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Extreme risk transmission among bitcoin and crude oil markets

Author

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  • Li, Dongxin
  • Hong, Yanran
  • Wang, Lu
  • Xu, Pengfei
  • Pan, Zhigang

Abstract

In the period of extreme events, this paper aims to study the extreme risk transmission between Bitcoin and crude oil market by using the extreme Granger causality test to test their causal relationship under extreme and non-extreme shocks. First, we can obtain different shocks of Bitcoin and crude oil returns based on empirical quantiles. Second, considering the different role that these shocks played in the causality between Bitcoin and crude oil, we conduct our research by testing the causality among different pairwise shocks. Further, given that these relationships may be changed at different time horizons, we also detect them from a frequency-domain perspective. Hence, we not only find the strong evidence of extreme risk transmission between Bitcoin and crude oil but also investigate the time-varying characteristic of this transmission, which may have a great impact on market participants and scholars related to Bitcoin-oil relations.

Suggested Citation

  • Li, Dongxin & Hong, Yanran & Wang, Lu & Xu, Pengfei & Pan, Zhigang, 2022. "Extreme risk transmission among bitcoin and crude oil markets," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722002094
    DOI: 10.1016/j.resourpol.2022.102761
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    4. Liu, Guangqiang & Zeng, Qing & Lei, Juan, 2022. "Dynamic risks from climate policy uncertainty: A case study for the natural gas market," Resources Policy, Elsevier, vol. 79(C).
    5. Mustafa Tevfik Kartal & Mustafa Kevser & Fatih Ayhan, 2023. "Asymmetric effects of global factors on return of cryptocurrencies by novel nonlinear quantile approaches," Economic Change and Restructuring, Springer, vol. 56(3), pages 1515-1535, June.
    6. Youssef El-Khatib & Abdulnasser Hatemi-J, 2023. "On a regime switching illiquid high volatile prediction model for cryptocurrencies," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(2), pages 485-498, July.
    7. Lu, Xunfa & Huang, Nan & Mo, Jianlei, 2024. "Time-varying causalities from the COVID-19 media coverage to the dynamic spillovers among the cryptocurrency, the clean energy, and the crude oil," Energy Economics, Elsevier, vol. 132(C).
    8. Liu, Jianjian & Wang, Shuhan & Xiang, Lijin & Ma, Shiqun & Xiao, Zumian, 2024. "Unveiling hidden connections: Spillover among BRICS' cryptocurrency-implied exchange rate discounts and US financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    9. Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Oil price and the Bitcoin market," Resources Policy, Elsevier, vol. 82(C).
    10. Hong, Yanran & Wang, Lu & Ye, Xiaoqing & Zhang, Yaojie, 2022. "Dynamic asymmetric impact of equity market uncertainty on energy markets: A time-varying causality analysis," Renewable Energy, Elsevier, vol. 196(C), pages 535-546.
    11. Goodell, John W. & Ben Jabeur, Sami & Saâdaoui, Foued & Nasir, Muhammad Ali, 2023. "Explainable artificial intelligence modeling to forecast bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 88(C).
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    More about this item

    Keywords

    Bitcoin; Crude oil markets; Granger causality; Extreme risk transmission; Time-frequency domain;
    All these keywords.

    JEL classification:

    • 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
    • F39 - International Economics - - International Finance - - - Other
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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