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Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges

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  • Friedhelm Victor
  • Andrea Marie Weintraud

Abstract

Cryptoassets such as cryptocurrencies and tokens are increasingly traded on decentralized exchanges. The advantage for users is that the funds are not in custody of a centralized external entity. However, these exchanges are prone to manipulative behavior. In this paper, we illustrate how wash trading activity can be identified on two of the first popular limit order book-based decentralized exchanges on the Ethereum blockchain, IDEX and EtherDelta. We identify a lower bound of accounts and trading structures that meet the legal definitions of wash trading, discovering that they are responsible for a wash trading volume in equivalent of 159 million U.S. Dollars. While self-trades and two-account structures are predominant, complex forms also occur. We quantify these activities, finding that on both exchanges, more than 30\% of all traded tokens have been subject to wash trading activity. On EtherDelta, 10% of the tokens have almost exclusively been wash traded. All data is made available for future research. Our findings underpin the need for countermeasures that are applicable in decentralized systems.

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  • Friedhelm Victor & Andrea Marie Weintraud, 2021. "Detecting and Quantifying Wash Trading on Decentralized Cryptocurrency Exchanges," Papers 2102.07001, arXiv.org.
    • Handle: RePEc:arx:papers:2102.07001
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Derek Liu & Francesco Piccoli & Katie Chen & Adrina Tang & Victor Fang, 2023. "NFT Wash Trading Detection," Papers 2305.01543, arXiv.org.
    2. Peter Fratrič & Giovanni Sileno & Sander Klous & Tom Engers, 2022. "Manipulation of the Bitcoin market: an agent-based study," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
    3. 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.
    4. Andrea Barbon & Angelo Ranaldo, 2023. "NFT Bubbles," Swiss Finance Institute Research Paper Series 23-20, Swiss Finance Institute.
    5. Vincent Gramlich & Tobias Guggenberger & Marc Principato & Benjamin Schellinger & Nils Urbach, 2023. "A multivocal literature review of decentralized finance: Current knowledge and future research avenues," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-37, December.
    6. Mohammad Javad Rajaei & Qusay H. Mahmoud, 2023. "A Survey on Pump and Dump Detection in the Cryptocurrency Market Using Machine Learning," Future Internet, MDPI, vol. 15(8), pages 1-17, August.
    7. Weber, Daniel, 2022. "Exploring markets: Non-Fungible Token," IU Discussion Papers - Business & Management 2 (April 2022), IU International University of Applied Sciences.
    8. Mingxiao Song & Yunsong Liu & Agam Shah & Sudheer Chava, 2023. "Abnormal Trading Detection in the NFT Market," Papers 2306.04643, arXiv.org, revised Aug 2023.
    9. 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).
    10. Kaihua Qin & Liyi Zhou & Yaroslav Afonin & Ludovico Lazzaretti & Arthur Gervais, 2021. "CeFi vs. DeFi -- Comparing Centralized to Decentralized Finance," Papers 2106.08157, arXiv.org, revised Jun 2021.

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