IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v88y2023icp1397-1417.html
   My bibliography  Save this article

Asymmetric spillover from Bitcoin to green and traditional assets: A comparison with gold

Author

Listed:
  • Duan, Kun
  • Zhao, Yanqi
  • Wang, Zhong
  • Chang, Yujia

Abstract

This paper studies asymmetric spillovers from Bitcoin to green and traditional assets by using a full distributional framework established by a recently-developed Quantile-on-Quantile approach. The spillovers from gold to the same are further studied to compare the effectiveness of the underlying digital investment shelter of Bitcoin with its traditional counterpart of gold. Statistical evidence indicates that the cross-market spillover features evident asymmetry and non-linearity from three perspectives involving various quantiles of the joint distribution of dependent and independent variables, data in return and volatility, and before/after the COVID-19 pandemic. The investment sheltering role of Bitcoin is examined by its weakly positive, negligible, or even negative dependence with financial assets under different market conditions, while such the role is found to be relatively stronger for green assets compared to that for traditional assets. Moreover, the digital investment shelter is shown to be more effective than the traditional shelter given Bitcoin’s weaker or even more negative dependence with both green and traditional financial assets than gold. Additional analyses confirm the robustness of our findings that should be of interest to various stakeholders.

Suggested Citation

  • Duan, Kun & Zhao, Yanqi & Wang, Zhong & Chang, Yujia, 2023. "Asymmetric spillover from Bitcoin to green and traditional assets: A comparison with gold," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1397-1417.
  • Handle: RePEc:eee:reveco:v:88:y:2023:i:c:p:1397-1417
    DOI: 10.1016/j.iref.2023.06.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056023002058
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2023.06.036?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Husain, Afzol & Karim, Sitara & Sensoy, Ahmet, 2024. "Financial fusion: Bridging Islamic and Green investments in the European stock market," International Review of Financial Analysis, Elsevier, vol. 94(C).
    2. Feng, Hao & Gao, Da & Duan, Kun & Urquhart, Andrew, 2023. "Does Bitcoin affect decomposed oil shocks differently? Evidence from a quantile-based framework," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Feng, Jingyu & Yuan, Ying & Jiang, Mingxuan, 2024. "Are stablecoins better safe havens or hedges against global stock markets than other assets? Comparative analysis during the COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 275-301.
    4. Duan, Kun & Liu, Yang & Yan, Cheng & Huang, Yingying, 2023. "Differences in carbon risk spillovers with green versus traditional assets: Evidence from a full distributional analysis," Energy Economics, Elsevier, vol. 127(PA).
    5. Hunjra, Ahmed Imran & Zhao, Shikuan & Goodell, John W. & Liu, Xiaoqian, 2024. "Digital economy policy and corporate low-carbon innovation: Evidence from a quasi-natural experiment in China," Finance Research Letters, Elsevier, vol. 60(C).
    6. Chen, Yan & Liu, Yakun & Zhang, Feipeng, 2024. "Coskewness and the short-term predictability for Bitcoin return," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

    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:reveco:v:88:y:2023:i:c:p:1397-1417. 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/inca/620165 .

    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.