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Large sample properties of parameter least squares estimates for time-varying arma models

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  • Christian Francq
  • Antony Gautier

Abstract

This paper considers estimation of ARMA models with time-varying coefficients. The ARMA parameters belong to d different regimes. The changes in regime occur at irregular time intervals. Consistency and asymptotic normality of least squares and quasi-generalized least squares estimators are shown. Copyright 2004 Blackwell Publishing Ltd.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 25 (2004)
Issue (Month): 5 (09)
Pages: 765-783

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Handle: RePEc:bla:jtsera:v:25:y:2004:i:5:p:765-783

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782

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Cited by:
  1. Zakoïan, Jean-Michel & Regnard, Nazim, 2011. "A Conditionally Heteroskedastic Model with Time-varying Coefficients for Daily Gas Spot Prices," Economics Papers from University Paris Dauphine, Paris Dauphine University 123456789/2603, Paris Dauphine University.
  2. Triantafyllopoulos, K. & Nason, G.P., 2007. "A Bayesian analysis of moving average processes with time-varying parameters," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 52(2), pages 1025-1046, October.
  3. Zakoïan, Jean-Michel & Regnard, Nazim, 2008. "GARCH (1,1) Models with Exogenously-Driven Volatility: Structure and Estimation," Economics Papers from University Paris Dauphine, Paris Dauphine University 123456789/2285, Paris Dauphine University.
  4. Zakoïan, Jean-Michel, 2010. "A class of DCC asymmetric GARCH models driven by exogenous variables," Economics Papers from University Paris Dauphine, Paris Dauphine University 123456789/5529, Paris Dauphine University.

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