This paper investigates leading indicators of systemic banking crises in a panel of 11 EU countries, with a particular focus on Finland. We use quarterly data from 1980Q1 to 2013Q2, in order to create a large number of macro-financial indicators, as well as their various transformations. We make...

This paper presents first steps toward robust models for crisis prediction. We conduct a horse race of conventional statistical methods and more recent machine learning methods as early-warning models. As individual models are in the literature most often built in isolation of other methods, the...

This paper presents first steps toward robust models for crisis prediction. We conduct a horse race of conventional statistical methods and more recent machine learning methods as early-warning models. As individual models are in the literature most often built in isolation of other methods, the...

This paper investigates leading indicators of systemic banking crises in a panel of 11 EU countries, with a particular focus on Finland. We use quarterly data from 1980Q1 to 2013Q2, in order to create a large number of macro-financial indicators, as well as their various transformations. We make...

This paper proposes a general statistical framework for systemic financial stress indices which measure the severity of financial crises on a continuous scale. Several index designs from the financial stress and systemic risk literature can be represented as special cases. We introduce an...

In this paper we propose a composite indicator that measures multidimensional sovereign bond market stress in the euro area as a whole and in individual euro area member states. It integrates measures of credit risk, volatility and liquidity at short-term and long-term bond maturities into a...

In this paper we propose a composite indicator that measures multi-dimensional sovereign bond market stress in the euro area as a whole and in individual euro area member states. It integrates measures of credit risk, volatility and liquidity at short-term and long-term bond maturities into a...

We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870-2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify...

I propose a dynamic general equilibrium model in which strategic interactions between banks and depositors may lead to endogenous bank fragility and slow recovery from crises. When banks' investment decisions are not contractible, depositors form expectations about bank risk-taking and demand a...

I propose a dynamic general equilibrium model in which strategic interactions between banks and depositors may lead to endogenous bank fragility and slow recovery from crises. When banks' investment decisions are not contractible, depositors form expectations about bank risk-taking and demand a...