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...

Banks increasingly use short-term wholesale funds to supplement traditional retail deposits. Existing literature mainly points to the "bright side" of wholesale funding: sophisticated financiers can monitor banks, disciplining bad but refinancing good ones. This paper models a "dark side" of...

We offer a theory of financial c ontagion b ased o n t he i nformation c hoice o f i nvestors after observing a financial crisis e lsewhere. We study global coordination games of regime change in two regions linked by an initially unobserved macro shock. A crisis in region 1 is a wake-up call to...

We propose the CoJPoD, a novel framework explicitly linking the cross-sectional and cyclical dimensions of systemic risk. In this framework, banking sector distress in the form of the joint probability of default of financial intermediaries (reflecting contagion from both direct and indirect...

This paper studies optimal financial policy in a world where the financial sector can become excessively optimistic. I decompose the welfare effects of bank capital regulation to demonstrate the effects of exuberance and its interaction with incentive problems in banking. The optimal policy...

We use financial accounts data at sector level to construct financial networks for individual euro area countries. We then connect the country-level networks to one large “Macro Network”, using information on cross-border linkages between the national banking sectors. We then evaluate the...

Why did the shadow banking sectors in the US and the euro area expand in the decade before the financial crisis and what are the implications for systemic risk and macro-prudential policy? This paper examines these issues with a model of the financial sector where the size of the shadow banking...

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...

We propose a novel observation-driven finite mixture model for the study of banking data. The model accommodates time-varying component means and covariance matrices, normal and Student's t distributed mixtures, and economic determinants of time-varying parameters. Monte Carlo experiments...

We propose a dynamic clustering model for uncovering latent time-varying group structures in multivariate panel data. The model is dynamic in three ways. First, the cluster location and scale matrices are time-varying to track gradual changes in cluster characteristics over time. Second, all...