We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common...

We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common...

We propose a dynamic semi-parametric framework to study time variation in tail parameters. The framework builds on the Generalized Pareto Distribution (GPD) for modeling peaks over thresholds as in Extreme Value Theory, but casts the model in a conditional framework to allow for time-variation...

We propose an empirical framework to assess joint and conditional probabilities of credit events from CDS prices observed in the market. Our model is based on a dynamic skewed-t distribution that captures many salient features of CDS data, including skewed and heavy-tailed changes in the price...

We address the question to what extent a central bank can de-risk its balance sheet by unconventional monetary policy operations. To this end, we propose a novel risk measurement framework to empirically study the time-variation in central bank portfolio credit risks associated with such...

We propose a two-stage estimation procedure to identify the effects of time-invariant regressors in a dynamic version of the Hausman-Taylor model. We first estimate the coefficients of the time-varying regressors and subsequently regress the first-stage residuals on the time-invariant regressors...

We study the impact of increasingly negative central bank policy rates on banks' propensity to become undercapitalized in a financial crisis ('SRisk'). We find that the risk impact of negative rates is moderate, and depends on banks' business models: Banks with diversified income streams are...

We address the question to what extent a central bank can de-risk its balance sheet by unconventional monetary policy operations. To this end, we propose a novel risk measurement framework to empirically study the time-variation in central bank portfolio credit risks associated with such...

We propose an empirical framework to assess joint and conditional probabilities of credit events from CDS prices observed in the market. Our model is based on a dynamic skewed-t distribution that captures many salient features of CDS data, including skewed and heavy-tailed changes in the price...

We develop a novel high-dimensional non-Gaussian modeling framework to infer measures of conditional and joint default risk for numerous financial sector firms. The model is based on a dynamic Generalized Hyperbolic Skewed-t block-equicorrelation copula with time-varying volatility and...