The prices of or spread on credit default swaps (CDS) theoretically represent the pure credit risk of a firm. Callen, Livnat and Segal (2007) note that although the CDS premium is related to credit ratings issued by the rating agencies, rather wide variation in CDS spreads are observed for firms...

Counterpart risk rating is at the heart of the banking business. In the new Basel II regulation, internal ratings have been given a central role. Although much research has been done on external ratings, much less is known about banks´ internal ratings. This paper presents new quantitative...

This paper proposes a machine learning approach to estimate physical forward default intensities. Default probabilities are computed using artificial neural networks to estimate the intensities of the inhomogeneous Poisson processes governing default process. The major contribution to previous...

Credit risk is the main risk in the banking sector and is as such one of key issues for financial stability. We estimate various PD models and use them in the application to credit rating classification. Models include firm specific characteristics and macroeconomic or time effects. By linking...

In banking practice, quantifying the probability of default is one of the most important elements of the lending decision, therefore it is also vital from a financial stability perspective. The aim of our research was to model the probability of default as precisely as possible in the case of...

Cyclicality in the losses of bank loans is important for bank risk management. Because loans have a different risk profile than bonds, evidence of cyclicality in bond losses need not apply to loans. Based on unique data we show that the default rate and loss given default of bank loans share a...