One of the main goals in non-life insurance is to estimate the claims reserve distribution. A generalized time series model, that allows for modeling the conditional mean and variance of the claim amounts, is proposed for the claims development. On contrary to the classical stochastic reserving...

This paper aims at explanation of the R-package HAC, which provides user friendly methods for dealing with high-dimensional hierarchical Archimedean copulae (HAC). A computationally ecient estimation procedure allows to recover the structure and the parameters of HACs from data. In addition,...

This paper aims at explanation of the R-package HAC, which provides user friendly methods for dealing with high-dimensional hierarchical Archimedean copulae (HAC). A computationally effcient estimation procedure allows to recover the structure and the parameters of HACs from data. In addition,...

This paper aims at explanation of the R-package HAC, which provides user friendly methods for dealing with high-dimensional hierarchical Archimedean copulae (HAC). A computationally effcient estimation procedure allows to recover the structure and the parameters of HACs from data. In addition,...

We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields...

Complex phenomena in environmental sciences can be conveniently represented by several inter-dependent random variables. In order to describe such situations, copula-based models have been studied during the last year. In this paper, we consider a novel family of bivariate copulas, called...

Modelling portfolio credit risk is one of the crucial challenges faced by financial services industry in the last few years. We propose the valuation model of collateralized debt obligations (CDO) based on hierarchical Archimedean copulae (HAC) with up to three parameters, with default...

This study proposes a novel framework for the joint modelling of commodity forward curves. Its key contribution is twofold. First, we introduce a family of dynamic conditional correlation models based on hierarchical Archimedean copulae (HAC-DCC), which are flexible but parsimonious instruments...

This study proposes a novel framework for the joint modelling of commodity forward curves. Its key contribution is twofold. First, dynamic correlation models are applied in this context as part of the modelling scheme. Second, we introduce a family of dynamic conditional correlation models based...

We introduce the notion of realized copula. Based on assumptions of the marginal distri- butions of daily stock returns and a copula family, realized copula is dened as the copula structure materialized in realized covariance estimated from within-day high-frequency data. Copula parameters are...