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Lead Behaviour in Bitcoin Markets

Author

Listed:
  • Ying Chen

    (Department of Mathematics and Risk Management Institute, National University of Singapore, Singapore 119077, Singapore)

  • Paolo Giudici

    (Department of Economics and Management, University of Pavia, 27100 Pavia, Italy)

  • Branka Hadji Misheva

    (School of Engineering, ZHAW University of applied sciences, 8005 Zurich, Switzerland)

  • Simon Trimborn

    (Department of Mathematics, National University of Singapore, Singapore 119077, Singapore)

Abstract

We aim to understand the dynamics of Bitcoin blockchain trading volumes and, specifically, how different trading groups, in different geographic areas, interact with each other. To achieve this aim, we propose an extended Vector Autoregressive model, aimed at explaining the evolution of trading volumes, both in time and in space. The extension is based on network models, which improve pure autoregressive models, introducing a contemporaneous contagion component that describes contagion effects between trading volumes. Our empirical findings show that transactions activities in bitcoins is dominated by groups of network participants in Europe and in the United States, consistent with the expectation that market interactions primarily take place in developed economies.

Suggested Citation

  • Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    • Handle: RePEc:gam:jrisks:v:8:y:2020:i:1:p:4-:d:305277
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    References listed on IDEAS

    as
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    Cited by:

    1. Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
    2. Arianna Agosto & Alessia Cafferata, 2020. "Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market," Risks, MDPI, vol. 8(2), pages 1-14, April.

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