Conditional Heteroskedasticity Driven by Hidden Markov Chains.

In this paper, we consider a GARCH equation where the coefficients depend on the state of a non-observed Markov chain. First we establish necessary and sufficient conditions ensuring the existence of a stationary solution. Next, in the case of ARCH regimes, we show that the maximum likelihood estimator is consistent. Then we discuss the identification problem. We illustrate our approach by an application based on real and simulated data sets.

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Year of publication:	1998
Authors:	Francq, C. ; Roussignol, M. ; Zakoian, J.-M.
Subject:	ESTIMATION OF PARAMETERS \| TESTING \| TIME SERIES \| ECONOMETRICS

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Type of publication:	Book / Working Paper
Notes:	33 pages
Classification:	C13 - Estimation ; C32 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005641039