important for banks to construct their risk profile and operate successfully. We use the German Creditreform database and …

financial econometrics. We propose a Tail Event driven Network Quantile Regression (TENQR) model which addresses these three … aspects. More precisely, our framework captures the risk propagation and dynamics in terms of a quantile (or expectile …) autoregression involving network effects quantified through an adjacency matrix. To reflect the nature and risk content of systemic …

modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM … where local estimation windows are fixed on an ad hoc basis …

Risiko verbinden ließe, wenn man nur die Finanzprodukte entsprechend gestaltete, hat sich diese Wahnvorstellung …

The Value-at-Risk calculation reduces the dimensionality of the risk factorspace. The main reasons for such … simple mappings: the mapping on the market index, the principal components model and the model with equally correlated risk …

The Value-at-Risk calculation reduces the dimensionality of the risk factor space. The main reasons for such … simple mappings: the mapping on the market index, the principal components model and the model with equally correlated risk …

The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a …