Crypto Wash Trading

62 Pages Posted: 2 Mar 2020 Last revised: 28 Aug 2022

See all articles by Lin William Cong

Lin William Cong

Cornell University - Samuel Curtis Johnson Graduate School of Management; National Bureau of Economic Research (NBER)

Xi Li

University of Reading - Henley Business School,; University of Newcastle - Newcastle University Business School

Ke Tang

Institute of Economics, School of Social Sciences, Tsinghua University

Yang Yang

Institute of Economics, School of Social Sciences, Tsinghua University

Multiple version iconThere are 2 versions of this paper

Date Written: July 1, 2021

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: Bitcoin; Cryptocurrency; FinTech; Forensic Finance; Fraud Detection; Regulation

JEL Classification: G18, G23, G29

Suggested Citation

Cong, Lin and Li, Xi and Tang, Ke and Yang, Yang, Crypto Wash Trading (July 1, 2021). Available at SSRN: https://ssrn.com/abstract=3530220 or http://dx.doi.org/10.2139/ssrn.3530220

Lin Cong

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

HOME PAGE: http://www.linwilliamcong.com/

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Xi Li

University of Reading - Henley Business School, ( email )

Whiteknights
Reading, Berkshire RG6 6AH
United Kingdom

University of Newcastle - Newcastle University Business School ( email )

5 Barrack Road
Devonshire Building
NEWCASTLE UPON TYNE, NE1 7RU
United Kingdom

Ke Tang

Institute of Economics, School of Social Sciences, Tsinghua University ( email )

No.1 Tsinghua Garden
Beijing, 100084
China

Yang Yang (Contact Author)

Institute of Economics, School of Social Sciences, Tsinghua University ( email )

MingZhai Building
Beijing, 100084
China

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