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首页> 外文期刊>The Journal of Risk Model Validation >Stress testing and modeling of rating migration under the Vasicek model framework: empirical approaches and technical implementation
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Stress testing and modeling of rating migration under the Vasicek model framework: empirical approaches and technical implementation

机译：在Vasicek模型框架下进行压力迁移和压力评估建模：经验方法和技术实施

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摘要

Under the Vasicek asymptotic single risk factor model, stress testing based on rating transition probability involves three components: the unconditional rating transition matrix, asset correlations and stress testing factor models for systematic downgrade (including default) risk. Conditional transition probability for stress testing given systematic risk factors can be derived accordingly. In this paper, we extend the work of Miu and Ozdemir on stress testing under this transition probability framework by using different asset correlations and different stress testing factor models for each nondefault rating. We propose two Vasicek models for each nondefault rating, one with a single latent factor for rating level asset correlations and another multifactor Vasicek model with a latent effect for systematic downgrade risk. Both models can be fitted effectively by using, for example, the SAS nonlinear mixed procedure. Analytical formulas for conditional transition probabilities are derived. Modeling downgrade risk rather than default risk addresses the issue of low default counts for high-quality ratings. As an illustration, we model the transition probabilities of a corporate portfolio. Portfolio default risk and credit loss under stress scenarios are derived accordingly. Our results show that stress testing models developed in this way demonstrate the desired sensitivity to risk factors that is generally expected.
机译：在Vasicek渐近单风险因子模型下，基于评级转换概率的压力测试涉及三个组成部分：无条件的评级转换矩阵，资产相关性和用于系统降级（包括违约）风险的压力测试因子模型。可以相应地得出给定系统风险因素的压力测试的条件转移概率。在本文中，我们通过对每个非违约等级使用不同的资产相关性和不同的压力测试因子模型，扩展了Miu和Ozdemir在此过渡概率框架下的压力测试工作。对于每种非违约评级，我们建议使用两种Vasicek模型，一种具有用于等级级别资产关联的潜在因素，另一种具有对系统降级风险具有潜在影响的多因素Vasicek模型。通过使用例如SAS非线性混合过程，可以有效地拟合两个模型。推导了条件转移概率的解析公式。对降级风险而不是违约风险进行建模解决了高质量评级的低违约计数问题。作为说明，我们对公司投资组合的转移概率进行建模。据此推导了在压力情景下的投资组合违约风险和信用损失。我们的结果表明，以这种方式开发的压力测试模型证明了对通常预期的风险因素的期望敏感性。

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