Precise sniping or insider trading? On the night before Maduro's arrest, a mysterious market prediction account made a frenzy of $400,000, prompting U.S. legislation

A prediction market trade centered around the fate of Venezuelan President Maduro is sparking an urgent crackdown in U.S. politics on a new frontier of “insider trading.” Reports indicate that a user invested approximately $32,500 on Polymarket, betting that Maduro would step down before January 31, and after the news of his arrest was made public, they made a profit of over $400,000, with a return rate exceeding 1,200%.

This move has raised significant “insider information” controversy because some trades occurred just hours before the official announcement. In response, U.S. Representative Ritchie Torres (D) is about to introduce the “2026 Financial Prediction Market Public Integrity Act,” aiming to prohibit federal officials from using non-public information obtained through their duties to trade in prediction markets, extending the principles of the Securities Exchange Act to this emerging field, which had a trading volume of over $44 billion in 2025.

A $400,000 “Accurate Prediction”: A Review of the Maduro Event Trading Full Picture

This geopolitical storm in early January 2026 not only caused waves in the real world but also staged a precision ambush akin to a financial espionage thriller within decentralized prediction markets. The entire event focused on a newly created Polymarket account at the end of December 2025. The account’s behavior was unusually clear and focused: it made only four predictions, all related to U.S. intervention in Venezuela, with the most significant bet being approximately $32,500 on “Maduro will step down before January 31.”

According to Axios, when the account purchased the relevant prediction contracts, each share was priced at about 7 cents, implying an implied success probability of only a single-digit percentage. For weeks, the market was dormant with low prices. However, a turning point occurred on the evening of January 2 (Friday). According to The Wall Street Journal, the price of the Maduro removal market began to quietly rise before 10 p.m. Eastern Time on Friday. A few hours later, on Saturday morning, President Trump officially announced that U.S. forces had successfully detained Maduro. With this explosive news confirmed, the prediction contract settled at nearly $1 per share.

Key Nodes in the Maduro Prediction Market Trade

Dormant Period (End of December 2025 - January 2, 2026):

• Account Behavior: Newly created account, focused on betting on U.S. intervention in Venezuela.
• Key Positioning: Bought “Maduro will step down before January 31” contract at about 7 cents per share, investing around $32,500.
• Market Sentiment: Implied probability was extremely low; trading was quiet.

Anomaly Period (January 2, Friday evening):

• Time: Before 10 p.m. Eastern Time.
• Market Signal: Contract prices started to break away from the bottom, showing a clear upward trend.
• Potential Information Source (Rumor): Some traders claimed on X platform that they observed a surge in Domino’s Pizza orders around the Pentagon (considered an informal indicator of military mobilization), prompting them to go long.

Confirmation and Settlement Period (January 3, Saturday morning):

• Official Announcement: President Trump officially announced Maduro’s arrest.
• Market Reaction: Relevant contracts surged to $1 and settled.
• Final Profit: The account gained over $400,000, with a total return exceeding 1,200%.

As a result, this mysterious account achieved over $400,000 in net profit in less than 24 hours, with a return rate surpassing 1,200%. This textbook-like “risk arbitrage,” due to its bold timing of position entry and the subtle timing of price movements slightly before the official announcement, quickly spread across social media and financial news circles, raising a core question: Did the trader have prior access to non-public insider information?

Legislators Act Urgently: Extending the “Securities Act” Principles to Prediction Markets

This “get-rich-quick myth” that has been hotly debated in the crypto community immediately touched a nerve among Washington regulators. Just hours after the event, Democratic Congressman Ritchie Torres leaked to the media that he would introduce legislation specifically targeting such risks.

According to Jake Sherman, founder of Punchbowl News, the proposed “2026 Financial Prediction Market Public Integrity Act” aims to close existing legal loopholes. In the U.S., insider trading involving publicly traded stocks is strictly regulated under the Securities Exchange Act, which prohibits members of Congress and federal officials from trading stocks based on non-public information obtained through their official duties. However, emerging prediction markets like Polymarket and Kalshi have not yet been explicitly covered by this regulatory framework.

Torres’ bill intends to extend the core spirit of the Securities Act to this new domain. It is expected to prohibit federal officials, political appointees, and administrative employees from trading prediction market contracts related to government policies or political outcomes when they possess or can reasonably access material non-public information through their roles. This means that insiders with privileged information about military actions, policy decisions, or economic data would be explicitly banned by law from betting on related events in prediction markets.

In response to this legislative initiative, prediction market platforms at the center of the controversy quickly reacted. Kalshi’s PR account responded to related reports, stating that according to their platform rules, insiders or decision-makers using material non-public information for trading is already prohibited. This suggests that the industry is aware of the issue and is attempting to establish self-regulation standards. However, Polymarket, the platform where this event occurred, has not yet responded to external inquiries as of press time. The dual movement of legislation and platform self-discipline indicates that, after demonstrating strong price discovery and market sentiment aggregation capabilities, prediction markets are inevitably entering the “compliance” deep waters.

The Achilles’ Heel of Prediction Markets: Efficiency, Controversy, and Political Entanglement

The storm triggered by the Maduro event is not the first time prediction markets have faced allegations of insider trading, but this time involving a national military operation elevates the issue to the level of national security and political integrity. This incident sharply reveals the inherent contradiction of prediction markets as an emerging financial/information tool: their efficiency partly stems from an insatiable appetite for all information, which can include illegal insider data.

