论文标题
信用资本需求中模型风险的度量
The measure of model risk in credit capital requirements
论文作者
论文摘要
基于内部评级的方法中的信用资本要求需要对两个关键参数进行校准：默认值和损失违约的可能性。这封信考虑了这两个参数的不确定性，并以基本的方式对这种不确定性进行了建模：它显示了如何在监管资本中计算并正确考虑这种估计风险。 我们分析了两个标准的真实数据集：一个由穆迪评级的所有公司组成，一个仅限于投机级。我们对边际分布和参数依赖性的统计测试模型假设。我们计算估计风险影响，并观察到参数依赖性大大提高了资本需求的尾巴风险。结果令人惊讶，要求增加监管资本的范围38 \％$ - $ 66 \％$。
Credit capital requirements in Internal Rating Based approaches require the calibration of two key parameters: the probability of default and the loss-given-default. This letter considers the uncertainty about these two parameters and models this uncertainty in an elementary way: it shows how this estimation risk can be computed and properly taken into account in regulatory capital. We analyse two standard real datasets: one composed by all corporates rated by Moody's and one limited only to the speculative grade ones. We statistically test model hypotheses on both marginal distributions and parameter dependency. We compute the estimation risk impact and observe that parameter dependency raises substantially the tail risk in capital requirements. The results are striking with a required increase in regulatory capital in the range $38\%$-$66\%$.
