A bivariate integer-valued autoregressive process of order 1 (BINAR(I)) with copula-joint innovations is studied. Different parameter estimation methods are analyzed and compared via Monte Carlo simulations with emphasis on estimation of the copula dependence parameter. An empirical application on defaulted and non-defaulted loan data is carried out using different combinations of copula functions and marginal distribution functions covering the cases where both marginal distributions are from the same family, as well as the case where they are from different distribution families
Copulas are full measures of dependence among random variables. They are increasingly popular among...
We define a copula process which describes the dependencies between arbitrarily many random variable...
In this paper we provide a review of copula theory with applications to finance. We illustrate the i...
Applications of Copulas in Loan Modelling. Copula applications for discrete data with autocorrelatio...
Integer-valued time series comprising count observations at regular time intervals can be observed i...
Integer-valued time series comprising count observations at regular time intervals can be observed i...
A class of bivariate integer-valued time series models was constructed via copula theory. Each serie...
We are studying linear and log-linear models for multivariate count time series data with Poisson ma...
We propose a new dynamic copula model where the parameter characterizing dependence follows an autor...
We propose a new dynamic copula model in which the parameter characterizing dependence follows an au...
Analysis of multivariate time series is a common problem in areas like finance and eco-nomics. The c...
We propose a new family of bivariate nonnegative integer-autoregressive (BINAR) models for count pro...
We define a copula process which describes the dependencies between arbitrarily many random variable...
This paper studies the estimation of copula-based semi parametric stationary Markov models. Describe...
Purpose – This paper aims to statistically model the serial dependence in the first and second momen...
Copulas are full measures of dependence among random variables. They are increasingly popular among...
We define a copula process which describes the dependencies between arbitrarily many random variable...
In this paper we provide a review of copula theory with applications to finance. We illustrate the i...
Applications of Copulas in Loan Modelling. Copula applications for discrete data with autocorrelatio...
Integer-valued time series comprising count observations at regular time intervals can be observed i...
Integer-valued time series comprising count observations at regular time intervals can be observed i...
A class of bivariate integer-valued time series models was constructed via copula theory. Each serie...
We are studying linear and log-linear models for multivariate count time series data with Poisson ma...
We propose a new dynamic copula model where the parameter characterizing dependence follows an autor...
We propose a new dynamic copula model in which the parameter characterizing dependence follows an au...
Analysis of multivariate time series is a common problem in areas like finance and eco-nomics. The c...
We propose a new family of bivariate nonnegative integer-autoregressive (BINAR) models for count pro...
We define a copula process which describes the dependencies between arbitrarily many random variable...
This paper studies the estimation of copula-based semi parametric stationary Markov models. Describe...
Purpose – This paper aims to statistically model the serial dependence in the first and second momen...
Copulas are full measures of dependence among random variables. They are increasingly popular among...
We define a copula process which describes the dependencies between arbitrarily many random variable...
In this paper we provide a review of copula theory with applications to finance. We illustrate the i...