The efficiency of the estimators of the parameters in GARCH processes

The Annals of Statistics · 2004 · Volume 32 · Issue 2

Abstract

We propose a class of estimators for the parameters of a GARCH(p,q) sequence. We show that our estimators are consistent and asymptotically normal under mild conditions. The quasi-maximum likelihood and the likelihood estimators are discussed in detail. We show that the maximum likelihood estimator is optimal. If the tail of the distribution of the innovations is polynomial, even a quasi-maximum likelihood estimator based on exponential density performs better than the standard normal density-based quasi-likelihood estimator of Lee and Hansen and Lumsdaine.

Keywords

62F12, 62M10, asymptotic covariance matrix, asymptotic normality, Fisher information number, GARCH(p, q) sequence, quasi-maximum likelihood

Enable JavaScript for citation tools and additional paper interactions.