Prediction markets are surging in popularity, allowing users to bet on everything from elections and military action to awards and celebrity news. But when traders have information the rest of the market does not, where is the line separating useful forecasting from unlawful conduct? In this episode of Bite-Sized Business Law, we speak with Joshua Mitts, the David J. Greenwald Professor of Law at Columbia Law School, about the legal questions surrounding informed trading in prediction markets. Joshua is the co-author of ‘From Iran to Taylor Swift: Informed Trading in Prediction Markets,’ which examines suspicious trading patterns across prediction platforms. Joshua explains how prediction markets work, why informed traders help them produce meaningful results, and when an information advantage becomes legally or socially concerning. He walks through case studies involving suspicious trading across national security, politics, major institutions, and celebrity news, and how confidential information can create major profits while also threatening national security, privacy, and institutional integrity. We also explore why traditional insider trading law does not apply to these markets, how the misappropriation doctrine may apply, and why anonymous blockchain wallets make enforcement difficult. Tune in to explore where prediction markets are heading and whether the law can keep up.

Key Points From This Episode:

• Introducing Joshua Mitts and his research on informed trading in prediction markets.
• Learn what prediction markets are and how their event contracts work.
• How blockchain technology has made prediction platforms more accessible.
• Discover the difference between informed trading and traditional insider trading.
• Hear why informed traders are vital for prediction markets to function.
• What made the trading before the U.S. attack on Iran seem unusually well-timed.
• Explore why the case studies in his paper raise concerns beyond national security.
• Discover how prediction markets can incentivize hacking and illegal data trading. 
• Unpack why existing insider trading laws do not apply easily to prediction markets.
• Why prediction markets make illegal trading difficult to investigate and prosecute.
• Find out how identity checks and greater platform oversight could help regulators.
• Uncover why bans are not the solution and what upcoming legislation would change.

Links Mentioned in Today’s Episode:

Joshua Mitts

Joshua Mitts on LinkedIn

Joshua Mitts on X

‘From Iran to Taylor Swift: Informed Trading in Prediction Markets’

Polymarket

Kalshi

Fordham University School of Law Corporate Law Center