IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v74y2025ics1544612324017367.html
   My bibliography  Save this article

The US-China tension and fossil fuel energy price volatility relationship

Author

Listed:
  • Li, Sitong
  • Chen, Huangen
  • Chen, Gengxuan

Abstract

Tensions in the US-China relationship and strategies such as trade sanctions and rare earth controls implemented in recent years affect the import and export shares of fossil fuels in both countries. Therefore, this paper evaluates the influence of the US-China Tension Index (UCT) on the price volatility of fossil fuels under the GARCH-MIDAS model structure. Using a rolling window approach for parameter estimation and generating forecasts, the results show that an increase in tension between the two countries raises the energy price volatility and the double asymmetric GARCH-MIDAS-UCT model beats the rest of the competition.

Suggested Citation

  • Li, Sitong & Chen, Huangen & Chen, Gengxuan, 2025. "The US-China tension and fossil fuel energy price volatility relationship," Finance Research Letters, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:finlet:v:74:y:2025:i:c:s1544612324017367
    DOI: 10.1016/j.frl.2024.106707
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324017367
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2024.106707?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    US-China tension; Fossil fuel; Volatility forecasting; GARCH-MIDAS;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:74:y:2025:i:c:s1544612324017367. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.