An Analysis of Simultaneous Company Defaults Using a Shot Noise Process
An Analysis of Simultaneous Company Defaults Using a Shot Noise Process
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使用散粒噪声过程分析同时发生的公司违约
DOI：
10.1016/j.jbankfin.2017.04.007
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发表时间：
2017
影响因子：
3.7
通讯作者：
M. Egami and R. Kevkhishvili
中科院分区：
文献类型：
--
作者：
Masahiko Egami;Rusudan Kevkhishvili;M. Egami and R. Kevkhishvili;M. Egami and R. Kevkhishvili
在次贷危机期间，很明显，实用的模型，如单因素高斯Copula模型，低估了公司违约相关性。试图合并默认依赖关系的复杂模型在实践中很难实现。在这项研究中，我们建立了一个公司资产过程的模型，在此基础上，我们使用期权理论方法计算了同时违约概率。在我们的模型中，散粒噪声过程是控制公司资产之间相关性的关键因素。驱动散粒噪声过程的风险因素对行业中的所有公司都是常见的，但散粒噪声参数是假定为公司特定的；因此，每家公司对这一共同风险因素的反应是不同的。我们的模型比通常使用的几何布朗运动资产模型更早地发出财务困境的预警，并预测出更高的同时违约概率。它在计算上也很简单，可以扩展到分析任何有限数量的公司。
During the subprime mortgage crisis, it became apparent that practical models, such as the one-factor Gaussian copula, had underestimated company default correlations. Complex models that attempt to incorporate default dependency are difficult to implement in practice. In this study, we develop a model for a company asset process, based on which we calculate simultaneous default probabilities using an option-theoretic approach. In our model, a shot noise process serves as the key element for controlling correlations among companies’ assets. The risk factor driving the shot noise process is common to all companies in an industry but the shot noise parameters are assumed company-specific; therefore, every company responds differently to this common risk factor. Our model gives earlier warning of financial distress and predicts higher simultaneous default probabilities than commonly used geometric Brownian motion asset model. It is also computationally simple and can be extended to analyze any finite number of companies.