The ACR model: a multivariate dynamic mixture autoregression

Frédérique Bec, Anders Rahbek () and Neil Shephard ()
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Anders Rahbek: Department of Economics, University of Copenhagen and Studiestraede 6, DK-1455 Copenhagen K, Denmark

No 2008-11, THEMA Working Papers from THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise

Abstract: In this paper we propose and analyse the Autoregressive Conditional Root (ACR) time series mmodel. It is a multivariate dynamic mixture autoregression which allows for non-stationary epochs. It proves to be an appealing alternative to existing nonlinear models such as e.g. the threshold autoregressive or Markov switching classes of models, which are commonly used to describe non-linear dynamics as implied by arbitrage in presence of transaction costs. Simple conditions on the parameters of the ACR process and its innovations, are shown to imply geometric ergodicity, stationarity and existence of moments. Furthermore, we establish consistency and asymptotic normality of the maximum likelihood estimators in the ACR model. An application to real exchange rate data illustrates the conclusions and analysis.

Keywords: Dynamic mixture vector autoregressive mmodel; autoregressive conditional root model; ACR; regime switching; stochastic unit root; threshold autoregression (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2008
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Journal Article: The ACR Model: A Multivariate Dynamic Mixture Autoregression (2008)
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Persistent link: http://EconPapers.repec.org/RePEc:ema:worpap:2008-11

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