Polymarket wash trading: study finds 25% artificial volume and $2.59B peak

A Columbia University study says wash trading inflated Polymarket reported activity on the Polymarket platform; the finding affects how investors interpret headline volume and the credibility of crypto prediction platforms.

What did the Columbia University study find about polymarket volumes and wash trading?

The research, co-authored among the others by Yash Kanoria, identifies repeated self trades and other artificial trading that raise reported volumes without adding genuine liquidity.

However, the authors do not allege that Polymarket itself orchestrated wrongdoing; instead, they say the crypto structure could have enabled the pattern. Moreover, the paper provides methods so others can replicate and test the results.

How much of the activity was artificial?

The study estimates that about 25% of buy and sell transactions over the last three years were wash trades. In addition, the researchers report market level differences: sports markets showed the largest distortion, while crypto markets were the smallest contributors to artificial volume.

How do per market breakdowns and rival data reshape views on prediction market fraud?

Specifically, the paper places artificial trading at 45% of all time volume in sports markets, 17% in election markets, 12% in politics markets, and 3% in crypto markets. Meanwhile, Polymarket reached a record trading high of $2.59 billion in October, and the platform secured $205 million in funding across 2024025 at a reported valuation of $1.2 billion. These figures complicate simple readings of notional volume as a proxy for market health.

What do accuracy and rival volumes tell us?

Notably, independent trackers report Polymarket’s market closing accuracy above 95% in many events, which supports its forecasting credibility despite volume issues. At the same time, rival Kalshi posted a monthly trading record above $4.39 billion in October, underscoring competitive dynamics in crypto and regulated prediction markets.

What are the regulatory consequences and next steps?

Regulators have already intervened: the CFTC previously imposed a civil penalty of $1.4 million and restricted U.S. user access, actions that highlight legal risks for unregistered offerings. Consequently, market participants and platforms may seek clearer surveillance, standardised reporting, and third party volume verification.

Finally, the study’s authors stress replication and peer review; until further independent analyses appear, investors should read headline trading numbers with caution and weigh both accuracy metrics and potential manipulation indicators when assessing prediction market data.