In this paper, we address two important issues in semiparametric survival model selection for censored data generated by the Archimedean copula family: method of estimating the parametric copulas and data reuse. We demonstrate that for selection among candidate copula models that could all be misspecified, estimators of the parametric copulas based on minimizing the selection criterion function...

A copula is a means of generating an n-variate distribution function from an arbitrary set of n univariate distributions. For the class of portfolio allocators that are risk averse, we use the copula approach to identify a large set of n-variate asset return distributions such that the relative magnitudes of portfolio shares can be ordered according to the reversed hazard rate ordering of the n...

The problem of estimation multivariate survival function under dependent random right-censoring observations is considered. To construct estimators, Archimedean copula functions are used. Consistency properties estimators proved by martingale techniques. possibility application to integral-type functionals discussed.

This paper details the correspondence between various dependence concepts and stochastic orderings for an Archimedean copula Cφ(x, y) = φ −1{φ(x) + φ(y)} and the aging properties of the corresponding life distribution Fφ(t) = 1− φ−1(t). Various applications of the results are given. AMS (2000) subject classification. Primary 62H05, 62H20; secondary 62N05.

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.

Companies in the same industry sector are usually stronger correlated than firms in different sectors, as they are similarly affected by macroeconomic effects, political decisions, and consumer trends. In spite of many stock return models taking account of this fact there are only a few credit default models taking it into consideration. In this paper we present a default model based on nested ...

The copula–entropy theory combines the entropy theory and the copula theory. The entropy theory has been extensively applied to derive the most probable univariate distribution subject to specified constraints by applying the principle of maximum entropy. With the flexibility to model nonlinear dependence structure, parametric copulas (e.g., Archimedean, extreme value, meta-elliptical, etc.) ha...

In this paper, we address risk aggregation and capital allocation problems in the presence of dependence between risks. The structure is defined by a mixed Bernstein copula which represents generalization well-known Archimedean copulas. Using new copula, probability density function cumulative distribution aggregate are obtained. Then, closed-form expressions for basic measures, such as tail va...

In the classical multivariate time series models the residuals are assumed to be normally distributed. However the assumption of normality is rarely consistent with the empirical evidence and leads to possibly incorrect inferences from financial models. The copula theory allows us to extend the classical time series models to nonelliptically distributed residuals. In this paper we analyze the t...

abstract background: keratoconus is a bilateral corneal disease, which one way to cure it is to transplant. the transplantation may be rejected by recipient's immune system, which leads to failure of the graft. this study aimed to analysis the factors affecting bilateral corneal graft rejection based on copula function. methods: a sample of bilateral graft rejection times was assessed. since co...