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Visibility graph analysis of Bitcoin price series

Author

Listed:
  • Liu, Keshi
  • Weng, Tongfeng
  • Gu, Changgui
  • Yang, Huijie

Abstract

The Bitcoin market attracts special attentions for its inspirational advantages over the traditional currency system. It can be regarded also as a typical social experiment of rare item markets. Analyzing the records for Bitcoin price can deepen our understanding of this market and provide us a useful reference for rare item markets. In this paper, by means of the visibility graph algorithm we display multi-scale patterns of visible relationships in Bitcoin volatility series. It is found that the visibility graph of Bitcoin is scale-free and has a hierarchical structure. At different time scales, the system works subsequently with an identical dynamical mechanism. These behaviors are shared by other virtual currencies and even the gold price series.

Suggested Citation

  • Liu, Keshi & Weng, Tongfeng & Gu, Changgui & Yang, Huijie, 2020. "Visibility graph analysis of Bitcoin price series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    • Handle: RePEc:eee:phsmap:v:538:y:2020:i:c:s0378437119316723
    DOI: 10.1016/j.physa.2019.122952
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    References listed on IDEAS

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    1. Lahmiri, Salim & Bekiros, Stelios & Salvi, Antonio, 2018. "Long-range memory, distributional variation and randomness of bitcoin volatility," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 43-48.
    2. Bariviera, Aurelio F., 2017. "The inefficiency of Bitcoin revisited: A dynamic approach," Economics Letters, Elsevier, vol. 161(C), pages 1-4.
    3. Blau, Benjamin M., 2018. "Price dynamics and speculative trading in Bitcoin," Research in International Business and Finance, Elsevier, vol. 43(C), pages 15-21.
    4. Bariviera, Aurelio F. & Basgall, María José & Hasperué, Waldo & Naiouf, Marcelo, 2017. "Some stylized facts of the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 82-90.
    5. Yang, Yue & Wang, Jianbo & Yang, Huijie & Mang, Jingshi, 2009. "Visibility graph approach to exchange rate series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4431-4437.
    6. Yang, Yue & Yang, Huijie, 2008. "Complex network-based time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(5), pages 1381-1386.
    7. Lahmiri, Salim & Bekiros, Stelios, 2018. "Chaos, randomness and multi-fractality in Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 28-34.
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    Cited by:

    1. Partida, Alberto & Gerassis, Saki & Criado, Regino & Romance, Miguel & Giráldez, Eduardo & Taboada, Javier, 2022. "The chaotic, self-similar and hierarchical patterns in Bitcoin and Ethereum price series," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    2. Davide Provenzano & Rodolfo Baggio, 2021. "Complexity traits and synchrony of cryptocurrencies price dynamics," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 941-955, December.
    3. Zhu, Jia & Wei, Daijun, 2021. "Analysis of stock market based on visibility graph and structure entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 576(C).
    4. Cao, Run-Hua & Deng, Zheng-Hong & Xu, Ji-Wei, 2022. "Analysis of precipitation characteristics in Shanghai based on the visibility graph algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).

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