This paper evaluates the impact of the March 2020 European Central Bank recommendation that banks do not pay dividends or buy back shares on their market values. It documents a causal negative impact on bank share prices of around 7% during the two weeks following its announcement. The...

Using a difference-in-differences approach and relying on conftdential supervisory data and an unique proprietary data set available at the European Central Bank related to the 2016 EU-wide stress test, this paper presents novel empirical evidence that supervisory scrutiny associated to stress...

This paper provides a first empirical analysis of the impact of the European Central Bank's (ECB's) climate-risk-related supervisory efforts on (i) climate risk exposure and related risk management of banks; and (ii) on the induced shifts in banks' portfolio choices with regard to additional...

The results of this paper provide empirical evidence that regulatory capital ratios drive bank Credit Default Swaps (CDS) and that markets react more to changes in capital requirements if implemented via direct adjustments to Pillar 1 risk weights than imposed as a percentage of Risk-Weighted...

Using a unique dataset of the Euro area and the U.S. bank lending standards, we find that low (monetary policy) short-term interest rates soften standards, for household and corporate loans. This softening - especially for mortgages - is amplified by securitization activity, weak supervision for...

We study spillovers from bank to sovereign risk in the euro area using difference specifications around the European Central Bank's release of stress test results for 130 significant banks on October 26, 2014. We document that following this information release bank equity prices in stressed...

We analyse the interaction between monetary and macroprudential policies in the euro area by means of a two-country DSGE model with financial frictions and cross-border spillover effects. We calibrate the model for the four largest euro area countries (i.e. Germany, France, Italy, and Spain),...

Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our...