Copulas and Temporal Dependence

Brendan Beare

University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego

Abstract: An emerging literature in time series econometrics concerns the modeling of potentially nonlinear temporal dependence in stationary Markov chains using copula functions. We obtain conditions that imply a geometric rate of mixing in models of this kind. A geometric rate of beta-mixing is shown to obtain under a rather strong condition that rules out asymmetry and tail dependence in the copula function. Rho-mixing, which implies a geometric rate of alpha-mixing, is obtained under a much weaker condition. We verify one or both of these conditions for a range of parametric copula functions that are opular in applied work.

Keywords: copula; Markov chain; maximal correlation; mean square contingency; mixing; canonical correlation; tail dependence (search for similar items in EconPapers)
Date: 2008-09-22
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Copulas and Temporal Dependence (2010)
Working Paper: Copulas and Temporal Dependence (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:cdl:ucsdec:qt2880q2jq

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