IDEAS home Printed from https://ideas.repec.org/a/hin/complx/6162671.html
   My bibliography  Save this article

A Lead-Lag Relationship and Forecast Research between China’s Crude Oil Futures and Spot Markets

Author

Listed:
  • Chi Zhang
  • Dandan Pan
  • Mingyan Yang
  • Zhengning Pu
  • Paulo Jorge Silveira Ferreira

Abstract

The integration of the global economy has led to an increasingly strong connection between the futures and spot markets of commodities. First, based on one-minute high-frequency prices, this paper applies the thermal optimal path (TOP) method to examine the lead-lag relationship between Chinese crude oil futures and spot from March 2018 to December 2021. Second, we apply the Mixed Frequency Data Sampling Regression (MIDAS) model and indicators such as deviation degree to test the degree of prediction of high-frequency prices in the futures market to the spot market. The experimental results show that the futures markets lead the spot market most of the time, but the lead effect reverses when major events occur; 60-minute futures high-frequency prices are the most predictive of daily spot data; crude oil futures’ predictive power declined after the Covid-19 outbreak and is more predictive when night trading is available. This study has important implications, not only to guide investors but also to provide empirical evidence and valid information for policy makers.

Suggested Citation

  • Chi Zhang & Dandan Pan & Mingyan Yang & Zhengning Pu & Paulo Jorge Silveira Ferreira, 2022. "A Lead-Lag Relationship and Forecast Research between China’s Crude Oil Futures and Spot Markets," Complexity, Hindawi, vol. 2022, pages 1-12, April.
    • Handle: RePEc:hin:complx:6162671
    DOI: 10.1155/2022/6162671
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2022/6162671.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/complexity/2022/6162671.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/6162671?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
    ---><---

    More about this item

    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:hin:complx:6162671. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.