The ACR Model: A Multivariate Dynamic Mixture Autoregression

Frédérique Bec, Anders Rahbek and Neil Shephard ()

Oxford Bulletin of Economics and Statistics, 2008, vol. 70, issue 5, pages 583-618

Abstract: This paper proposes and analyses the autoregressive conditional root (ACR) time-series model. This multivariate dynamic mixture autoregression allows for non-stationary epochs. It proves to be an appealing alternative to existing nonlinear models, e.g. the threshold autoregressive or Markov switching class of models, which are commonly used to describe nonlinear 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, consistency and asymptotic normality of the maximum likelihood estimators are established. An application to real exchange rate data illustrates the analysis. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2008.

Date: 2008
View citations in EconPapers

Downloads: (external link)
http://www.blackwell-synergy.com/doi/abs/10.1111/j.1468-0084.2008.00512.x link to full text (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: The ACR model: a multivariate dynamic mixture autoregression (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:bla:obuest:v:70:y:2008:i:5:p:583-618

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0305-9049

Access Statistics for this article

Oxford Bulletin of Economics and Statistics is edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, Gavin Cameron, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple

More articles in Oxford Bulletin of Economics and Statistics from Department of Economics, University of Oxford
Series data maintained by Christopher F. Baum ().