While there is substantial need for dependence models in higher dimensions, most existing models quickly become rather restrictive and barely balance parsimony and flexibility. Hierarchical constructions may improve on that by grouping variables in different levels. In this paper, the new class of hierarchical Kendall copulas is proposed and discussed. Hierarchical Kendall copulas are built up ...

A copula is a function which joins or “couples” a multivariate distribution function to its one-dimensional marginal distribution functions. The word “copula” was first used in a mathematical or statistical sense by Sklar (1959) in the theorem which bears his name (see the next section). But the functions themselves predate the use of the term, appearing in the work of Hoeffding, Fréchet, Dall’...

In this paper we address the problem of a-migrativity (for a fixed a) for semicopulas, copulas and quasi-copulas. We introduce the concept of an a-sum of semicopulas. This new concept allows us to completely characterize a-migrative semicopulas and copulas. Moreover, a-sums also provide a means to obtain a partial characterization of a-migrative quasicopulas. 2010 Elsevier Inc. All rights reser...

This paper studies the general multivariate dependence of a random vector using associated copulas. We extend definitions and results of positive dependence to the general dependence case. This includes associated tail dependence functions and associated tail dependence coefficients. We derive the relationships among associated copulas and study the associated copulas of the perfect dependence ...

In this paper we establish the convergence of the vine copulas estimator and prove that all vine copula estimator have comparable asymptotic variance. We make these proofs under weaker hypothesis than that of the framework usually considered in the literature. Namely, we lift the conditional independence hypothesis through the use of conditional copulas. We also exhibit the underlying tree stru...

One of the main problems in credit risk management is the correlated default. In large portfolios, computing the default dependencies among issuers is an essential part in quantifying the portfolio's credit. The most important problems related to credit risk management are understanding the complex dependence structure of the associated variables and lacking the data. This paper aims at introdu...

The new class of matrix-tilted Archimedean copulas is introduced. It combines properties and elliptical by introducing a tilting matrix in the stochastic representation copulas, similar to Cholesky factor for copulas. Basic this copula construction are discussed further extension outlined.

This paper investigates the volatility and dependence of Chinese tourism demand for Singapore, Malaysia, and Thailand (SMT) destinations, using the vine copula based auto regression moving average-generalized autoregressive conditional heteroskedasticity (ARMA-GARCH) model. It is found that a jolt to the tourist flow can have long-standing ramifications for the SMT countries. The estimation of ...

The construction of distributions with given marginals has been a problem of interest to statisticians for many years. Today, in view of Sklar’s theorem [25, 26], this problem can be reduced to the construction of a copula. Copulas are a special type of aggregation functions, and nowadays are of interest in fuzzy set theory [5, 6, 12, 14, 16]. Nelsen [22] summarizes different methods of constru...

In this paper discrete quasi-copulas (defined on a square grid I n of [0,1]) are studied and it is proved that they can be represented by means of a special class of matrices with entries in [-1,1]. Special considerations are made for the case of irreducible discrete quasi-copulas (those with range In) defined on the finite chain In, showing that they can be represented through Alternating-Sign...