Mean targeting estimator for the integer-valued GARCH(1,1) model
Mean targeting estimator for the integer-valued GARCH(1,1) model
复制标题
整数值 GARCH(1, 1) 模型的平均目标估计器
DOI：
10.1007/s00362-017-0958-9
复制
发表时间：
2020-04-01
影响因子：
1.3
通讯作者：
Zhu, Fukang
中科院分区：
文献类型：
--
作者：
Li, Qi;Zhu, Fukang
整数值的GARCH模型通常用于对计数的时间序列建模。最大似然估计（MLE）是用来估计未知参数，但MLE的数值结果是敏感的初始值的选择，这也发生在估计的Gestival模型。为了减轻这种数值上的困难，我们提出了一种替代MLE，并将其命名为均值目标估计（MTE），这是一个类似的Gestival模型中使用的方差目标估计。建立了MTE的一致性和渐近正态性。与标准的极大似然估计的比较，并讨论了平均目标法的优点。特别是，它表明，MTE可以是上级MLE估计参数或预测时，模型是很好的指定和误指定。我们进行数值研究，以确认我们的理论研究结果，并说明我们的建议的实际效用。
The integer-valued GARCH model is commonly used in modeling time series of counts. Maximum likelihood estimation (MLE) is used to estimate unknown parameters, but numerical results for MLE are sensitive to the choice of initial values, which also occurs in estimating the GARCH model. To alleviate this numerical difficulty, we propose an alternative to MLE and name it as mean targeting estimation (MTE), which is an analogue to variance targeting estimation used in the GARCH model. Consistency and asymptotic normality for MTE are established. Comparisons with the standard MLE are provided and the merits of the mean targeting method are discussed. In particular, it is shown that MTE can be superior to MLE for estimating parameters or prediction when the model is well specified and misspecified. We conduct numerical studies to confirm our theoretical findings and illustrate the practical utility of our proposals.