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 …

. Nevertheless it is not very often consistent with the real data. Copulae allows for an extension of the classical time series … models to nonelliptically distributed residuals. In this paper we apply different copulae to the calculation of the static … and dynamic Value-at-Risk of portfolio returns and Profit-and-Loss function. In our findings copula based multivariate …

This paper make an overview of the copula theory from a practical side. We consider different methods of copula … Gaussian copulae but also Hierarchical Archimedean Copulae. Afterwards we provide an empirical part to support the theory. …

representation as a time-varying heavy-tailed copula which is particularly useful if the interest focuses on dependence structures …

This paper considers efficient estimation of copula-based semiparametric strictly stationary Markov models. These … models are characterized by nonparametric invariant distributions and parametric copula functions; where the copulas capture … maximum likelihood estimation (MLE) for the copula parameter, the invariant distribution and the conditional quantiles. We …

difficult in a nonparametric setting. There we suggest a copula-based solution, which has potential benefits even when the … marginal datasets X and Y are empty. For example, if the copula density is sufficiently smooth in the region where we wish to … if the marginals are close to being independent. We suggest using wavelet estimators to approximate the copula density …

bivariate distribution. The versatility arising from inserting GTL marginal distributions into copula-constructed bivariate … expenditures to speeding tickets and international disputes illustrate the value of the proposed GTL-copula estimator. …