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

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  • 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
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    References listed on IDEAS

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    1. Huang, Yingying & Duan, Kun & Urquhart, Andrew, 2023. "Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    2. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    3. Hsu, Shu-Han & Sheu, Chwen & Yoon, Jiho, 2021. "Risk spillovers between cryptocurrencies and traditional currencies and gold under different global economic conditions," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
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    Cited by:

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    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. He, Xie & Hamori, Shigeyuki, 2024. "Asymmetric Higher-Moment spillovers between sustainable and traditional investments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
    4. Ben Jabeur, Sami & Gozgor, Giray & Rezgui, Hichem & Mohammed, Kamel Si, 2024. "Dynamic dependence between quantum computing stocks and Bitcoin: Portfolio strategies for a new era of asset classes," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    5. 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.
    6. 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).
    7. 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).
    8. 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).

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