Copula-Dependent Defaults in Intensity Models

P. Schönbucher, Dirk Schubert
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引用次数: 329

Abstract

In this paper we present a new approach to incorporate dynamic default dependency in intensity-based default risk models. The model uses an arbitrary default dependency structure which is specified by the Copula of the times of default, this is combined with individual intensity-based models for the defaults of the obligors without loss of the calibration of the individual default-intensity models. The dynamics of the survival probabilities and credit spreads of individual obligors are derived and it is shown that in situations with positive dependence, the default of one obligor causes the credit spreads of the other obligors to jump upwards, as it is experienced empirically in situations with credit contagion. For the Clayton copula these jumps are proportional to the pre-default intensity. If information about other obligors is excluded, the model reduces to a standard intensity model for a single obligor, thus greatly facilitating its calibration. To illustrate the results they are also presented for Archimedean copulae in general, and Gumbel and Clayton copulae in particular. Furthermore it is shown how the default correlation can be calibrated to a Gaussian dependency structure of CreditMetrics-type.
强度模型中的copula依赖默认值
本文提出了一种在基于强度的违约风险模型中引入动态违约依赖的新方法。该模型使用由违约次数的Copula指定的任意违约依赖结构,该结构与基于个体强度的债务人违约模型相结合,而不会丢失个体违约强度模型的校准。推导了单个债务人的生存概率和信用利差的动态,并表明,在正依赖的情况下,一个债务人的违约导致其他债务人的信用利差向上跳升,正如在信用传染情况下的经验经验一样。对于克莱顿联结,这些跳跃与违约前的强度成正比。如果排除其他债务人的信息,该模型将简化为单个债务人的标准强度模型,从而大大方便了其校准。为了说明这些结果,我们还介绍了阿基米德copulae的一般情况,特别是Gumbel和Clayton copulae。此外,它还显示了如何将默认相关性校准为creditmetrics类型的高斯依赖结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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