The Macroeconomic Influence of China Futures Market: A GARCH-MIDAS Approach

被引：0
|
作者：
Liu, Ruobing [1 ]
Yang, Jianhui [1 ]
Ruan, Chuanyang [2 ,3 ]
机构：
[1] South China Univ Technol, Sch Business Adm, Guangzhou 510640, Peoples R China
[2] Guangdong Univ Finance & Econ, Sch Business Adm, Guangzhou 510320, Peoples R China
[3] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200240, Peoples R China
来源：
ADVANCES IN HARMONY SEARCH, SOFT COMPUTING AND APPLICATIONS | 2020年 / 1063卷
关键词：
GARCH-MIDAS; China futures market; Macroeconomic fundamentals; Long-run variance; VOLATILITY; RETURN;
D O I：
10.1007/978-3-030-31967-0_28
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We revisit the relationship between the commodities futures market volatility and the macroeconomic factors, by employing the GARCH-MIDAS model, which can decompose the conditional variance into the secular and short-run component. We introduce the level or the variance of the macroeconomic variables into the GARCH-MIDAS model, to test the impact of the macroeconomic variables on the long-run variance. In the paper, we find the variance of PPI and IP has a more significant impact on the volatility of China commodities futures market than the level of the macroeconomic variables.
引用
下载
收藏
页码：244 / 251
页数：8
相关论文
共 50 条
  • [21] Forecasting exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach
    Eniayewu, Patience Eyo
    Samuel, Gideon Tukura
    Joshua, Jeremiah Dandaura
    Samuel, Bazitei Tuapreghe
    Dogo, Bishara Saidu
    Yusuf, Umar
    Ihekuna, Rosemond Onyinye
    Mevweroso, Chioma Reacheal
    SCIENTIFIC AFRICAN, 2024, 23
  • [22] Identifying the Determinants of Crude Oil Market Volatility by the Multivariate GARCH-MIDAS Model
    Chuang, O-Chia
    Yang, Chenxu
    ENERGIES, 2022, 15 (08)
  • [23] Output - Inflation nexus in selected African countries: A GARCH-MIDAS approach
    Babangida, Hassana Umar
    Belonwu, Maximillian
    Abubakar, Sani
    Pennap, Nanfa
    Wilfred, Mwakapwa
    Okafor, Samson Nonso
    Eyinla, Titoluwa
    Onuogu, Ijeoma
    SCIENTIFIC AFRICAN, 2024, 23
  • [24] Sentiment, Herding and Volatility Forecasting: Evidence from GARCH-MIDAS Approach
    Cui, Yanxian
    Zheng, Hong
    Yuan, Ying
    FLUCTUATION AND NOISE LETTERS, 2023, 22 (02):
  • [25] A Real-Time GARCH-MIDAS model
    Wu, Xinyu
    Zhao, An
    Cheng, Tengfei
    FINANCE RESEARCH LETTERS, 2023, 56
  • [26] Inflation and stock return volatility in selected African countries: A GARCH-MIDAS approach
    Muhammad, Kamaludeen
    Saleh, Abulbashar
    Bello, Umar M.
    Tule, Jeremiah M.
    John, Elijah A.
    Edet, Joy E.
    Ohiaeri, Iheanacho
    Eneanya, Chukwuemeka N.
    SCIENTIFIC AFRICAN, 2024, 25
  • [27] Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime-switching GARCH-MIDAS models
    Ma, Feng
    Lu, Xinjie
    Wang, Lu
    Chevallier, Julien
    JOURNAL OF FORECASTING, 2021, 40 (06) : 1070 - 1085
  • [28] Political, economic, and financial country risks and the volatility of the South African Exchange Traded Fund market: A GARCH-MIDAS approach
    Damien Kunjal
    Faeezah Peerbhai
    Paul-Francois Muzindutsi
    Risk Management, 2022, 24 : 236 - 258
  • [29] Political, economic, and financial country risks and the volatility of the South African Exchange Traded Fund market: A GARCH-MIDAS approach
    Kunjal, Damien
    Peerbhai, Faeezah
    Muzindutsi, Paul-Francois
    RISK MANAGEMENT-AN INTERNATIONAL JOURNAL, 2022, 24 (03): : 236 - 258
  • [30] Economic uncertainty and stock market asymmetric volatility: analysis based on the asymmetric GARCH-MIDAS model
    Wang, Zaifeng
    Xing, Tiancai
    Wang, Xiao
    INTERNATIONAL JOURNAL OF EMERGING MARKETS, 2024,
12345