We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under...

We develop the regime-switching default risk (RSDR) model as a generalization of Merton's default risk (MDR) model. The RSDR model supports an expanded range of asset probability density functions. First, we show using simulation that the RSDR model incorporates sudden changes in asset values...

Credit ratings are commonly used by lenders to assess the default risk, because every credit is connected with a possible loss. If the probability of a default is above a certain threshold, a credit will not be provided. The purpose of this paper is to test whether credit ratings contribute...

Im Mittelpunkt dieses Beitrag stehen Verweildauermodelle und deren Verwendung als Analyseinstrumente für die Bewertung und Berechnung von Kreditausfallrisiken. Verschiedene Möglichkeiten zur Berechnung der Dauer des Nichtausfalls eines Kredites werden dabei vorgestellt. Die hier vorgestellten...

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...

This paper aims to model the probability of a borrower violating an asset value covenant in a shipping bank loan agreement, where the main collateral (the vessel) exhibits very high price volatility. We estimate a logistic regression model on the largest dataset of shipping bank loans examined...

Dynamic models for credit rating transitions are important ingredients for dynamic credit risk analyses. We compare the properties of two such models that have recently been put forward. The models mainly differ in their treatment of systematic risk, which can be modeled either using discrete...

Recent models for credit risk management make use of Hidden Markov Models (HMMs). The HMMs are used to forecast quantiles of corporate default rates. Little research has been done on the quality of such forecasts if the underlying HMM is potentially mis-specified. In this paper, we focus on...