We introduce a general approach to nonlinear quantile regression modelling that is based on the specification of the copula function that defines the dependency structure between the variables of interest. Hence we extend Koenker and Bassett’s [1978] original statement of the quantile regression problem by determining a distribution for the dependent variable Y conditional on the regressors X a...

This paper concerns the application of copula functions in VaR valuation. The copula function is used to model the dependence structure of multivariate assets. After the introduction of the traditional Monte Carlo simulation method and the pure copula method we present a new algorithm based on mixture copula functions and the dependence measure, Spearman’s rho. This new method is used to simula...

The paper considers likelihood-based estimation of multivariate models, in which only marginal distributions are correctly specified. The unknown joint distribution is modelled with a copula function, which may be misspecified. In a GMM framework, we study robustness and efficiency of resulting estimators, propose improvements to existing estimators and discuss tests of copula validity. It is s...

In some past works by the author and collaborators, the notion of ageing function of an exchangeable survival model was introduced and several properties of it were analyzed. Generally, the ageing function turns out to be a semi-copula. Here we focus attention on the special class of survival models whose ageing function is actually a copula. For pairs of models in this class we define a notion...

For a multivariate vector X with discrete components, we construct, by means of explicit randomised transformations of X, multivariate couplings of copula representers U associated to X. As a result, we show that any copula can be constructed in this manner, giving a full probabilistic characterisation of the set of copula functions associated to X. The dependence properties of these copula rep...

Estimation of distribution algorithms based on copula, and a number of different distribution functions were selected as the dimension of the marginal distribution function by applying K-S test. Dynamic K-S test, that is, dynamic adjust frequency of K-S test in different stages. In the estimation of the probability model stage, according to the actual distribution of the dominant group respect...

Heterogeneity of economic agents is emphasized in a new trend of macroeconomics. Accordingly the new emerging discipline requires one to replace the production function, one of key ideas in the conventional economics, by an alternative which can take an explicit account of distribution of firms’ production activities. In this paper we propose a new idea referred to as production copula; a copul...

The univariate Piecing-Together approach (PT) fits a univariate generalized Pareto distribution (GPD) to the upper tail of a given distribution function (df) in a continuous manner. A multivariate extension was established by Aulbach et al. (2011a): The upper tail of a given copula C was cut off and substituted by the upper tail of a multivariate GPD-copula in a continuous manner. The result is...