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Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy

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  • Duan, Kun
  • Gao, Yang
  • Mishra, Tapas
  • Satchell, Stephen

Abstract

Heterogeneity in informational inefficiency in a cross-market virtual currency, such as Bitcoin, allows for the extraction of differential gains from a portfolio of investments over time. In this paper, we measure inefficiency in five country/region segmented Bitcoin markets based on dynamic estimation of the fractional integration order of their price series. Results reveal a time-varying and country-specific pattern of inefficiency in the five Bitcoin markets, although the degree of inefficiency in each market has declined over time. Further, we introduce a new decomposition method to disentangle components of the inefficiency degree. Results suggest that the total variation around the convergence benchmark has fallen, whilst the proportion due to the difference between convergence and efficiency has risen from approximately 77% in 2013 to almost 100% in 2020. Besides, evidence of convergence emerges until the outbreak of COVID-19, beyond which the inefficiency degree diverges measurably. We show that Bitcoin markets have become more efficient after the first-wave COVID era and then the nature of market segmentation has played a less important role, levelling the cross-market difference and thus reducing the potential for arbitrage.

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  • 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).
    • Handle: RePEc:eee:intfin:v:83:y:2023:i:c:s1042443123000100
    DOI: 10.1016/j.intfin.2023.101742
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    2. Hyeonoh Kim & Eojin Yi & Jooyoung Jeon & Taeyoung Park & Kwangwon Ahn, 2024. "After the Split: Market Efficiency of Bitcoin Cash," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 411-427, July.
    3. Aliu, Florin, 2024. "Do infectious diseases explain Bitcoin price Fluctuations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 93(C).
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    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. Shimeng Shi & Jia Zhai & Yingying Wu, 2024. "Informational inefficiency on bitcoin futures," The European Journal of Finance, Taylor & Francis Journals, vol. 30(6), pages 642-667, April.
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    More about this item

    Keywords

    Bitcoin; Long-memory; Market efficiency; Market segmentation; COVID-19 epidemic;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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