Copulas and Temporal Dependence

An emerging literature in time series econometrics concerns the modeling of potentially nonlinear temporal dependence in stationary Markov chains using copula functions. We obtain sufficient conditions for a geometric rate of mixing in models of this kind. Geometric β-mixing is established under a ... Ausführliche Beschreibung

1. Person: Beare, Brendan K.
Quelle: in Econometrica : journal of the Econometric Society, an international society for the advancement of economic theory in its relation to statistics and mathematics Vol. 78, No. 1 (2010), p. 395-410
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Format: Online-Artikel
Sprache: English
Veröffentlicht: 2010
Beschreibung: Online-Ressource
Schlagworte: research-article
Copula
Markov chain
maximal correlation
mean square contingency
mixing
canonical correlation
tail dependence
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Anmerkung: Copyright: Copyright 2010 The Econometric Society
Zusammenfassung: An emerging literature in time series econometrics concerns the modeling of potentially nonlinear temporal dependence in stationary Markov chains using copula functions. We obtain sufficient conditions for a geometric rate of mixing in models of this kind. Geometric β-mixing is established under a rather strong sufficient condition that rules out asymmetry and tail dependence in the copula function. Geometric ρ-mixing is obtained under a weaker condition that permits both asymmetry and tail dependence. We verify one or both of these conditions for a range of parametric copula functions that are popular in applied work.
ISSN: 1468-0262

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