Dependence and mixing for perturbations of copula-based Markov chains

Martial Longla, Mathias Muia Nthiani and Fidel Djongreba Ndikwa

Statistics & Probability Letters, 2022, vol. 180, issue C

Abstract: This paper explores the impact of perturbations of copulas on dependence properties of the Markov chains they generate. We use an observation that is valid for convex combinations of copulas to establish sufficient conditions for the mixing coefficients ρn, αn and some other measures of association. New copula families are derived based on perturbations of copulas and their multivariate analogs for n-copulas are provided in general. Several families of copulas can be constructed from the provided framework.

Keywords: Perturbation; Central limit theorem; Copulas; Mixing rates; Dependence coefficients (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.spl.2021.109239

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