We estimate default measures for US banks using a model capable of handling volatility clustering like those observed during the Global Financial Crisis (GFC). In order to account for the time variation in volatility, we adapted a GARCH option pricing model which extends the seminal structural approach of default by Merton (J Finance 29(2):449, 1974) and calculated “distance to default” indicators that respond to heightened market developments. With its richer volatility dynamics, our results better reflect higher expected default probabilities precipitated by the GFC. The diagnostics show that the model generally outperforms standard models of default and offers relatively good indicators in assessing bank failures.

我们使用能够处理波动性聚类的模型（如在全球金融危机（GFC）期间观察到的模型）来估计美国银行的默认度量。为了考虑波动率的时间变化，我们采用了GARCH期权定价模型，该模型扩展了Merton的违约的主要结构方法（J Finance 29（2）：449，1974），并计算了响应的“违约距离”指标加快市场发展。凭借其更丰富的波动性动态，我们的结果更好地反映了GFC沉淀出的更高的预期违约概率。诊断表明，该模型通常优于默认的默认模型，并在评估银行故障方面提供了相对较好的指标。