The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market

被引:23
|
作者
Luo, Xingguo [1 ,2 ]
Qin, Shihua [1 ]
Ye, Zinan [1 ]
机构
[1] Zhejiang Univ, Coll Econ, Hangzhou 310027, Zhejiang, Peoples R China
[2] Zhejiang Univ, Acad Financial Res, Hangzhou 310027, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Gold futures; Realized volatility; Volatility forecasting; Volatility Index; EXCHANGE; DYNAMICS; PRICE;
D O I
10.1016/j.frl.2016.06.012
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper investigates the information content of the CBOE Gold ETF Volatility Index (GVZ) and jumps in forecasting realized volatility of the Shanghai gold futures market. We find strong in-sample evidence that the GVZ and jumps are significant and both greatly improve next day volatility forecasts. Also, these results are robust when the recent financial crisis is considered. Further, out-of-sample analysis confirms that the GVZ and jumps are important factors in forecasting future volatility. More important, we show that the GVZ outperforms jumps in terms of forecasting performance. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:105 / 111
页数:7
相关论文
共 50 条
  • [21] Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks
    Asai, Manabu
    Gupta, Rangan
    McAleer, Michael
    INTERNATIONAL JOURNAL OF FORECASTING, 2020, 36 (03) : 933 - 948
  • [22] Forecasting bitcoin volatility: Evidence from the options market
    Hoang, Lai T.
    Baur, Dirk G.
    JOURNAL OF FUTURES MARKETS, 2020, 40 (10) : 1584 - 1602
  • [23] Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets
    Prokopczuk, Marcel
    Symeonidis, Lazaros
    Simen, Chardin Wese
    JOURNAL OF FUTURES MARKETS, 2016, 36 (08) : 758 - 792
  • [24] Asymmetric Information and Volatility Forecasting in Commodity Futures Markets
    Liu, Qingfu
    Wong, Ieokhou
    An, Yunbi
    Zhang, Jinqing
    PACIFIC-BASIN FINANCE JOURNAL, 2014, 26 : 79 - 97
  • [25] The information content of uncertainty indices for natural gas futures volatility forecasting
    Liang, Chao
    Ma, Feng
    Wang, Lu
    Zeng, Qing
    JOURNAL OF FORECASTING, 2021, 40 (07) : 1310 - 1324
  • [26] Do intraday data contain more information for volatility forecasting? Evidence from the Chinese commodity futures market
    Jiang, Ying
    Liu, Xiaoquan
    Ye, Wuyi
    APPLIED ECONOMICS LETTERS, 2015, 22 (03) : 218 - 222
  • [27] Forecasting gold futures market volatility using macroeconomic variables in the United States
    Fang, Libing
    Yu, Honghai
    Xiao, Wen
    ECONOMIC MODELLING, 2018, 72 : 249 - 259
  • [28] Forecasting the Asian stock market volatility: Evidence from WTI and INE oil futures
    Ghani, Maria
    Ma, Feng
    Huang, Dengshi
    INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, 2024, 29 (02) : 1496 - 1512
  • [29] Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets
    Qiao, Gaoxiu
    Teng, Yuxin
    Li, Weiping
    Liu, Wenwen
    NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2019, 49 : 133 - 151
  • [30] Forecasting volatility of EUA futures: New evidence
    Guo, Xiaozhu
    Huang, Yisu
    Liang, Chao
    Umar, Muhammad
    ENERGY ECONOMICS, 2022, 110