论文标题
基于葡萄藤的有条件推论，并申请了公司债券的信贷差异数据
Conditional Inferences Based on Vine Copulas with Applications to Credit Spread Data of Corporate Bonds
论文作者
论文摘要
了解公司债券信贷差异的依赖关系对于风险管理很重要。具有尾部依赖性的藤蔓copula模型用于分析中国公司债券的信用点差数据，了解不同部门之间的依赖性并执行条件推断。它显示了尾巴依赖的效果如何影响风险转移，或者给出一个变量的条件分布是极端的。与线性回归相比，葡萄藤模型还提供了更准确的交叉预测结果。这些有条件的推理技术是分析由来自各个部门的公司债券组成的投资组合的债券信用差异的统计贡献。
Understanding the dependence relationship of credit spreads of corporate bonds is important for risk management. Vine copula models with tail dependence are used to analyze a credit spread dataset of Chinese corporate bonds, understand the dependence among different sectors and perform conditional inferences. It is shown how the effect of tail dependence affects risk transfer, or the conditional distributions given one variable is extreme. Vine copula models also provide more accurate cross prediction results compared with linear regressions. These conditional inference techniques are a statistical contribution for analysis of bond credit spreads of investment portfolios consisting of corporate bonds from various sectors.
