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Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis

Author

Listed:
  • Pengfei Wang

    (Tianjin University)

  • Wei Zhang

    (Tianjin University)

  • Xiao Li

    (Nankai University)

  • Dehua Shen

    (Tianjin University)

Abstract

This paper gives the first empirical evidence on the relationships between trading volume and return volatility of the Bitcoin denominated in fifteen foreign currencies by investigating two competing hypotheses, i.e., mixture of distribution hypothesis (MDH) and sequential information arrival hypothesis (SIAH). Allowing for both linear and nonlinear correlation and causality tests, the empirical results mainly show that: first, trading volume and return volatility are negatively correlated, implying a lack of support for the MDH; second, we document significant lead–lag relationships between trading volume and return volatility, which support the SIAH; third, the results are robust to alternative measurements of trading volume, data source and sub-period analysis. Generally speaking, these findings have practical implications for investors, who are interested in investing in Bitcoin market.

Suggested Citation

  • Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    • Handle: RePEc:spr:jeicoo:v:14:y:2019:i:2:d:10.1007_s11403-019-00250-9
    DOI: 10.1007/s11403-019-00250-9
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    Cited by:

    1. Kais Tissaoui & Taha Zaghdoudi & Khaled issa Alfreahat, 2020. "Can intraday public information explain Bitcoin Returns and Volatility? A PGARCH-Based Approach," Economics Bulletin, AccessEcon, vol. 40(3), pages 2085-2092.
    2. Min Liu & Wei‐Chong Choo & Chi‐Chuan Lee & Chien‐Chiang Lee, 2023. "Trading volume and realized volatility forecasting: Evidence from the China stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 76-100, January.
    3. Ao Shu & Feiyang Cheng & Jianlei Han & Zini Liang & Zheyao Pan, 2023. "Arbitrage across different Bitcoin exchange venues: Perspectives from investor base and market related events," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(5), pages 5183-5210, December.
    4. Clement Moyo & Andrew Phiri, 2023. "Re-Examining Bitcoin’s Price–Volume Relationship: A Time-Varying Spectral Analysis," JRFM, MDPI, vol. 16(7), pages 1-16, July.
    5. Adedeji Daniel Gbadebo, 2023. "Dynamic Asymmetric Causality of Bitcoin’s Price-Volume Relation," SAGE Open, , vol. 13(4), pages 21582440231, December.
    6. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    7. Beata Szetela & Grzegorz Mentel & Yuriy Bilan & Urszula Mentel, 2021. "The relationship between trend and volume on the bitcoin market," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 25-42, March.

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    More about this item

    Keywords

    Bitcoin; Trading volume; Return volatility; Mixture of distribution hypothesis; Sequential information arrival hypothesis; Foreign currencies;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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