Crypto Wash Trading

Lin Cong, Xi Li (), Ke Tang and Yang Yang ()
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Xi Li: ICMA Centre, Henley Business School, University of Reading, Reading RG6 6BA, United Kingdom
Yang Yang: School of Engineering Mathematics and Technology, University of Bristol, Bristol BS8 1TW, United Kingdom

Management Science, 2023, vol. 69, issue 11, 6427-6454

Abstract: We present the first systematic approach to detect fake transactions on cryptocurrency exchanges by exploiting robust statistical and behavioral regularities associated with authentic trading. Our sample consists of 29 centralized exchanges, among which the regulated ones feature transaction patterns consistently observed in financial markets and nature. In contrast, unregulated exchanges display abnormal first significant digit distributions, size rounding, and transaction tail distributions, indicating widespread manipulation unlikely driven by a specific trading strategy or exchange heterogeneity. We then quantify the wash trading on each unregulated exchange, which averaged more than 70% of the reported volume. We further document how these fabricated volumes (trillions of dollars annually) improve exchange ranking, temporarily distort prices, and relate to exchange characteristics (e.g., age and user base), market conditions, and regulation. Overall, our study cautions against potential market manipulations on centralized crypto exchanges with concentrated power and limited disclosure requirements and highlights the importance of fintech regulation.

Keywords: Bitcoin; CeFi; cryptocurrency; forensic finance; fraud detection; regulation (search for similar items in EconPapers)
Date: 2023
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http://dx.doi.org/10.1287/mnsc.2021.02709 (application/pdf)

Related works:
Working Paper: Crypto Wash Trading (2022)
Working Paper: Crypto Wash Trading (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:69:y:2023:i:11:p:6427-6454

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