Bootstrap prediction intervals for ARCH models

被引：47
|
作者：
Reeves, JJ [1 ]
机构：
[1] Univ New S Wales, Sch Banking & Finance, Sydney, NSW 2052, Australia
来源：
INTERNATIONAL JOURNAL OF FORECASTING | 2005年 / 21卷 / 02期
关键词：
forecasting; GARCH; non-Gaussian time series; resampling;
D O I：
10.1016/j.ijforecast.2004.09.005
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In this paper, we construct prediction intervals for autoregressive conditional heteroskedasticity (ARCH) models using the bootstrap. We use both a parametric and non-parametric bootstrap, which take account of parameter uncertainty. We compare our prediction intervals to traditional asymptotic prediction intervals and find that the bootstrap leads to improved accuracy. The accuracy of the bootstrap is empirically demonstrated with the Yen/US$ exchange rate. (c) 2004 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：237 / 248
页数：12
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