The ACR Model: A Multivariate Dynamic Mixture Autoregression

36 Pages Posted: 16 Sep 2008

See all articles by Frédérique Bec

Frédérique Bec

University of Cergy-Pontoise; National Institute of Statistics and Economic Studies (INSEE)

Anders Rahbek

University of Copenhagen - Department of Statistics and Operations Research; University of Copenhagen - Department of Economics

Neil Shephard

Harvard University

Date Written: 0000

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.

Suggested Citation

Bec, Frédérique and Rahbek, Anders and Shephard, Neil, The ACR Model: A Multivariate Dynamic Mixture Autoregression (0000). Oxford Bulletin of Economics and Statistics, Vol. 70, Issue 5, pp. 583-618, October 2008. Available at SSRN: https://ssrn.com/abstract=1269063 or http://dx.doi.org/10.1111/j.1468-0084.2008.00512.x

Frédérique Bec (Contact Author)

University of Cergy-Pontoise ( email )

33 boulevard du port
F-95011 Cergy-Pontoise Cedex, 95011
France

National Institute of Statistics and Economic Studies (INSEE) ( email )

15 Boulevard Gabriel Peri
Malakoff Cedex, 1 92245
France

Anders Rahbek

University of Copenhagen - Department of Statistics and Operations Research

Universitetsparken 5
DK-2100
Denmark
+45 3532 0682 (Phone)

University of Copenhagen - Department of Economics

Øster Farimagsgade 5
Bygning 26
1353 Copenhagen K.
Denmark

Neil Shephard

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

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