- Columbia University reports wash trading in Polymarket trades.
- 25% of trades identified as inflated.
- No public statement from Polymarket leadership.
Columbia University’s study reveals that 25% of trades on the decentralized prediction market Polymarket were artificially inflated, highlighting significant wash trading activities during December 2024.
This revelation calls into question the integrity of such platforms, with potential impacts on user trust and market dynamics but no immediate systemic risk for broader crypto ecosystems.
Columbia Study Reveals 25% of Polymarket Trades Inflated
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A Columbia University study claims that 25% of trades on Polymarket are artificially inflated via wash trading. The study indicates some periods show up to 60% inflated trades. This research is based on extensive transaction data analysis.
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Research led by Rajiv Sethi and Yash Kanoria underscores the prevalence of wash trading in Polymarket. Their findings point to notable influence on specific market categories. Polymarket leadership has not commented publicly on the issue.
Rajiv Sethi, Professor of Economics at Columbia University, remarked, “Approximately 25% of trades on Polymarket are artificially inflated via wash trading, with some periods peaking as high as 60%.”
The study has not yet triggered immediate financial or regulatory actions. However, the revelation could influence user trust and reduce platform reputation, indirectly affecting the platform’s total value locked and user base interest.
No official statement from Polymarket’s executive team or major industry figures such as KOLs and regulators has been observed. Financial impacts remain superficial, although potential long-term shifts could alter market dynamics.
Despite the significant wash trading figure, ETH and BTC markets show no immediate reaction. Still, the broader prediction market sector may face scrutiny, especially in decentralized ecosystems. Past occurrences have led to protocol changes.
Potential regulatory and technological implications require market oversight and stringent transaction monitoring. Aligning incentives to deter wash trading presents a challenge. Similar historical trends suggest a need for governance adjustments among prediction markets.
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