This paper discusses the uses of copulas for modelling multivariate density functions and explains how copula methods can be applied to the study of macroeconomic relationships. It suggests that copulas are well suited to the study of these relationships and can sometimes shed new light on them. It then sets out the main steps of copula methodology and provides an illustrative application to th...

In this paper we deal with the identification of dependencies between time series of equity returns. Marginal distribution functions are assumed to be known, and a bivariate chi-square test of fit is applied in a fully parametric copula approach. Several families of copulas are fitted and compared with Spanish stock market data. The results show that the t-copula generally outperforms other dep...

We develop sampling algorithms for multivariate Archimedean copulas. For exchangeable copulas, where there is only one generating function, we first analyse the distribution of the copula itself, deriving a number of integral representations and a generating function representation. One of the integral representations is related, by a form of convolution, to the distribution whose Laplace trans...

This paper presents an analysis of Irish clefting couched within LexicalFunctional Grammar. In Irish, cleft sentences are formed using two syntactic permutations. First, a copula is introduced, taking the clefted phrase or word as a predicate. Second, a relative clause is formed containing the remaining material of the original sentence. This basic pattern is valid across a variety of languages...

Copula functions can be utilized in financial applications to determine the dependence structure of asset returns portfolio. Empirical evidence has proved inadequacy multi-normal distribution, traditionally adopted model distribution. employed a flexible way for building efficient algorithms and simulate more adequate distribution assets. This paper aims describe some simple statistical procedu...

This paper presents the role of copula functions in the theory of aggregation operators and an axiomatic characterization of Archimedean aggregation functions. In this context we are focusing our attention about several properties of aggregation functions, like supermodularity and Schur-concavity.

A useful method for representing Bayesian classifiers is through discriminant functions. Here, using copula functions, we propose a new model for discriminants. This model provides a rich and generalized class of decision boundaries. These decision boundaries significantly boost the classification accuracy especially for high dimensional feature spaces. We strengthen our analysis through simula...

In this paper we address the problem of option ranking in qualitative evaluation models. Current approaches make the assumptions that when qualitative data are suitably mapped into discrete quantitative data, they form monotone or closely linear tabular value functions. Although the power of using monotone and linear functions to model decision maker’’s preferences is impressive, there are many...