Maximum Likelihood Estimators for Markov Switching Autoregressive Processes with ARCH Component

  • We consider a mixture of AR-ARCH models where the switching between the basic states of the observed time series is controlled by a hidden Markov chain. Under simple conditions, we prove consistency and asymptotic normality of the maximum likelihood parameter estimates combining general results on asymptotics of Douc et al (2004) and of geometric ergodicity of Franke et al (2007).

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Metadaten
Author:Jürgen Franke, Joseph Tadjuidje Kamgaing
URN (permanent link):urn:nbn:de:hbz:386-kluedo-16268
Serie (Series number):Report in Wirtschaftsmathematik (WIMA Report) (124)
Document Type:Preprint
Language of publication:English
Year of Completion:2009
Year of Publication:2009
Publishing Institute:Technische Universität Kaiserslautern
Tag:AR-ARCH ; Markov switching ; consistency; geometric ergodicity ; mixture models
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:510 Mathematik

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