Bank default indicators with volatility clustering (Q2036008)

The authors estimate default measures for US banks using a model capable of handling volatility clustering, like those observed during the Global Financial Crisis. In order to account for the time variation in volatility, they adapted a GARCH option pricing model and calculated ``distance to default'' indicators that respond to heightened market developments. With richer volatility dynamics, their results better reflect higher expected default probabilities precipitated by the Global Financial Crisis. The diagnostics show that the model generally outperforms standard models of default and offers relatively good indicators in assessing bank failures.