Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE
GARCH 模型的两阶段非高斯 QML 估计与高斯 QMLE 效率检验
In generalized autoregressive conditional heteroskedastic (GARCH) models, the standard identifiability assumption that the variance of the iid process is equal to 1 can be replaced by an alternative moment assumption. We show that, for estimating the original specification based on the standard identifiability assumption, efficiency gains can be expected from using a quasi-maximum likelihood (QML) estimator based on a non Gaussian density and a reparameterization based on an…