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Detecting Crypto Wash Trading with Liquidity Jumps and Diffusion

Article arXiv papers · Author: Qi Deng et al.
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Summary

The document proposes detecting possible wash trading in crypto markets by measuring short-term liquidity fluctuations. It defines liquidity jump as the size of a fluctuation and liquidity diffusion as its volatility. The suggested signal is the joint elevation of both measures, assessed against US stocks as a benchmark, with the aim of distinguishing manipulation-related activity from ordinary liquidity changes.

The paper reports that a simulated regulatory intervention removing likely wash trades significantly lowers liquidity diffusion while leaving liquidity jump largely unchanged. It interprets this pattern through a model in which manipulative traders increase both the level and variability of price pressure, while passive investors affect the level alone. The approach is presented as a monitoring tool for investors and regulators, but the excerpt gives no sample details, thresholds, or validation beyond the stated comparison and simulation. The measures therefore indicate a proposed market-quality signal, not definitive proof that any particular trading activity is manipulation.

Key ideas

  • Liquidity jump measures the size of short-term liquidity fluctuations, while liquidity diffusion measures their volatility.
  • The proposed wash-trading signal is a joint increase in both liquidity measures.
  • US stocks serve as a benchmark for evaluating the crypto liquidity patterns.
  • A simulated removal of likely wash trades reduces liquidity diffusion but leaves liquidity jump largely unchanged.
  • The framework is a monitoring aid and does not establish that every flagged fluctuation is manipulation.

Tags

CryptoMarket microstructureStatisticsRisk management
Full text
# Liquidity Jump, Liquidity Diffusion, and Crypto Wash Trading


# Liquidity Jump, Liquidity Diffusion, and Crypto Wash Trading









We develop a new framework to detect wash trading in crypto assets through real-time liquidity fluctuation. We propose that short-term price jumps in crypto assets results from wash trading-induced liquidity fluctuation, and construct two complementary liquidity measures, liquidity jump (size of fluctuation) and liquidity diffusion (volatility of fluctuation), to capture the behavioral signature of wash trading. Using US stocks as a benchmark, we demonstrate that joint elevation in both liquidity metrics indicates wash trading in crypto assets. A simulated regulatory treatment that removes likely wash trades confirms this dynamic: it reduces liquidity diffusion significantly while leaving liquidity jump largely unaffected. These findings align with a theoretical model in which manipulative traders amplify both the level and variance of price pressure, whereas passive investors affect only the level. Our model offers practical tools for investors to assess market quality and for regulators to monitor manipulation risk on crypto exchanges without oversight.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.