We investigate whether banks actively manage their exposure to interest rate risk in the short run. Using bank-level data of German banks for the period 2011Q4- 2017Q2, we find evidence that banks actively manage their interest rate risk exposure in their banking books: They take account of...

Carrying out interbank contagion simulations for the German banking sector for the period from the first quarter of 2008 to the second quarter of 2011, we obtain the following results: (i) The system becomes less vulnerable to direct interbank contagion over time. (ii) The loss distribution for...

Using a unique data set on German banks' sector specific loan exposures to the real economy and the corresponding write-offs and write-downs, we examine the impact of loan portfolio sector concentration on credit risk. By controlling for common risk factors, we separate the bank-specific...

Using unique data sets on German banks, we decompose their net interest margin and quantify the different components by estimating the costs of the various functions they perform. We investigate three major functions: namely, liquidity and payment management for the customers, the bearing of...

This paper investigates contagion at the German interbank market under the assumption of a stochastic loss given default (LGD). We combine a unique data set about the LGD of interbank loans with data about interbank exposures. We find that the frequency distribution of the LGD is u-shaped. Under...

Using a unique data set on German banks' loans to the German real economy, we investigate banks' credit risk. This data set includes the volume of loans per bank and industry as well as the corresponding write-downs. Our empirical study for the period 2003-2011 yields the following results: (i)...

Using detailed data of all German banks, we find that banks which have suffered heavy credit losses reduce their corporate lending business by 1.32 euro for each euro lost; with 95% confidence, the effect is between 0.85 and 1.80 euros. This sensitivity is in line with (quite heterogeneous)...