Crypto Wash Trading

• 成果类型: Article
• 署名作者: Cong, Lin William; Li, Xi; Tang, Ke; Yang, Yang
• 署名单位: Cornell University; National Bureau of Economic Research; University of Reading; Tsinghua University; University of Bristol
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2021.02709
• 发表日期: 2023
• 页码: 6427-6454
• 关键词: Bitcoin; CeFi; Cryptocurrency; forensic finance; fraud detection; regulation

摘要

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.