Group-specific estimations can significantly improve the predictive power of accountingbased rating models. This is shown using a binary logistic regression model applied to the Deutsche Bundesbank's USTAN dataset, which contains 300,000 financial statements provided by German companies for the...

The detection of business-cycle turning points is usually performed with non-linear discrete-regime models such as binary dependent variable (e.g., probit or logit) or Markov-switching methods. The probit model has the drawback that the continuous underlying target variable is discretized, with...

Einleitung in die Ermittlung der Übernahme- und Fusionswahrscheinlichkeit für Akquiseziele in der deutschen Stahlindustrie auf Basis von Finanzkennzahlen -- Methodisch-konzeptionelle Grundlagen zu den eingesetzten Arbeitstechniken und Hypothesen zu Übernahmen und Fusionen -- Identifizierung...

This paper employs an Extreme Value Theory framework to investigate the existence of contagion between European and US banks. The fact that many regulators have no detailed data sets about interbank cross-exposures raises the necessity of finding market-based indicators in order to analyze the...

We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show...