Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator

B-Tier
Journal: Econometric Theory
Year: 1994
Volume: 10
Issue: 1
Pages: 29-52

Authors (2)

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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.

Technical Details

RePEc Handle
repec:cup:etheor:v:10:y:1994:i:01:p:29-52_00
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-25