fundamental characteristic. We compare our empirical findings with a single Gaussian copula, a correlation-weighted average of … Gaussian copulas, the K-copula which directly addresses the nonstationarity of dependencies as a model parameter, and the … skewed Student's t-copula. The K-copula covers the empirical dependence structure on the local scale most adequately, whereas …

promising class of models are the hierarchical Archimedean copulae (HAC) that allow for non-exchangeable and non … for stock indices the copula parameter changes dynam- ically but the hierarchical structure is constant over time …. Interestingly in our exchange rate example both structure and parameters vary dynamically. -- copula ; multivariate distribution …

error terms. The inefficiency and noise terms being dependent, a copula function which reflects the dependence between them …

, conditional quantiles are specified via hierarchical Archimedean copula. The parameters and structure of this copula are …

We introduce a copula-based dynamic model for multivariate processes of (non-negative) high-frequency trading variables … multiplicative error model we map the resulting residuals into a Gaussian domain using a Gaussian copula. Based on high … proposed copula-based transformation is supported by the data and allows capturing (multivariate) dynamics in higher order …

estimation of these two top distributions. We leverage the bivariate parametric/non-parametric copula to extrapolate both income … and wealth distributions from German PHF (Panel on Household Finance) data. The copula modelling potentially reduces the …. The copula estimate can help us to perform out-of-sample prediction on the very top of the tail distribution from one …

smoothed transition regression (LSTR) model where possible threshold endogeneity is addressed based on copula theory. We also …

estimation of these two top distributions by using the best data available for Germany. We leverage the bivariate copula to … model. The copula modelling grants the separability in choosing the estimation domain as well as the parametric … model fit with external validation. The copula estimate can help us to perform out-of-sample prediction on the very top of …

directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We …