This paper describes a machine learning technique to timely identify cases of individual bank financial distress. Our work represents the first attempt in the literature to develop an early warning system specifically for small European banks. We employ a machine learning technique, and build a...

This paper describes a machine learning technique to timely identify cases of individual bank financial distress. Our work represents the first attempt in the literature to develop an early warning system specifically for small European banks. We employ a machine learning technique, and build a...

Periods of economic and financial stress traditionally give rise to profound changes in economic theory and in the way policy decisions are taken. Motivated by the recent interest in renewing macroeconomics after the global financial crisis, we collected the views of senior central bank staff in...

Periods of economic and financial stress traditionally give rise to profound changes in economic theory and in the way policy decisions are taken. Motivated by the recent interest in renewing macroeconomics after the global financial crisis, we collected the views of senior central bank staff in...

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double-indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in...

We study empirically how competition among high-frequency traders (HFTs) affects their trading behavior and market quality. Our analysis exploits a unique dataset, which allows us to compare environments with and without high-frequency competition, and contains an exogenous event - a tick size...