In this paper we develop a general framework to analyze state space models with time-varying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

We assess whether the euro had an impact first on the degree of integration of European financial markets, and, second, on the euro area term structure. We propose two methodologies to measure integration: one relies on time-varying GARCH correlations, and the other one on a regression...

This paper presents a methodology to calculate the Systemic Risk Ranking of financial institutions in the European banking sector using publicly available information. The pro- posed model makes use of the network structure of financial institutions by including the stock return series of all...

This paper presents a methodology to calculate the Systemic Risk Ranking of financial institutions in the European banking sector using publicly available information. The proposed model makes use of the network structure of financial institutions by including the stock return series of all...

We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR, bridge equations) and offers methods to manage data selection and adjust for Covid-19 observations. The toolbox aims at simplifying two key tasks: creating new nowcasting...

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting in ation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions for forecasting in ation with the ability of quantile regression to...

Markow switching models with time-varying means, variances and mixing weights are applied to characterise business cycle variation in the probability distribution and higher order moments of stock returns. This allows us to provide a comprehensive characterization of risk that goes well beyond...