Direct Evidence of Bitcoin Wash Trading

84 Pages Posted: 3 Jun 2019 Last revised: 18 Jan 2024

See all articles by Arash Aloosh

Arash Aloosh

EMLV Business School Paris

Jiasun Li

George Mason University - Department of Finance

Date Written: December 18, 2022

Abstract

We use the internal trading records of a major Bitcoin exchange leaked by hackers to detect and characterize wash trading — a type of market manipulation in which a single trader clears her own limit orders to “cook” transaction records. Our finding provides direct evidence for the widely-suspected “fake volume” allegation against cryptocurrency exchanges, which has so far only been backed by indirect estimation. We then use our direct evidence to evaluate various indirect techniques for detecting the presence of wash trades and find measures based on Benford’s law, trade size clustering, lognormal distributions, and structural breaks to be useful, while ones based on power law tail distributions to give opposite conclusions. We also provide suggestions to effectively apply various indirect estimation techniques.

Keywords: bitcoin; cryptocurrency; exchanges; forensics; market manipulation; regulation.

JEL Classification: G12, G18, O31, O35

Suggested Citation

Aloosh, Arash and Li, Jiasun, Direct Evidence of Bitcoin Wash Trading (December 18, 2022). Available at SSRN: https://ssrn.com/abstract=3362153 or http://dx.doi.org/10.2139/ssrn.3362153

Arash Aloosh

EMLV Business School Paris ( email )

12 Av. Léonard de Vinci
Paris, La Défense 92400
France

Jiasun Li (Contact Author)

George Mason University - Department of Finance ( email )

Fairfax, VA 22030
United States

HOME PAGE: http://sites.google.com/view/jiasunli

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