An Empirical Analysis of the Price Volatility Characteristics of China's Soybean Futures Market Based on ARIMA-GJR-GARCH Model

被引：5
|
作者：
Xu, Yang [1 ]
Xia, Zhihao [2 ]
Wang, Chuanhui [2 ]
Gong, Weifeng [2 ,3 ]
Liu, Xia [2 ]
Su, Xiaodi [2 ]
机构：
[1] Ocean Univ China, Management Coll, Qingdao 266100, Peoples R China
[2] Qufu Normal Univ, Sch Econ, Rizhao 276826, Peoples R China
[3] Nanjing Univ Aeronaut & Astronaut, Sch Econ & Management, Nanjing 211006, Peoples R China
来源：
JOURNAL OF MATHEMATICS | 2021年 / 2021卷
关键词：
OIL PRICE; COINTEGRATION;
D O I：
10.1155/2021/7765325
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
As the main force in the futures market, agricultural product futures occupy an important position in the China's market. Taking the representative soybean futures in Dalian Commodity Futures Market of China as the research object, the relationship between price fluctuation characteristics and trading volume and open position was studied. The empirical results show that the price volatility of China's soybean futures market has a "leverage effect." The trading volume and open interest are divided into expected parts and unexpected parts, which are added to the conditional variance equation. The expected trading volume coefficient is estimated. Also, the estimated value of the expected open interest coefficient is, respectively, smaller than the estimated value of the unexpected trading volume coefficient and the estimated value of the unexpected open interest coefficient. Therefore, the impact of expected trading volume on the price fluctuation of China's soybean futures market is less than that of unexpected trading volume on the price of soybean futures market. This paper adds transaction volume as an information flow to the variance of the conditional equation innovatively and also observes transaction volume as the relationship between conditional variance and price fluctuations.
引用
收藏
页数：9
相关论文
共 50 条
  • [31] Price risk management effect on the China's egg "Insurance plus Futures" mode: an empirical analysis based on the AR-Net model
    Liu, Chen
    Zhao, Yuhe
    [J]. KUWAIT JOURNAL OF SCIENCE, 2022, : 1 - 14
  • [32] The Optimal Hedge Ratio of Stock Index Futures : An Empirical Analysis Based on Copula-GARCH Model
    Zhao, Jiamin
    Shen, Yi
    [J]. ADVANCES IN BUSINESS INTELLIGENCE AND FINANCIAL ENGINEERING, 2008, 5 : 727 - +
  • [33] Volatility Spillovers in the CSI300 Futures and Spot Markets in China: Empirical Study Based on Discrete Wavelet Transform and VAR-BEKK-bivariate GARCH Model
    Li, Shiyun
    [J]. 3RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, ITQM 2015, 2015, 55 : 380 - 387
  • [34] Is China's hog futures market effective? Based on the perspective of price discovery and hedging functions
    Peng, Chengliang
    [J]. APPLIED ECONOMICS LETTERS, 2024,
  • [35] Using CARR Model and GARCH Model to Forecast Volatility of the Stock Index: Evidence from China's Shanghai Stock Market
    Zou Wen-jun
    Guo Ming-yuan
    [J]. 2014 INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE & ENGINEERING (ICMSE), 2014, : 1106 - 1112
  • [36] Empirical research on the relationship between futures market and economic growth in China Based on the VAR model
    Yang Kaijun
    Liu Huijuan
    [J]. PROCEEDINGS OF THE 7TH (2015) INTERNATIONAL CONFERENCE ON FINANCIAL RISK AND CORPORATE FINANCE MANAGEMENT, 2015, : 123 - 128
  • [37] Economic uncertainty and stock market asymmetric volatility: analysis based on the asymmetric GARCH-MIDAS model
    Wang, Zaifeng
    Xing, Tiancai
    Wang, Xiao
    [J]. INTERNATIONAL JOURNAL OF EMERGING MARKETS, 2024,
  • [38] Market Efficiency Test Methods and the Empirical Evidence of China's Non-GMO Soybean Futures Markets on the Effectiveness
    Deng, Yong-Qin
    Zhou, Ya-Dan
    Chen, Ying
    [J]. INTERNATIONAL CONFERENCE ON ECONOMICS AND MANAGEMENT ENGINEERING (ICEME 2014), 2014, : 27 - 42
  • [39] Relationships Between Oil Shocks and China's Price: An Empirical Analysis Based on VAR Model
    Wu Xiang
    Wang Xiaolei
    [J]. PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON INNOVATION AND MANAGEMENT, VOLS I AND II, 2014, : 55 - 59
  • [40] THE RISK MEASUREMENT OF CHINA'S CARBON FINANCIAL MARKET: BASED ON GARCH AND VAR MODEL
    Wang, L.
    Tang, L.
    Qiu, X. M.
    Zhang, X. X.
    Ma, R. H.
    [J]. APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 2019, 17 (04): : 9301 - 9315
12345