Liquidity Jump, Liquidity Diffusion, and Crypto Wash Trading

TL;DR

This paper introduces a real-time liquidity-based framework to detect wash trading in crypto assets by analyzing liquidity jumps and diffusion, validated through US stock benchmarks and simulated regulatory interventions.

Contribution

It presents novel liquidity measures for identifying wash trading in crypto markets and demonstrates their effectiveness through empirical analysis and a theoretical model.

Findings

Elevated liquidity jump and diffusion indicate wash trading activity.

Regulatory simulation reduces liquidity diffusion but not liquidity jump.

Theoretical model links trader behavior to liquidity fluctuations.

Abstract

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.