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摘要翻译：
违约事件的压力情景对信贷组合损失分布的影响可以通过确定以这些事件为条件的损失分布来评估。虽然用蒙特卡罗模拟方法估计违约事件条件下的损失分布在概念上很容易，但对于两个或多个同时发生的违约事件来说，这就变得不切实际了，因为条件事件极其罕见。对于具有独立随机损失给定违约分布的CreditRisk+投资组合模型，我们给出了一种计算条件损失分布的解析方法。这种情况下的解析解可以用来检查条件损失分布近似的准确性，从而无条件模型在有压力的输入违约概率(PDs)下运行。结果证明这个近似是无偏的。然而，数值例子表明，这种近似可能严重不准确，但这种不准确导致了对尾部损失的高估，因此这种方法在保守方面是错误的。
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英文标题：
《The two defaults scenario for stressing credit portfolio loss
distributions》
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作者：
Dirk Tasche
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最新提交年份：
2015
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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英文摘要：
The impact of a stress scenario of default events on the loss distribution of a credit portfolio can be assessed by determining the loss distribution conditional on these events. While it is conceptually easy to estimate loss distributions conditional on default events by means of Monte Carlo simulation, it becomes impractical for two or more simultaneous defaults as then the conditioning event is extremely rare. We provide an analytical approach to the calculation of the conditional loss distribution for the CreditRisk+ portfolio model with independent random loss given default distributions. The analytical solution for this case can be used to check the accuracy of an approximation to the conditional loss distribution whereby the unconditional model is run with stressed input probabilities of default (PDs). It turns out that this approximation is unbiased. Numerical examples, however, suggest that the approximation may be seriously inaccurate but that the inaccuracy leads to overestimation of tail losses and hence the approach errs on the conservative side.
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PDF链接：
https://arxiv.org/pdf/1002.2604
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