Asymptotic Theory of Univariate GARCH Estimation: Stationary and Nonstationary Case
Asymptotic Theory of Univariate GARCH Estimation: Stationary and Nonstationary Case
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单变量 GARCH 估计的渐近理论：平稳和非平稳情况
DOI：
10.11845/sxjz.2013.42.02.0138
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Wang Hui
中科院分区：
文献类型：
--
作者：
Wang Hui
广义自回归条件异方差模型（ARCH/ GARCH）是最常用的波动参数化方法。本文综述了单变量GARCH模型的估计方法，重点讨论了拟极大似然法和最小绝对偏差法的渐近结果。讨论了非平稳GARCH模型的估计问题。
Models of (Generalized) Autoregressive Conditional Heteroskedasticity(ARCH/ GARCH) form the most popular way of parameterizing volatility. This paper contains a sur- vey of estimation methods of univariate GARCH models with a special attention given to the asymptotic results of the quasi-maximum likelihood method and the least absolute deviation method. The estimation for non-stationary GARCH model is also discussed.