This paper studies how a bank regulator's aggregate and bank-specific information dis-closure policy affects social welfare. We apply global games to studying an economy where depositors, with strategic complementarities among them, face uncertainties about both aggregate and bank-specific...

One of the main challenges that banks face in modeling operational risk is the instability of risk estimates caused by heavy-tailed and insufficient loss data. To address these issues, we propose a loss scaling method to combine a bank's internal loss data with external loss data of other banks....

In this paper, we compare the performance of two non-parametric methods of classification, Regression Trees (CART) and the newly Multivariate Adaptive Regression Splines (MARS) models, in forecasting bankruptcy. Models are implemented on a large universe of US banks over a complete market cycle...

We study the credit risk of banks in Germany from lending to non-financial firms. We model changes in Expected Credit Loss, which is derived from the guidelines in the IFRS 9 accounting standard. We map the accounting model to a dataset with individual loans as the unit of observation...

This study develops a framework for stress testing the credit exposures of Hong Kong's retail banks to macroeconomic shocks. Macro stress testing is performed with the framework to assess the vulnerability of banks' overall loan portfolios and mortgage exposures. A variety of shocks, similar to...