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Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network

Author

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  • Weili Chen
  • Jun Wu
  • Zibin Zheng
  • Chuan Chen
  • Yuren Zhou

Abstract

The cryptocurrency market is a very huge market without effective supervision. It is of great importance for investors and regulators to recognize whether there are market manipulation and its manipulation patterns. This paper proposes an approach to mine the transaction networks of exchanges for answering this question.By taking the leaked transaction history of Mt. Gox Bitcoin exchange as a sample,we first divide the accounts into three categories according to its characteristic and then construct the transaction history into three graphs. Many observations and findings are obtained via analyzing the constructed graphs. To evaluate the influence of the accounts' transaction behavior on the Bitcoin exchange price,the graphs are reconstructed into series and reshaped as matrices. By using singular value decomposition (SVD) on the matrices, we identify many base networks which have a great correlation with the price fluctuation. When further analyzing the most important accounts in the base networks, plenty of market manipulation patterns are found. According to these findings, we conclude that there was serious market manipulation in Mt. Gox exchange and the cryptocurrency market must strengthen the supervision.

Suggested Citation

  • Weili Chen & Jun Wu & Zibin Zheng & Chuan Chen & Yuren Zhou, 2019. "Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network," Papers 1902.01941, arXiv.org.
    • Handle: RePEc:arx:papers:1902.01941
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    References listed on IDEAS

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    1. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    2. Athey, Susan & Parashkevov, Ivo & Sarukkai, Vishnu & Xia, Jing, 2016. "Bitcoin Pricing, Adoption, and Usage: Theory and Evidence," Research Papers 3469, Stanford University, Graduate School of Business.
    3. Jamal Bouoiyour & Refk Selmi, 2015. "What Does Bitcoin Look Like?," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 449-492, November.
    4. Gandal, Neil & Hamrick, JT & Moore, Tyler & Oberman, Tali, 2018. "Price manipulation in the Bitcoin ecosystem," Journal of Monetary Economics, Elsevier, vol. 95(C), pages 86-96.
    5. Gillespie, Colin S., 2015. "Fitting Heavy Tailed Distributions: The poweRlaw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i02).
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    Cited by:

    1. Friedhelm Victor & Andrea Marie Weintraud, 2021. "Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges," Papers 2102.07001, arXiv.org.
    2. Chen, Jialan & Lin, Dan & Wu, Jiajing, 2022. "Do cryptocurrency exchanges fake trading volumes? An empirical analysis of wash trading based on data mining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    3. Usman W. Chohan, 2021. "Oversight and Regulation of Cryptocurrencies: BitLicense," World Scientific Book Chapters, in: Stéphane Goutte & Khaled Guesmi & Samir Saadi (ed.), Cryptofinance A New Currency for a New Economy, chapter 6, pages 105-120, World Scientific Publishing Co. Pte. Ltd..
    4. Dean Fantazzini & Raffaella Calabrese, 2021. "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, vol. 14(11), pages 1-23, October.
    5. Karl Oton Rudolf & Samer Ajour El Zein & Nicola Jackman Lansdowne, 2021. "Bitcoin as an Investment and Hedge Alternative. A DCC MGARCH Model Analysis," Risks, MDPI, vol. 9(9), pages 1-22, August.
    6. Saggese, Pietro & Belmonte, Alessandro & Dimitri, Nicola & Facchini, Angelo & Böhme, Rainer, 2023. "Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 251-270.
    7. Tsang, Kwok Ping & Yang, Zichao, 2022. "Do connections pay off in the bitcoin market?," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 1-18.
    8. Zhengjie Huang & Zhenguang Liu & Jianhai Chen & Qinming He & Shuang Wu & Lei Zhu & Meng Wang, 2022. "Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods," Papers 2211.14779, arXiv.org.
    9. Xiao Fan Liu & Xin-Jian Jiang & Si-Hao Liu & Chi Kong Tse, 2020. "Knowledge Discovery in Cryptocurrency Transactions: A Survey," Papers 2010.01031, arXiv.org.
    10. Ioannis Giagkiozis & Emilio Said, 2023. "Reconciling Open Interest with Traded Volume in Perpetual Swaps," Papers 2310.14973, arXiv.org, revised Apr 2024.
    11. Gu, Zhuoming & Lin, Dan & Wu, Jiajing, 2022. "On-chain analysis-based detection of abnormal transaction amount on cryptocurrency exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    12. Ji, Qiang & Bouri, Elie & Kristoufek, Ladislav & Lucey, Brian, 2021. "Realised volatility connectedness among Bitcoin exchange markets," Finance Research Letters, Elsevier, vol. 38(C).

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