摘要
运用高频金融数据建模和预测中国有色金属期货市场波动率,并探索已实现波动率的波动时变性和杠杆效应。拓展了LHAR-CJ模型,并对上海期货交易所铜和铝期货进行实证研究。研究表明,已实现波动率存在动态依赖性和时变性,它们均可通过长记忆性的HAR-GARCH结构体现。此外,中国有色金属期货市场波动率存在显著的周杠杆效应。最后,样本内预测和样本外预测的结果表明,考虑了已实现波动率的波动时变性和杠杆效应的HAR-CJ-G模型能有效地提高解释能力和样本外预测能力。
This paper seeks to model and forecast the Chinese nonferrous metals futures market volatility and allows new insights into the time-varying volatility of realized volatility and leverage effects using high-frequency data.The LHAR-CJ model is extended and the empirical research on copper and aluminum futures in Shanghai Futures Exchange suggests the dynamic dependencies and time-varying volatility of realized volatility,which are captured by long memory HAR-GARCH model.Besides,the findings also show the significant weekly leverage effects in Chinese nonferrous metals futures market volatility.Finally,in-sample and out-of-sample forecasts are investigated,and the results show that the LHAR-CJ-G model,considering time-varyingvolatility of realized volatility and leverage effects,effectively improves the explanatory power as well as out-of sample predictive performance.
作者
朱学红
张宏伟
钟美瑞
Xue-hong ZHU;Hong-wei ZHANG;Mei-rui ZHONG(School of Business, Central South University, Changsha 410083, China;Institute of Metal Resources Strategy, Central South University, Changsha 410083, China)
基金
Project(13&ZD169)supported by the Major Program of the National Social Science Foundation of China
Project(2016zzts009)supported by Doctoral Students Independent Explore Innovation Project of Central South University,China
Project(13YJAZH149)supported by the Social Science Foundation of Ministry of Education of China
Project(2015JJ2182)supported by the Social Science Foundation of Hunan Province,China
Project(71573282)supported by the National Natural Science Foundation of China
Project(15K133)supported by the Educational Commission of Hunan Province of China
关键词
波动率预测
杠杆效应
波动时变性
有色金属期货
高频数据
volatility forecasting
leverage effect
time-varying volatility
nonferrous metals futures
high-frequency data