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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Author:Jürgen Franke, Joseph Tadjuidje Kamgaing
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
Date of the Publication (Server):2009/10/19
Tag:AR-ARCH; Markov switching; consistency; geometric ergodicity; mixture models
Faculties / Organisational entities:Kaiserslautern - Fachbereich Mathematik
DDC-Cassification:5 Naturwissenschaften und Mathematik / 510 Mathematik
Licence (German):Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011