...
首页> 外文期刊>Economic modelling >Can GARCH-class models capture long memory in WTI crude oil markets?
【24h】

Can GARCH-class models capture long memory in WTI crude oil markets?

机译:GARCH类模型能否在WTI原油市场中获得长期记忆?

获取原文
获取原文并翻译 | 示例
           

摘要

This paper investigates the issue whether GARCH-type models can well capture the long memory widely existed in the volatility of WTI crude oil returns. In this frame, we model the volatility of spot and futures returns employing several GARCH-class models. Then, using two non-parametric methods, detrended fluctuation analysis (DFA) and rescaled range analysis (R/S), we compare the long memory properties of conditional volatility series obtained from GARCH-class models to that of actual volatility series. Our results show that GARCH-class models can well capture the long memory properties for the time scale larger than a year. However, for the time scale smaller than a year, the GARCH-class models are misspecified.
机译:本文探讨了WARCH原油收益波动性中GARCH型模型能否很好地捕捉长期存在的长期记忆的问题。在此框架中,我们使用几种GARCH类模型对现货和期货收益的波动性进行建模。然后,使用去趋势波动分析(DFA)和重标范围分析(R / S)这两种非参数方法,比较了从GARCH类模型获得的条件波动率序列与实际波动率序列的长期记忆特性。我们的结果表明,GARCH类模型可以很好地捕获大于一年的时间范围内的长存储属性。但是,对于小于一年的时间范围,GARCH类模型指定不正确。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号