Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
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DOI：
10.3150/bj/1093265632
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发表时间：
2004-08-01
期刊：
影响因子：
1.5
通讯作者：
Zakoïan, JM
中科院分区：
文献类型：
--
作者：
Francq, C;Zakoïan, JM
我们证明了纯广义自回归条件异方差（GARCH）过程的参数的拟极大似然估计的强相合性和渐近正态性，以及噪声序列驱动的GARCH模型的自回归移动平均模型。结果在温和的条件下获得。
We prove the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator of the parameters of pure generalized autoregressive conditional heteroscedastic (GARCH) processes, and of autoregressive moving-average models with noise sequence driven by;a GARCH model. Results are obtained under mild conditions.