We investigate the puzzle in the literature that various parametric loss given default (LGD) statistical models perform similarly by comparing their performance in a simulation framework. We find that, even using the full set of explanatory variables from the assumed data generating process,...

We propose an alternative approach to the modeling of the positive dependence between the probability of default and the loss given default in a portfolio of exposures, using a bivariate urn process. The model combines the power of Bayesian nonparametrics and statistical learning, allowing for...

In this study, we consider the construction of through-the-cycle ("TTC") PD models designed for credit underwriting uses and point-in-time ("PIT") PD models suitable for early warning uses, considering which validation elements should be emphasized in each case. We build PD models using a long...

In this paper we study the impact of model uncertainty, which occurs when linking a stress scenario to default probabilities, on reduced-form credit risk stress testing. This type of uncertainty is omnipresent in most macroeconomic stress testing applications due to short time series for banks'...

The paper sought to explore the role of bank capital in mitigating credit risk and promoting financial stability. To achieve this, we constructed a Financial Soundness Index to evaluate financial stability conditions. A Panel Vector Auto Regression Model was employed using annual bank-level data...

The internal ratings-based (IRB) approach maps banks’ risk profiles more adequately than the standardized approach. After switching to IRB, banks’ risk-weighted asset (RWA) densities are thus expected to diverge, especially across countries with different supervisory strictness and risk...

This paper assesses the sensitivity of solvency stress testing results to the choice of credit risk variable and level of data aggregation at which the stress test is conducted. In practice, both choices are often determined by technical considerations, such as data availability. Using data for...