Researcher Says a Total Ban on Insider Trading Could Hurt Prediction Markets

A researcher cited in a new academic discussion says a “maximal” ban on insider trading could undermine prediction markets rather than improve them. Balbinder Singh Gill argued that informed trades can help prices reflect reality more accurately, even if they raise concerns about fairness.

The point matters because prediction markets rely on active participation to produce useful signals. According to Gill, “The same insider trade that improves the accuracy of the price today can reduce the participation that makes the price informative tomorrow.”

That creates a tension for platforms and regulators: tighter restrictions may make markets feel cleaner, but they can also reduce the flow of information that gives prediction markets value in the first place. The research suggests that the design of these markets may need to balance integrity rules with the need for informed trading.

For crypto and broader market participants, the debate is relevant because prediction markets are often used as real-time tools for gauging sentiment and expectations. The findings add another layer to ongoing questions about how much access informed traders should have in markets that depend on fast, credible price discovery.