Measuring Portfolio Credit Risk: Modelling Versus Calibration Errors

Abstract

A model-based assessment of credit risk is subject to both specification and calibration errors. Focusing on a well known credit risk model, we propose a methodology for quantifying the relative importance of alternative sources of such errors and apply this methodology to a large data set. We find that flawed calibration of the model can substantially affect the measured level of portfolio credit risk. By contrast, a model mis-specification generally has a limited impact, especially for large, well diversified portfolios.

JEL Classification: C15, G13, G21, G28