Consistency of maximum likelihood estimators for the regime-switching GARCH model

Xie, Yingfu

doi:10.1080/02331880701442619

Sammanfattning

The regime-switching GARCH (generalized autoregressive conditionally heteroscedastic) model incorporates the idea of Markov switching into the more restrictive GARCH model, which significantly extends the GARCH model. However, the statistical inference for such an extended model is rather difficult because observations at any time point then depend on the whole regime path and the likelihood becomes intractable quickly as the length of observations increases. In this paper, by transforming it into an infinite order ARCH model, we obtain the possibility of writing a likelihood which can be handled directly and the consistency of the maximum likelihood estimators is proved. Simulation studies to illustrate the consistency and asymptotic normality of the estimators (for both Gaussian and non-Gaussian innovations) and a model specification problem are presented.

Nyckelord

GARCH model; regime switching; MLE; consistency; asymptotic normality; model specification

Publicerad i

Statistics
2009, volym: 43, nummer: 2, sidor: 153-165
Utgivare: TAYLOR & FRANCIS LTD

SLU författare

Xie, Yingfu
- Institutionen för skogsekonomi, Sveriges lantbruksuniversitet

UKÄ forskningsämne

Sannolikhetsteori och statistik

Publikationens identifierare

DOI: https://doi.org/10.1080/02331880701442619

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/61231