This paper develops an empirical procedure for analyzing the impact of model misspecification and calibration errors on measures of portfolio credit risk. When applied to large simulated portfolios with realistic characteristics, this procedure reveals that violations of key assumptions of the...

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...

Are there simple yet reliable indicators of banks' systemic importance? In addressing this question, this article explores three model-based measures of systemic importance and finds that bank size helps approximate each of them. A bank's total interbank lending and borrowing provide useful...

We develop a measure of systemic importance that accounts for the extent to which a bank propagates shocks across the banking system and is vulnerable to propagated shocks. Based on Shapley values, this measure gauges the contribution of interconnected banks to systemic risk, in contrast to...

Why should risk management systems account for parameter uncertainty? In order to answer this question, this paper lets an investor in a credit portfolio face non-diversifiable estimation-driven uncertainty about two parameters: probability of default and asset-return correlation. Bayesian...