The CreditRisk model has been widely used for calculating the loss distribution of a credit portfolio. However, its basic assumption of independent risk factors is not consistent with reality. Although the dependent structure can be mimicked by setting factor weights, a reasonable way to introduce correlated risk factors is needed. In this paper, an extension of the CreditRisk model, called the mixed vector model, is proposed. This model incorporates some common background factors with positive and negative correlations, so it can accommodate the complicated dependence structure of risk factors. The mixed vector model can rebuild the negative correlations better than other extended CreditRisk models. Moreover, it can be translated into the original CreditRisk framework with conditionally independent risk factors, so the numerical algorithm for calculating the loss distribution for the CreditRisk model can be reused with little modification.

中文翻译：

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使用 CreditRisk+ 对相关风险因素进行建模

CreditRisk 模型已被广泛用于计算信用组合的损失分布。然而，其对独立危险因素的基本假设与现实不符。尽管可以通过设置因子权重来模拟依赖结构，但需要一种引入相关风险因子的合理方法。在本文中，提出了 CreditRisk 模型的扩展，称为混合向量模型。该模型融合了一些具有正相关和负相关的常见背景因素，因此可以适应风险因素复杂的依赖结构。混合向量模型可以比其他扩展的 CreditRisk 模型更好地重建负相关。此外，它可以转化为具有条件独立风险因素的原始 CreditRisk 框架，