A Comparison Research on Dynamic Characteristics of Chinese and American Energy Prices

被引:42
作者
He, Qizhi [1 ,2 ]
Zhang, Xu [3 ]
Xia, Pingfan [4 ]
Zhao, Chenyu [5 ,6 ]
Li, Shuangbo [1 ,7 ]
机构
[1] Zhejiang Gongshang Univ, Sch Math & Stat, Hangzhou, Zhejiang, Peoples R China
[2] Zhejiang Gongshang Univ, Collaborat Innovat Ctr Stat Data Engn Technol & A, Hangzhou, Zhejiang, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Dept Finance, Nanjing, Jiangsu, Peoples R China
[4] Hefei Univ Technol, Management Sci & Engn, Hefei, Anhui, Peoples R China
[5] Zhejiang Gongshang Univ, Sch Finance, Hangzhou, Zhejiang, Peoples R China
[6] Zhejiang Gongshang Univ, Modern Business Res Ctr, Hangzhou, Zhejiang, Peoples R China
[7] Zhejiang Gongshang Univ, Hangzhou, Zhejiang, Peoples R China
关键词
Energy Price; Learning Expectation; Learning Speed; Persistence; Volatility; MULTIVARIATE STOCHASTIC VOLATILITY; MODELS;
D O I
10.4018/JGIM.319042
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
This study compares the dynamic characteristic of Chinese and American energy prices from the perspectives of learning expectation, volatility, persistence, and so on. First, the most suitable learning speeds for energy prices are determined and the energy price expectations are calculated by the learning models. Second, volatility characteristics and Granger-spillover effects among different energy prices and expectations are examined using the stochastic models based on the coefficient significance and DIC criteria. Third, the dynamic correlation coefficients are obtained by the selected stochastic models that have the lower DIC values. Fourth, expectation, volatility, and foreign energy price are introduced into the persistence model, and the persistence characteristics and reasons behind Chinese and American energy prices are empirically tested and compared. Finally, conclusions and suggestions are given based on the theoretical analysis and empirical results.
引用
收藏
页数:16
相关论文
共 24 条
  • [1] Multivariate stochastic volatility: A review
    Asai, Manabu
    McAleer, Michael
    Yu, Jun
    [J]. ECONOMETRIC REVIEWS, 2006, 25 (2-3) : 145 - 175
  • [2] Chen S., 2021, J QUANT ECON, V12, P27
  • [3] Exploring the role of natural resources, natural gas and oil production for economic growth of China
    Cui, Lianbiao
    Weng, Shimei
    Kirikkaleli, Dervis
    Bashir, Muhammad Adnan
    Rjoub, Husam
    Zhou, Yuanxiang
    [J]. RESOURCES POLICY, 2021, 74
  • [4] Fan C., 2016, Econ Res J, P17
  • [5] INVESTIGATING CAUSAL RELATIONS BY ECONOMETRIC MODELS AND CROSS-SPECTRAL METHODS
    GRANGER, CWJ
    [J]. ECONOMETRICA, 1969, 37 (03) : 424 - 438
  • [6] TESTING FOR CAUSALITY - A PERSONAL VIEWPOINT
    GRANGER, CWJ
    [J]. JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 1980, 2 (04) : 329 - 352
  • [7] How Does Inequality Affect the Residents' Subjective Well-Being: Inequality of Opportunity and Inequality of Effort
    He, Qizhi
    Tong, Hao
    Liu, Jia-Bao
    [J]. FRONTIERS IN PSYCHOLOGY, 2022, 13
  • [8] Huang PK., 2012, APPL FINANC EC, V22, P1603, DOI [10.1080/09603107.2012.669459, DOI 10.1080/09603107.2012.669459]
  • [9] Natural resources tax volatility and economic performance: Evaluating the role of digital economy
    Ma, Qiang
    Mentel, Grzegorz
    Zhao, Xin
    Salahodjaev, Raufhon
    Kuldasheva, Zebo
    [J]. RESOURCES POLICY, 2022, 75
  • [10] Milani F., 2005, ADAPTIVE LEARNING IN, DOI [10.2139/ssrn.748865, DOI 10.2139/SSRN.748865]