Jumps and gold futures volatility prediction

被引：1
|
作者：
Li, Xiaoqian [1 ]
Ma, Xiaoqi [1 ]
机构：
[1] Jeonju Univ, Dept Business Adm, Jeonju Si 55069, South Korea
来源：
FINANCE RESEARCH LETTERS | 2023年 / 58卷
关键词：
Jump; Chinese gold futures market; HAR; Volatility forecasting; FORECASTING VOLATILITY;
D O I：
10.1016/j.frl.2023.104492
中图分类号：
F8 [财政、金融];
学科分类号：
0202 ;
摘要：
This paper mainly checks whether jump component is efficient to predict Chinese gold futures volatility. Based on the high-frequency data, we find jump component can provide valuable in-formation to forecast the volatility of Chinese gold futures market based on the heterogeneous autoregressive-realized volatility model. This paper tries to examine the role of jump in Chinese gold futures market.
引用
收藏
页数：5
相关论文
共 50 条
  • [31] Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks
    Shen, Dehua
    Urquhart, Andrew
    Wang, Pengfei
    EUROPEAN FINANCIAL MANAGEMENT, 2020, 26 (05) : 1294 - 1323
  • [32] Forecasting volatility of EUA futures: New evidence
    Guo, Xiaozhu
    Huang, Yisu
    Liang, Chao
    Umar, Muhammad
    ENERGY ECONOMICS, 2022, 110
  • [33] Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures
    Luo, Jiawen
    Zhang, Qun
    JOURNAL OF FUTURES MARKETS, 2024, 44 (02) : 151 - 217
  • [34] Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes
    Gong, Xu
    Lin, Boqiang
    INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, 2022, 27 (01) : 610 - 640
  • [35] Volatility prediction comparison via robust volatility proxies: An empirical deviation perspective
    Wang, Weichen
    An, Ran
    Zhu, Ziwei
    JOURNAL OF ECONOMETRICS, 2024, 239 (02)
  • [36] Meta-LSTR: Meta-Learning with Long Short-Term Transformer for futures volatility prediction
    Chen, Yunzhu
    Ye, Neng
    Zhang, Wenyu
    Fan, Jiaqi
    Mumtaz, Shahid
    Li, Xiangming
    EXPERT SYSTEMS WITH APPLICATIONS, 2025, 265
  • [37] Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models
    Agnolucci, Paolo
    ENERGY ECONOMICS, 2009, 31 (02) : 316 - 321
  • [38] Trading volume, realized volatility and jumps in the Australian stock market
    Shahzad, Hassan
    Huu Nhan Duong
    Kalev, Petko S.
    Singh, Harminder
    JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY, 2014, 31 : 414 - 430
  • [39] Volatility forecasting in Chinese nonferrous metals futures market
    Zhu, Xue-hong
    Zhang, Hong-wei
    Zhong, Mei-rui
    TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA, 2017, 27 (05) : 1206 - 1214
  • [40] Evolving Possibilistic Fuzzy Modeling for Realized Volatility Forecasting With Jumps
    Maciel, Leandro
    Ballini, Rosangela
    Gomide, Fernando
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2017, 25 (02) : 302 - 314
12345