Minimum distance estimation of GARCH(1,1) models

被引：10
|
作者：
Storti, G. [1 ]
机构：
[1] Univ Salerno, Dipartimento Sci Encon & stat, I-84084 Fisciano, SA, Italy
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2006年 / 51卷 / 03期
关键词：
GARCH models; minimum distance estimation; autocovariance function; quasi maximum likelihood; high frequency;
D O I：
10.1016/j.csda.2005.11.020
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
A distribution free approach to the estimation of GARCH(1, 1) models is presented. More specifically, the proposed method relies on a Minimum Distance Estimator (MDE) based on the autocovariance function of the squared observations. The asymptotic properties of the estimator are studied giving conditions for its consistency and asymptotic normality while its finite sample efficiency is assessed by means of a simulation study. Finally the proposed estimation method is applied to a time series of hourly returns on the FIFSE100 index futures. (c) 2005 Elsevier B.V. All rights reserved.
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页码：1803 / 1821
页数：19
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