 affected sovereign bond yields in Europe by analyzing changes in financial correlations through network filtering methods, revealing decreased correlations and key economic relations during the pandemic.

Contribution

It introduces a comprehensive analysis of sovereign bond yield networks during COVID-19 using multiple filtering methods and identifies significant economic and health variable influences.

Findings

Mean correlation decreased during COVID-19 across methods.

Distinct network centrality trends observed during the pandemic.

Key economic relations identified via exponential random graph models.

Abstract

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.