This paper uses data on bilateral foreign exposures of domestic banking systems in order to construct early warning models for financial crises that take into account cross-country spill-overs of vulnerabilities. The empirical results show that incorporating cross-country financial linkages can...

Macroeconomic imbalances increase the vulnerability of an economy to adverse shocks, which in turn can lead to crises with severe economic and social costs. We propose an early warning model that predicts such crises. We identify a set of macroeconomic indicators capturing domestic and external...

This paper proposes a framework for deriving early-warning models with optimal out-of-sample forecasting properties and applies it to predicting distress in European banks. The main contributions of the paper are threefold. First, the paper introduces a conceptual framework to guide the process...

This study seeks to answer whether it is possible to design an early warning system framework that can signal the risk of fiscal stress in the near future, and what shape such a system should take. To do so, multiple models based on econometric logit and the random forest models are designed and...

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...