Working Paper: NBER ID: w30783
Authors: Lin William Cong; Xi Li; Ke Tang; Yang Yang
Abstract: We introduce systematic tests exploiting robust statistical and behavioral patterns in trading to detect fake transactions on 29 cryptocurrency exchanges. Regulated exchanges feature patterns consistently observed in financial markets and nature; abnormal first-significant-digit distributions, size rounding, and transaction tail distributions on unregulated exchanges reveal rampant manipulations unlikely driven by strategy or exchange heterogeneity. We quantify the wash trading on each unregulated exchange, which averaged over 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 userbase), market conditions, and regulation.
Keywords: Cryptocurrency; Wash Trading; Market Manipulation; Regulation
JEL Codes: G18; G23; G29
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| lack of regulation (G18) | prevalence of wash trading (G18) |
| wash trading (G10) | exchange rankings (A14) |
| exchange characteristics (age and user base) (D16) | wash trading (G10) |