Parameterization of Copulas and Covariance Decay of Stochastic Processes

Abstract

In this work we study the problem of constructing stochastic processes with a predetermined covariance decay by parameterizing its marginals and a given family of copulas. We show that the proposed methodology is compatibility-free and present several examples to illustrate the theory, including the important Gaussian and Euclidean families of copulas. We associate the theory to common applied time series models.

References in corpus (3)

• Efficient estimation of copula-based semiparametric Markov models
• Copulas for Markovian dependence
• On the behavior of the DFA and DCCA in trend-stationary processes