A copula-based method to integrate a real vector-valued function, obtaining a single real number, is discussed. Special attention is paid to the case when the underlying universe is finite. The integral considered here is shown to be an extension of [0, 1]-valued copula-based universal integrals.

Consider semiparametric bivariate copula models in which the family of copula functions is parametrized by a Euclidean parameter of interest and in which the two unknown marginal distributions are the in nite dimensional nuisance parameters The e cient score for can be characterized in terms of the solutions of two coupled Sturm Liouville equations In case the family of copula functions corresp...

In this paper, we address the concept of conditional independence between two random variables X and Y given entity Θ. We identify impact on analytic form predictive 2-copula Y. obtain a representation in terms functions associated with copulas Θ Through infinite exchangeable sequences amplify validity our results, obtaining copula only one these quantity

Given a bivariate distribution, the set of canonical correlations and functions is in general finite or countable. By using an inner product between two functions via an extension of the covariance, we find all the canonical correlations and functions for the so-called Cuadras-Augé copula and prove the continuous dimensionality of this distribution.

This paper uses copula functions in order to evaluate tail probabilities and market risk trade-offs at a given confidence level, dropping the joint normality assumption on returns. Copulas enable to represent distribution functions separating the marginal distributions from the association structure. We present an application to two stock market indices: for each market we recover the marginal ...

This paper examines the hedging effectiveness of gold futures for the stock market in minimizing variance and downside risks, including value at risk and expected shortfall using data from the Iran emerging capital market during four different sub-periods from December 2008 to August 2018. We employ dynamic conditional correlation models including VARMA-BGARCH (DCC, ADCC, BEKK, and ABEKK) and c...

This paper suggests a new technique to construct first order Markov processes using products of copula functions, in the spirit of Darsow et al. (1992). The approach requires the definition of: i) a sequence of distribution functions of the increments of the process; ii) a sequence of copula functions representing dependence between each increment of the process and the corresponding level of t...

‎One of the most useful tools for handling multivariate distributions of dependent variables in terms of their marginal distribution is a copula function‎. ‎The copula families capture a fair amount of attention due to their applicability and flexibility in describing the non-Gaussian spatial dependent data‎. ‎The particular properties of the spatial copula are rarely ...

Using distributed generations (DGs) with optimal scheduling and optimal distribution feeder reconfiguration (DFR) are two aspects that can improve efficiency as well as technical and economic features of microgrids (MGs). This work presents a stochastic copula scenario-based framework to jointly carry out optimal scheduling of DGs and DFR. This framework takes into account non-dispatchable and ...

Abstract A prominent example of a perturbation the bivariate product copula (which characterizes stochastic independence) is parametric family Eyraud-Farlie-Gumbel-Morgenstern copulas which allows small dependencies to be modeled. We introduce and discuss several perturbations, some them perturbing copula, while others perturb general copulas. particularly interesting case based on two function...