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The Autoregressive Conditional Root (ACR) Model

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  • Frédérique Bec

    (Crest)

  • Anders Rahbek

    (Crest)

  • Neil Shephard

    (Crest)

Abstract

In this paper we propose and analyse the Autoregressive Conditional Root (ACR) timeseries model, which allows for endogenously generated regime switching between seemingly stationaryand non-stationary epochs. It proves to be an appealing alternative to existing nonlinear models suchas e.g. the threshold autoregressive or Markov switching classes of models, which are commonly used todescribe nonlinear dynamics as implied by arbitrage in presence of transaction costs. Simple conditionson 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 normalityof the maximum likelihood estimators in the ACR model. An application to French-German exchangerate data illustrate the conclusions and analysis.

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Bibliographic Info

Paper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2005-26.

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Length: 30
Date of creation: 2005
Date of revision:
Handle: RePEc:crs:wpaper:2005-26

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Cited by:
  1. Frédérique Bec & Songlin Zeng, 2012. "Are Southeast Asian Real Exchange Rates Mean Reverting?," THEMA Working Papers 2012-25, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  2. Frédérique Bec & Alain Guay & Emmanuel Guerre, 2002. "Adaptive Consistent Unit Root Tests Based on Autoregressive Threshold Model," Working Papers 2002-46, Centre de Recherche en Economie et Statistique.
  3. Jumah, Adusei & Kunst, Robert M., 2008. "Optimizing Time-series Forecasts for Inflation and Interest Rates Using Simulation and Model Averaging," Economics Series 231, Institute for Advanced Studies.

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