Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator
Sang-Won Lee and
Bruce Hansen ()
Econometric Theory, 1994, vol. 10, issue 01, 29-52
This paper investigates the sampling behavior of the quasi-maximum likelihood estimator of the Gaussian GARCH(1,1) model. The rescaled variable (the ratio of the disturbance to the conditional standard deviation) is not required to be Gaussian nor independent over time, in contrast to the current literature. The GARCH process may be integrated (α + β = 1), or even mildly explosive (α + β > 1). A bounded conditional fourth moment of the rescaled variable is sufficient for the results. Consistent estimation and asymptotic normality are demonstrated, as well as consistent estimation of the asymptotic covariance matrix.
References: Add references at CitEc
Citations View citations in EconPapers (210) Track citations by RSS feed
Downloads: (external link)
http://journals.cambridge.org/abstract_S0266466600008215 link to article abstract page (text/html)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:cup:etheor:v:10:y:1994:i:01:p:29-52_00
Access Statistics for this article
More articles in Econometric Theory from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Series data maintained by Keith Waters ().