QUASI-MAXIMUM LIKELIHOOD ESTIMATION OF SEMI-STRONG GARCH MODELS

被引:30
|
作者
Escanciano, Juan Carlos [1 ]
机构
[1] Indiana Univ, Dept Econ, Bloomington, IN 47405 USA
关键词
CONDITIONAL SKEWNESS; ASYMPTOTIC NORMALITY; CONSISTENCY; INFERENCE; ERRORS; ARCH;
D O I
10.1017/S0266466609090689
中图分类号
F [经济];
学科分类号
02 ;
摘要
This note proves the consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) of the parameters of a generalized autoregressive conditional heteroskedastic (LARCH) model with martingale difference centered squared innovations. The results are obtained under mild conditions and generalize and improve those in Lee and Hansen (1994, Econometric Theory 10, 29-52) for the local QMLE in semistrong GARCH(1, 1) models. In particular, no restrictions on the conditional mean are imposed. Our proofs closely follow those in Francq and Zakoian (2004, Bernoulli 10, 605-637) for independent and identically distributed innovations.
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页码:561 / 570
页数:10
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