State dependent correlations in the Vasicek default model

IF 0.6 Q4 STATISTICS & PROBABILITY
A. Metzler
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引用次数: 0

Abstract

Abstract This paper incorporates state dependent correlations (those that vary systematically with the state of the economy) into the Vasicek default model. Other approaches to randomizing correlation in the Vasicek model have either assumed that correlation is independent of the systematic risk factor (zero state dependence) or is an explicit function of the systematic risk factor (perfect state dependence). By contrast, our approach allows for an arbitrary degree of state dependence and includes both zero and perfect state dependence as special cases. This is accomplished by expressing the factor loading as a function of an auxiliary (Gaussian) variable that is correlated with the systematic risk factor. Using Federal Reserve data on delinquency rates we use maximum likelihood to estimate the parameters of the model, and find the empirical degree of state dependence to be quite high (but generally not perfect). We also find that randomizing correlation, without allowing for state dependence, does not improve the empirical performance of the Vasicek model.
Vasicek默认模型中的状态相关关系
本文将状态依赖相关性(那些随着经济状态系统变化的相关性)纳入Vasicek默认模型。Vasicek模型中其他随机化相关性的方法要么假设相关性独立于系统风险因素(零状态依赖),要么假设相关性是系统风险因素的显式函数(完全状态依赖)。相比之下,我们的方法允许任意程度的状态依赖,并将零状态依赖和完全状态依赖作为特殊情况。这是通过将因子负荷表示为与系统风险因子相关的辅助(高斯)变量的函数来实现的。使用美联储关于拖欠率的数据,我们使用最大似然来估计模型的参数,并发现国家依赖的经验程度相当高(但通常不完美)。我们还发现,在不考虑状态依赖的情况下,随机化相关并不能提高Vasicek模型的经验性能。
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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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):  -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations
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