Executing offsetting buy and sell transactions to inflate apparent trading volume without taking real market risk. On prediction markets, wash trading can artificially boost platform metrics and distort liquidity signals, and is federally prohibited under the Commodity Exchange Act.
Cluster: Liquidity & Trading
Executing offsetting buy and sell transactions to inflate apparent trading volume without taking real market risk. On prediction markets, wash trading can artificially boost platform metrics and distort liquidity signals, and is federally prohibited under the Commodity Exchange Act.
Referenced in 2 articles
Kalshi's perpetual futures on Bitcoin and Ether topped a billion dollars of volume in their first week, and a recent paper flagged a striking anomaly in the trade-level data: almost sixty percent of the Ether perp's volume came from trades of nearly identical dollar size, which it attributed to wash trading. Sethi offers a cleaner explanation grounded in Kalshi's market-maker rewards. Because a perp tracks its underlying almost instantly, a maker who posts at the minimum size needed for the rebate is exposed to adverse selection, and any quote that survives even briefly gets picked off in a single fill by arbitrageurs watching the spot price. Volume therefore clusters at the reward threshold without any colluding counterparties, but the rewards end up flowing to aggressive low-latency traders rather than buying the resting liquidity they were meant to purchase. Sethi argues the fee refunds Kalshi pays high-volume takers make this worse, and notes a recent CFTC advisory warning that incentive schemes built around volume targets invite exactly this kind of distortion.
Examines how to distinguish wash trading from legitimate market making on Polymarket using network analysis. Wash traders exhibit homophily, trading only within their collusive group, while market makers trade indiscriminately with diverse counterparties. Describes an algorithm developed by Columbia researchers that identified a cluster of 200 wallets generating $113 million in volume with just $57.86 in aggregate losses.