一元GARCH模型估计的渐近理论:平稳与非平稳情形(英文)  

Asymptotic Theory of Univariate GARCH Estimation:Stationary and Nonstationary Case

作　　者：王辉[1] 

机构地区：[1]中央财经大学金融学院,北京100081

出　　处：《数学进展》2013年第2期138-152,共15页Advances in Mathematics（China）

基　　金：Partially supported by a grant from the"Project 211"of the Central University of Finance and Economics,the CUFE Young Scholar Innovation Fund and NSFC(No.11101448)

摘　　要：ARCH/GARCH模型是刻画波动率最常用的模型.本文综述一元GARCH模型的估计方法,主要讨论准最大似然估计和最小绝对偏差估计方法的渐近性质.此外,本文还讨论了非平稳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 survey of estimation methods of univaxiate GARCH models with a special attention given to the asymptotic results of the quasi-maximum likeShood method and the least absolute deviation method. The estimation for non-stationary GARCH model is also discussed.

关 键 词：GARCH 相合性 渐近正态性 准最大似然估计 最小绝对偏移估计 

分 类 号：O211.4[理学—概率论与数理统计] O211.64[理学—数学]