Author
Listed:
- Lin William Cong
(SC Johnson College of Business, Cornell University, Ithaca, New York 14853; National Bureau of Economic Research, Cambridge, Massachusetts 02138)
- Xi Li
(ICMA Centre, Henley Business School, University of Reading, Reading RG6 6BA, United Kingdom)
- Ke Tang
(Institute of Economics, School of Social Sciences, Tsinghua University, Beijing 100190, China; Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China)
- Yang Yang
(School of Engineering Mathematics and Technology, University of Bristol, Bristol BS8 1TW, United Kingdom)
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.
Suggested Citation
Lin William Cong & Xi Li & Ke Tang & Yang Yang, 2023.
"Crypto Wash Trading,"
Management Science, INFORMS, vol. 69(11), pages 6427-6454, November.
Handle:
RePEc:inm:ormnsc:v:69:y:2023:i:11:p:6427-6454
DOI: 10.1287/mnsc.2021.02709
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