IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v128y2023ics0140988323006928.html
   My bibliography  Save this article

The hedging performance of green bond markets in China and the U.S.: Novel evidence from cryptocurrency uncertainty

Author

Listed:
  • Zhong, Yufei
  • Chen, Xuesheng
  • Wang, Chengfang
  • Wang, Zhixian
  • Zhang, Yuchen

Abstract

Analysing the green bond's hedging performance against cryptocurrency uncertainty is essential to maximising investment returns. The study innovatively uses the TVP-SV-VAR process to capture the time-dependent connection among cryptocurrency uncertainties and the green bond markets in China and the U.S. The quantitative outcomes present that cryptocurrency policy uncertainty (CPU) has favourable effects on China's green bond (CGB), often evidencing the property of China's green bond to hedge against cryptocurrency uncertainty. However, CPU's adverse and insignificant impacts on CGB refute this opinion. CPU has negative effects on U.S. green bonds (USGB) most of the time, which underlines that the U.S. green bond market is not an effectual safe haven against cryptocurrency uncertainty. By comparison, China's green bond has better hedging performance than the U.S. one regarding the uncertainties in the cryptocurrency market. Additionally, various time points accompanied by massive undulations in CPU and critical incidents exhibit interrelations among CPU, CGB and USGB. Further, we replace CPU with cryptocurrency price uncertainty (CPRU) to examine the robustness and confirm that the reported results and corresponding discussions are credible. Under the severe cryptocurrency risks, the conclusion offers significant implications to investors and relevant policymakers.

Suggested Citation

  • Zhong, Yufei & Chen, Xuesheng & Wang, Chengfang & Wang, Zhixian & Zhang, Yuchen, 2023. "The hedging performance of green bond markets in China and the U.S.: Novel evidence from cryptocurrency uncertainty," Energy Economics, Elsevier, vol. 128(C).
    • Handle: RePEc:eee:eneeco:v:128:y:2023:i:c:s0140988323006928
    DOI: 10.1016/j.eneco.2023.107194
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988323006928
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2023.107194?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

    Green bond; Hedging performance; Cryptocurrency uncertainty; Time-dependent; China; The United States;
    All these keywords.

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:eneeco:v:128:y:2023:i:c:s0140988323006928. 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/eneco .

    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.