Detecting unusual trading patterns on cryptocurrency exchanges by means of complexity measures
Finding fake trades on crypto exchanges by measuring market chaos
Researchers developed a method to spot unusual trading patterns on cryptocurrency exchanges by analyzing the statistical complexity of trades rather than just price movements. Applied to Bitcoin, Ethereum, and Ripple across four major exchanges in spring 2025, the approach uncovered a striking anomaly on Bitget: after mid-May, transaction counts spiked dramatically while actual trading volume and price movement stayed flat—a signature suggesting artificially inflated trade numbers rather than genuine market activity.
Cryptocurrency exchanges have no consistent oversight, making them vulnerable to manipulation schemes like wash trading, where fake transactions create a false impression of liquidity and market health. This detection method could help regulators and traders identify when an exchange's reported activity doesn't match real money flowing through it, reducing the risk of losses from trading on artificially inflated markets. The technique works where price-based monitoring fails, making it a practical tool for auditing exchange integrity.