Insider Trading Concerns in Prediction Markets

A significant wager placed on the Polymarket platform has drawn attention to the regulatory status of prediction markets. Just prior to the capture of Venezuelan President Nicolás Maduro, a newly created account bet $30,000 on his ouster, resulting in a payout of over $400,000. This event has raised questions about whether the bettor possessed inside information regarding US government plans.

The Commodity Futures Trading Commission (CFTC) oversees prediction markets, but the rules regarding insider trading are not as clearly defined as they are for the stock market. While the Securities and Exchange Commission (SEC) strictly prohibits trading on material non-public information, the CFTC's approach is more ambiguous. The main rule prohibiting such activity is only 15 years old and was designed for commodities rather than event betting. Consequently, there is currently no general statutory standard that explicitly bans trading on insider information across all prediction markets.

Platforms vary in their policies. Some, like Kalshi, explicitly ban insider trading, while others, such as Polymarket, are more lenient. Furthermore, tracking and proving insider trading on these platforms is difficult for regulators. Experts suggest that while the CFTC could bring cases, the agency lacks the resources and appetite to do so effectively. The debate continues over whether insider knowledge enhances market accuracy or undermines fairness.

The recent activity on prediction markets began with a specific, high-stakes wager. Just ahead of the first weekend of January, a bettor utilized a newly created account to place a $30,000 position on the exit of Venezuelan President Nicolás Maduro. The bet proved lucrative, yielding over $400,000 in winnings. This specific instance of success has intensified scrutiny on the mechanisms of these platforms.

However, this is not an isolated incident. In December, a different user on Polymarket reportedly made $1 million by correctly guessing 22 out of 23 of Google's most searched terms for the year. These patterns of success have led some observers to question if participants are utilizing private knowledge to gain an advantage.

The core function of prediction markets is to aggregate information to forecast future events. Some argue that encouraging knowledgeable insiders to participate improves the accuracy of these forecasts. However, this creates a tension with the concept of fair play. As one former regulator noted, prediction markets are "ripe" for an insider trading case, though whether action is taken remains a separate question.

The regulatory environment for prediction markets is distinct from that of traditional stock exchanges. The CFTC oversees these markets, but its track record of pursuing insider trading violations is sparse compared to the SEC. The primary regulation in this space is a rule established roughly 15 years ago as part of the Dodd-Frank regulations. This rule mimics the SEC's ban but applies to commodities and derivatives.

The rule prohibits trading based on private information obtained "in breach of a pre-existing duty" or through fraud. Legal experts explain that this means if a person has a fiduciary duty to keep information secret and trades on it anyway, they are in violation. However, the application of this rule to prediction markets is considered an "awkward fit."

Yesha Yadav, a professor at Vanderbilt University's law school, describes the situation as an "evolving regulatory approach." She notes that there is currently a "lack of clarity" regarding how existing CFTC regulations should be applied to prediction markets. The agency has brought few cases under this rule, and those it has brought were settled rather than litigated in court, leaving little legal precedent.

Even if the CFTC wished to crack down on insider trading, significant logistical hurdles exist. Gathering evidence requires substantial resources that the agency may not possess. Additionally, the nature of some platforms makes it difficult to track the identities of those placing bets. Given the CFTC's generally "hands-off" approach to prediction markets, there is currently little appetite for such scrutiny.

Platforms themselves adopt varying stances on the issue:

• Kalshi: Explicitly bans insider trading and supports legislation to bar government officials from using nonpublic information.
• Polymarket: Is more lenient regarding the practice. The platform's CEO has previously stated that it is "cool" that the platform creates a financial incentive for people to divulge information to the market.
• Manifold Markets: A smaller competitor that encourages the practice, though it generally does not use real money.

There is a delicate balance between maintaining market integrity and ensuring accuracy. If platforms are perceived as rigged because insiders always win, liquidity may dry up. As Aitan Goelman, a former CFTC enforcement head, noted regarding Polymarket's perspective: "They don't want it to look like everything's gamed and unfair."

Determining what constitutes insider information in the context of event betting is complex. In traditional securities, it is clear: knowing about an unannounced product launch at a company like Meta is insider information. In prediction markets, the lines are blurred.

Experts offer hypothetical scenarios to illustrate the gray area:

• Clear Violation: If a family member of a high-ranking official bets based on confidential government plans.
• Likely Permissible: If a pizza delivery worker near the Pentagon notices a surge in orders and bets on geopolitical events.
• Complex Case: If Taylor Swift bets on her own wedding date, she possesses the information, but she is also the one controlling the event.

Ultimately, the legality of the underlying markets themselves is also in question. Critics argue that prediction markets are essentially gambling and should be regulated as such. Until the legal status is clarified and the CFTC develops a clearer framework for enforcement, the question of whether insider trading is a feature or a flaw in prediction markets remains unanswered.