主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

中国管理科学 ›› 2021, Vol. 29 ›› Issue (9): 54-64.doi: 10.16381/j.cnki.issn1003-207x.2019.1695

• 论文 • 上一篇    下一篇

考虑结构变化和长记忆性的国际原油价格波动率预测研究

张跃军1,2, 张晗1,2, 王金丽1,2   

  1. 1. 湖南大学工商管理学院, 湖南 长沙 410082;
    2. 湖南大学资源与环境管理研究中心, 湖南 长沙 410082
  • 收稿日期:2019-10-25 修回日期:2020-01-22 出版日期:2021-09-20 发布日期:2021-09-20
  • 通讯作者: 张跃军(1980-),男(汉族),湖南安仁人,湖南大学工商管理学院,教授,博士生导师,博士,研究方向:石油资产定价与预测,E-mail:zyjmis@126.com. E-mail:zyjmis@126.com
  • 基金资助:
    国家自然科学基金资助项目(71774051);湖南省科技创新计划(2020RC4016);教育部长江学者奖励计划(T2020095)

Volatility Forecasting of Crude Oil Market Based on Structural Changes and Long Memory

ZHANG Yue-jun1,2, ZHANG Han1,2, WANG Jin-li1,2   

  1. 1. Business School, Hunan University, Changsha 410082, China;
    2. Center for Resource and Environmental Management, Hunan University, Changsha 410082, China
  • Received:2019-10-25 Revised:2020-01-22 Online:2021-09-20 Published:2021-09-20

摘要: 原油市场普遍存在结构变化现象,可能会引发原油价格波动率的长记忆性,导致模型参数的有偏估计。为此,本文考虑原油价格波动率的结构变化和长记忆性特征,采用考虑结构断点的GARCH族模型和MMGARCH模型对WTI和Brent油价波动率进行预测建模。结果表明,WTI和Brent油价波动率中确实存在明显的结构变化和长记忆性特征,而能够捕捉这两种特征的GARCH族模型往往比忽略它们的模型取得更好的油价波动率预测效果,特别是,同时动态捕捉结构变化和长记忆性特征的MMGARCH模型对油价波动率的预测性能优于其他相关模型。

关键词: 原油市场, 波动率预测, 结构变化, 长记忆性

Abstract: The structural changes which may result in spurious long memory always occur in crude oil market, and then they usually lead to the biased estimation of parameters. As a result, the features of structural changes and long memory have become the key to the rational modeling and accurate forecasting of crude oil price volatility. However, the existing models often only consider a certain factor, or only consider the long memory or short memory in the volatility, which may lead to the inaccurate forecasting of crude oil price volatility. In this situation, this paper aims to investigate whether the volatility forecasting models considering structural change and long memory have better forecasting performance on crude oil price volatility than traditional models, and whether the mixed memory GARCH model considering different memory and volatility level appears effective in depicting the characteristics of structural changes and long memory in crude oil price volatility. Therefore, both of the characteristics are focused on, and the GARCH-type models incorporating structural break points and the MMGARCH model are used to estimate and forecast crude oil price volatility. The empirical results prove the existence of structural change and long memory characteristics in crude oil market volatility, and indicate that the models which incorporate the two characteristics usually yield superior fitting and forecasting performance to standard GARCH-type models. In particular, the MMGARCH model outperforms other competitive models on forecasting crude oil price volatility, which indicates that the MMGARCH model can dynamically depict the volatility level and memory of the process, and then capture the structural changes and long memory simultaneously. Therefore, the MMGARCH model can be considered a helpful alternative to make accurate crude oil price volatility forecasting.

Key words: crude oil market, volatility forecasting, structural changes, long memory

中图分类号: