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首页> 外文期刊>The Journal of Risk Model Validation >Asset price bubbles and the quantification of credit risk capital with sensitivity analysis, empirical implementation and an application to stress testing
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Asset price bubbles and the quantification of credit risk capital with sensitivity analysis, empirical implementation and an application to stress testing

机译：资产价格泡沫和信贷风险资本量化的敏感性分析，经验实施以及在压力测试中的应用

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This paper presents an analysis of the impact of asset price bubbles on standard credit risk measures, extending research by Jacobs published in 2015 in which the author constructed a model, provided evidence that asset price bubbles understate economic credit capital and proposed a new credit risk measure that is robust to this bias (the expected holding period credit loss, or EHPCL). We perform a sensitivity analysis of the model parameters on the resulting credit risk measures as well as the changes in their relationship to the constant elasticity of variance (CEV) parameter; this controls the degree of market departure from fair value, illustrating an application of an important model validation procedure. We also perform an exercise in which we calibrate the model to historical equity prices and project credit losses on both baseline and stressed conditions for bubble and nonbubble parameter estimate settings. Through the estimation of the CEV model parameters from a long time series, we find statistically significant evidence that the historical Standard & Poor's index exhibits only mild bubble behavior, but this translates into underestimation of potential extreme credit losses according to standard measures by an order of magnitude. However, while there is still some underestimation of unexpected credit losses under the EHPCL measure, it is of a much lower severity than in the case of traditional measures: it is on the order of 1.5% in the former, compared with tenfold in the latter. However, the degree of relative underestimation of risk due to asset price bubbles is significantly attenuated under stressed parameter settings in our model. The implication of these findings is that risk managers should be wary of measuring tail credit losses according to standard credit risk measures. Alternative measures, such as the EHPCL, should be considered, including benchmarking to stress testing generated credit losses.
机译：本文对资产价格泡沫对标准信用风险度量的影响进行了分析，并扩展了Jacobs在2015年发表的研究，作者建立了一个模型，提供了证据表明资产价格泡沫低估了经济信用资本，并提出了新的信用风险度量对这种偏见（预期的持有期信用损失，或EHPCL）是有力的。我们对所得信用风险度量的模型参数以及它们与恒定弹性方差（CEV）参数之间关系的变化进行敏感性分析；这控制了市场偏离公允价值的程度，说明了重要模型验证程序的应用。我们还执行了一个练习，在该练习中，我们针对泡沫和非泡沫参数估计设置的基线和压力条件，将模型校准为历史股票价格并预测了信用损失。通过对长时间序列的CEV模型参数进行估计，我们发现了具有统计意义的证据，即历史标准普尔指数仅表现出温和的泡沫行为，但这意味着根据标准测度，潜在的极端信用损失被低估了一个数量级。大小。然而，尽管在EHPCL措施下仍会低估意外信用损失，但严重程度要比传统措施低得多：前者约为1.5％，后者则是后者的十倍。 。但是，在我们模型中的压力参数设置下，由于资产价格泡沫引起的相对低估风险的程度大大降低了。这些发现的含义是，风险管理人员应警惕根据标准信用风险衡量标准来衡量拖尾信用损失。应该考虑其他措施，例如EHPCL，包括对压力测试产生的信用损失进行基准测试。

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