Prediction markets may need a balanced approach to insider trading rules, according to new academic research cited by Cointelegraph. ⚖️ Research suggests price accuracy may be highest when enforcement is “calibrated,” not maximal Too little enforcement could let insiders crowd out regular participants Too much enforcement may reduce useful information that improves market pricing The paper argues enforcement should vary by information source — from researched insights to leaked or outcome-influencing information Kalshi is reportedly adding employment disclosure requirements for users in certain sensitive markets A key debate for prediction markets: how to protect fairness without reducing market efficiency.
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