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arXiv:2108.10984econ.GN

Crypto Wash Trading

Lin William Cong, Xi Li, Ke Tang, Yang Yang

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

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.

arXiv comments
Journal reference
DOI
doi:10.2139/ssrn.3530220
Subjects
econ.GNGeneral Economics

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Dec 2022 to Dec 2022. Found in 1 HN submission from Nov 2021 to Nov 2021. Open submission discussions.

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Discussed in comments1 thread

  1. Crypto Wash Trading 1 comment
    • Seems to be the same paper as this preprint on arXiv from last August: https://arxiv.org/abs/2108.10984 Earlier discussion: https://news.ycombinator.com/item?id=29279146

      loegView on HNParent context

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