The efficiency of the estimators of the parameters in GARCH processes
The efficiency of the estimators of the parameters in GARCH processes
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DOI：
10.1214/009053604000000120
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发表时间：
2004-04
影响因子：
4.5
通讯作者：
I. Berkes;Lajos Horv'ath
中科院分区：
文献类型：
--
作者：
I. Berkes;Lajos Horv'ath
本文提出了一类Gestival（p，q）序列参数的估计。我们证明了我们的估计是一致的，渐近正态在温和的条件下。详细讨论了拟极大似然估计和似然估计。我们证明了极大似然估计是最优的。如果新息分布的尾部是多项式的，即使是基于指数密度的准最大似然估计也比Lee和汉森和Lumsdaine的基于标准正态密度的准似然估计表现得更好。
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.