gravity equations are estimated by Copula-based Markov switching seemingly unrelated regression approach. The best …'s t copula is applied for joint distribution. Analyzing the bilateral trade flow is separated into two situations, namely …

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 …

We consider the problem of estimating the marginals in case there is knowledge on the copula. If the copula is smooth … convergence n-1/2, but a smaller asymptotic variance. In this paper we show that smoothness assumptions on the copula are … necessary: we construct both a (non-smooth) copula and, exploiting the information our copula provides, estimators of the …

For multivariate distributions in the domain of attraction of a max-stable distribution, the tail copula and the stable … similar in structure to the weak limit of the empirical copula process. We extend this multivariate result to continuous … functional data by establishing the asymptotic normality of the estimators of the tail copula,uniformly over all finite subsets …

-distance (MD) and maximum-likelihood (ML) estimators for bivariate parametric copulae. In particular, I consider Cramer …-von-Mises-, Kolmogorov-Smirnov- and L1-variants of the CvM-statistic based on the empirical copula process, Kendall's dependence function and … the copula, the sample size or the location of the parameter, maximum-likelihood yields smaller estimation biases at less …

copula density. Our methodology extends the work of Wu, Wang, and Walker (2015) by introducing dependence from a covariate in …

promising class of models are the hierarchical Archimedean copulae (HAC) that allow for non-exchangeable and non … for stock indices the copula parameter changes dynamically but the hierarchical structure is constant over time …