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Crypto Wash Trading

Lin Cong, Xi Li, Ke Tang and Yang Yang

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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.

Date: 2021-08
New Economics Papers: this item is included in nep-ban, nep-isf, nep-mst and nep-pay
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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http://arxiv.org/pdf/2108.10984 Latest version (application/pdf)

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Journal Article: Crypto Wash Trading (2023) Downloads
Working Paper: Crypto Wash Trading (2022) Downloads
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