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Re-examination of international bond market dependence: Evidence from a pair copula approach

机译:重新审查国际债券市场依赖性:来自一对拷贝的方法

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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, Germany, 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 inter-connected 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.
机译:财务文献提供了有关在发达国家和新兴国家的国际债券市场之间依赖的实质性证据。该领域的早期作品是基于线性模型和多变量加型模型。基于这些模型的局限,本文重新研究了美国,英国,日本,德国,加拿大,法国,意大利,澳大利亚和欧元区的政府债券市场之间的非线性,多元和尾依赖结构。 1970年1月至2019年2月采用ARMA-GARCH基对COPULA模型。我们发现,我们样本中的债券市场倾向于在积极的冲击和较低的尾部依赖性方面具有占据上尾依赖性。估计的C-VINE显示欧元区的平均依赖最高。 D-VINE,具有最佳链依赖性结构,显示了英国,美国,意大利,日本,欧元区,法国,加拿大,德国和澳大利亚的最佳连通顺序。 R-VINE Copula结果强调了所选经济体之间存在的债券市场关系的复杂动态。估计的R-VINE显示欧元区,德国和澳大利亚是最多连接的节点。所有国家的债券市场的多变量分布结构(相互依赖性)与C葡萄藤,D-VINE和R-VINE Copulas进行了建模。在本申请中,R-VINE Copula允许所有债券市场的详细建模,因此为所有市场之间的相互依存性提供更准确的良好良好和均方误差。鉴于债券市场的波动性变化,我们使用时变的Copulas进行额外的测试,并发现所检查的债券市场之间的依赖结构与动态依赖性参数图揭示依赖结构的性质是强烈的在危机期间。

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