Re-examination of international bond market dependence: Evidence from a pair copula approach
Keywords: 
International bond markets
Bond markets integration
Copula
Tail dependence
Issue Date: 
2021
Publisher: 
Elsevier
ISSN: 
1057-5219
Note: 
This is an open access article under the CC BY-NC-ND license
Citation: 
Aikins-Abakah, E.J. (Emmanuel Joel); Addo-Jr., E. (Emmanuel); Gil-Alana, L.A. (Luis A.); et al. "Re-examination of international bond market dependence: Evidence from a pair copula approach". International Review of Financial Analysis. (74), 2021, 101678
Abstract
The finance literature provides substantial evidence on the dependence between international bond markets across developed and emerging countries. Early works in this area were based on linear models and multivariate GARCH models. However, based on the limitations of these models this paper re-examines the non-linearity, multivariate and tail dependence structure between government bond markets of the US, UK, Japan, Ger- many, Canada, France, Italy, Australia and the Eurozone, from January 1970 to February 2019 using ARMA- GARCH based pair- copula models. We find that the bond markets in our sample tend to have both upper tail dependence in terms of positive shocks and lower tail dependence in terms of negative shocks. The estimated C-vine shows Eurozone has the highest average dependency. The D-vine, with optimal chain dependency structure shows the best order of connectedness to be the UK, the USA, Italy, Japan, Eurozone, France, Canada, Germany and Australia. The R-vine copula results underline the complex dynamics of bond market relations existing between the selected economies. The estimated R-vine shows Eurozone, Germany and Australia are the most interconnected nodes. The multivariate distribution structure (interdependency) of bond markets for all countries were modelled with the C-vine, D-vine and R-vine copulas. In this application, the R-vine copula allows for detailed modelling of all bond markets and hence provides a more accurate goodness of fit and mean square error for the interdependency between all markets. In light of the changing volatility in bond markets, we conduct additional tests using time-varying copulas and find that the dependence structure among the bond markets examined is time-varying with the dynamic dependence parameter plots revealing that the nature of the dependence structure is intense during crisis periods

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