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Research Recommends Balanced Insider Trading Enforcement in Prediction Markets, Released June 2

Prediction Market

2026-06-10 08:51:46

According to research released on June 2, Stevens Institute of Technology professor Balbinder Singh Gill recommends that prediction market regulators adopt a balanced approach to insider trading rather than imposing outright bans. In a formal economic model, Gill found that market accuracy follows a "hump-shaped" relationship with enforcement intensity: too little enforcement allows insiders to dominate and crowd out other participants, while excessive enforcement removes valuable information insiders contribute. Gill concluded that optimal enforcement lies in the middle, distinguishing between different information sources—allowing legitimate research while strictly regulating information from leaks or misappropriation. The findings coincide with increased regulatory scrutiny, including CFTC warnings in April and Congressional investigations into prediction market platforms in May.

Disclaimer: The information on this page may come from third-party sources and is for reference only. It does not represent the views or opinions of Gate and does not constitute any financial, investment, or legal advice. Virtual asset trading involves high risk. Please do not rely solely on the information on this page when making decisions. For details, see the Disclaimer.

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