Modelling the link between the global macro-financial factors and firms’ default probabilities constitutes an elementary part of financial sector stress-testing frameworks. Using the Global Vector Autoregressive(GVAR) model and constructing a linking satellite equation for the firm-level...

In 2001, government guarantees for savings banks in Germany were removed following a law suit. We use this natural experiment to examine the effect of government guarantees on bank risk taking, using a large data set of matched bank/borrower information. The results suggest that banks whose...

Credit risk models used in quantitative risk management treat credit risk analysis conceptually like a single person decision problem. From this perspective an exogenous source of risk drives the fundamental parameters of credit risk: probability of default, exposure at default and the recovery...

Using a novel panel data set we study the macroeconomic determinants of nonperforming loans (NPLs) across 75 countries during the past decade. According to our dynamic panel estimates, the following variables are found to significantly affect NPL ratios: real GDP growth, share prices, the...

Following the financial crisis, the share of non-performing loans has significantly increased, while the regulatory guidelines on the Internal-Ratings Based (IRB) approach for capital adequacy calculation related to defaulted exposures remains too general. As a result, the high-risk nature of...

Credit risk models used in quantitative risk management treat credit risk analysis conceptually like a single person decision problem. From this perspective an exogenous source of risk drives the fundamental parameters of credit risk: probability of default, exposure at default and the recovery...

In 2001, government guarantees for savings banks in Germany were removed following a law suit. We use this natural experiment to examine the effect of government guarantees on bank risk taking, using a large data set of matched bank/borrower information. The results suggest that banks whose...

We propose an empirical framework to assess joint and conditional probabilities of credit events from CDS prices observed in the market. Our model is based on a dynamic skewed-t distribution that captures many salient features of CDS data, including skewed and heavy-tailed changes in the price...

This paper explores how the need to transition to a low-carbon economy influences firm credit risk. It develops a novel dataset which augments data on firms’ green-house gas emissions over time with information on climate disclosure practices and forward-looking emission reduction targets,...

We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common...