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On an asymmetric extension of multivariate Archimedean copulas based on quadratic form

Elena Di Bernardino, Didier Rullière (2016)

Dependence Modeling

An important topic in Quantitative Risk Management concerns the modeling of dependence among risk sources and in this regard Archimedean copulas appear to be very useful. However, they exhibit symmetry, which is not always consistent with patterns observed in real world data. We investigate extensions of the Archimedean copula family that make it possible to deal with asymmetry. Our extension is based on the observation that when applied to the copula the inverse function of the generator of an...

On Bartlett's test for correlation between time series

Jiří Anděl, Jaromír Antoch (1998)

Kybernetika

An explicit formula for the correlation coefficient in a two-dimensional AR(1) process is derived. Approximate critical values for the correlation coefficient between two one-dimensional AR(1) processes are tabulated. They are based on Bartlett’s approximation and on an asymptotic distribution derived by McGregor. The results are compared with critical values obtained from a simulation study.

On copulas that generalize semilinear copulas

Juan Fernández Sánchez, Manuel Úbeda-Flores (2012)

Kybernetika

We study a wide class of copulas which generalizes well-known families of copulas, such as the semilinear copulas. We also study corresponding results for the case of quasi-copulas.

On extremal dependence of block vectors

Helena Ferreira, Marta Ferreira (2012)

Kybernetika

Due to globalization and relaxed market regulation, we have assisted to an increasing of extremal dependence in international markets. As a consequence, several measures of tail dependence have been stated in literature in recent years, based on multivariate extreme-value theory. In this paper we present a tail dependence function and an extremal coefficient of dependence between two random vectors that extend existing ones. We shall see that in weakening the usual required dependence allows to...

On measures of concordance.

Marco Scarsini (1984)

Stochastica

We give a general definition of concordance and a set of axioms for measures of concordance. We then consider a family of measures satisfying these axioms. We compare our results with known results, in the discrete case.

On monotone dependence functions of the quantile type

Andrzej Krajka, Dominik Szynal (1995)

Applicationes Mathematicae

We introduce the concept of monotone dependence function of bivariate distributions without moment conditions. Our concept gives, among other things, a characterization of independent and positively (negatively) quadrant dependent random variables.

Optimal solutions of multivariate coupling problems

Ludger Rüschendorf (1995)

Applicationes Mathematicae

Some necessary and some sufficient conditions are established for the explicit construction and characterization of optimal solutions of multivariate transportation (coupling) problems. The proofs are based on ideas from duality theory and nonconvex optimization theory. Applications are given to multivariate optimal coupling problems w.r.t. minimal l p -type metrics, where fairly explicit and complete characterizations of optimal transportation plans (couplings) are obtained. The results are of interest...

Orbital semilinear copulas

Tarad Jwaid, Bernard de Baets, Hans de Meyer (2009)

Kybernetika

We introduce four families of semilinear copulas (i.e. copulas that are linear in at least one coordinate of any point of the unit square) of which the diagonal and opposite diagonal sections are given functions. For each of these families, we provide necessary and sufficient conditions under which given diagonal and opposite diagonal functions can be the diagonal and opposite diagonal sections of a semilinear copula belonging to that family. We focus particular attention on the family of orbital...

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