The core appeal of prediction markets lies in their reputation as a “collective intelligence” mechanism, capable of more agile and accurate reflection of the probability of future events. This was evident during the 2024 U.S. presidential election, where data from prediction markets diverged significantly from traditional polls, attracting nationwide attention. The staggering $44 billion trading volume in 2025 further demonstrates their large user base and capital attraction. However, once this efficiency is combined with insider information, it corrupts the fairness of the market: insiders with privileged access can risk-free profit from the public, eroding trust and turning the market into a zero-sum or even negative-sum game.

This incident also unexpectedly involves U.S. political figures. Notably, Donald Trump’s eldest son, Donald Trump Jr., has close ties with major prediction platforms. Since January 2025, he has served as a strategic advisor to Kalshi, and after investing eight figures through his venture firm in August, he joined the advisory board of Polymarket. While these high-level connections may not be directly related to this specific trade, they add political drama and public suspicion to the event, making regulatory calls more urgent and necessary. It raises a deeper question: when the prediction market’s underlying assets are political outcomes, and the platforms are intertwined with political circles, how can their independence and fairness be ensured?

Future Impact: How Will Regulatory Implementation Shape the Prediction Market Landscape?

While Torres’ bill is still in the proposal stage, its symbolic significance and potential direction are clear. It marks the formal inclusion of prediction markets—especially those involving political and policy predictions—into the serious financial regulatory framework in the U.S. This trend will have profound industry implications.

First, the most immediate effect is the purification of the user base. If passed, the bill will directly exclude high-risk, information-advantaged users—namely federal officials and related personnel. Although this may temporarily impact liquidity in certain political contracts, in the long run, establishing a “firewall” to protect most participants’ fairness will help attract a broader range of ordinary traders relying on public information and independent analysis, promoting healthy market development.

Second, platforms will face stricter compliance requirements. Future prediction platforms may need to develop monitoring systems similar to traditional brokerages to identify and report suspicious trading patterns, especially abnormal price movements involving sensitive topics before major government announcements. Platforms might be required to cooperate with regulators to investigate potential insider trading. Kalshi’s existing rules suggest that leading platforms are already aware of this, but legislation will elevate such self-regulation to legally binding obligations.

Finally, this could drive evolution in product design. To avoid complex regulatory risks, platforms might focus more on sports, entertainment, or tech trend predictions, which are less sensitive politically. Alternatively, they may develop more complex products, such as index-based or bundled prediction products, to diversify risks and regulatory scrutiny related to individual political events. In any case, the era of nearly unrestricted betting on any geopolitical event—an era of wild growth—may soon come to an end. Regulatory intervention is both a challenge and a necessary rite of passage for prediction markets to move from the fringes to the mainstream, from gray areas to transparency.

What Are Prediction Markets? How Do They Work and Who Are the Main Platforms?

For readers unfamiliar with this field, “prediction markets” may still be a new concept. In short, prediction markets are platforms that allow users to “trade” on the outcomes of future events. They are essentially large, ongoing polls and probability assessments, but with real money as stakes, making them theoretically more reflective of collective beliefs than ordinary polls.

Core operation mechanism: The platform creates an event, such as “Will Maduro step down before January 31, 2026?” and generates two corresponding tokens or shares: “Yes” and “No.” Each share’s initial price is usually set at $0.50, representing a 50% probability. As users buy and sell, prices fluctuate dynamically. If you believe the event will happen, buy the “Yes” shares at the current price (e.g., $0.07); if the event occurs, each “Yes” share will be worth $1, giving you a profit of $0.93. Conversely, if you believe it will not happen, you can buy “No” shares or sell “Yes” shares. The market price ultimately converges to the collective estimated probability of the event.

Major platforms include:

1. Polymarket: A decentralized prediction market platform based on Polygon blockchain. Known for its wide range of topics (politics, finance, crypto, sports) and high liquidity. Users trade using stablecoins.
2. Kalshi: A regulated, centralized prediction market platform approved by the U.S. Commodity Futures Trading Commission (CFTC). It is the first to legally offer prediction markets related to U.S. political and economic events, giving it higher credibility in traditional finance.
3. Others: Such as Manifold Markets, which offer community-driven, customizable prediction markets.

Proponents see prediction markets as effective tools for aggregating information and revealing “hidden knowledge,” while critics worry about gambling, manipulation, and issues like insider trading exemplified by this incident.

Historical Cases — Prediction Markets Repeatedly Crossing the “Insider” Red Line

Using non-public information for profit in prediction markets is not unique to the Maduro event. Historically, similar controversies have accompanied the development of prediction markets, continually testing industry boundaries.

One of the most classic cases occurred during the 2020 U.S. presidential election. In Wisconsin, a key swing state, before official vote counts finished and media remained cautious, the “Biden wins Wisconsin” contract on PredictIt (another regulated prediction market) surged dramatically hours before the official announcement, approaching $1 (certainty). Many traders suspected insiders—such as early vote counters or media personnel with access to data streams—had manipulated the market. Although unconfirmed, this event sparked widespread discussion about insider information in political prediction markets.

Another domain involves mergers and acquisitions. Before official announcements, stock price movements of target companies often trigger insider trading investigations. Similarly, prediction markets have seen sudden activity and one-way price movements on contracts about whether a tech company will be acquired, before news is publicly released. While the underlying asset shifts from stocks to event contracts, the core issue of profiting from undisclosed material information remains the same.

These cases, like the Maduro incident, involve highly sensitive information with tightly controlled disclosure processes (national politics, military actions, corporate secrets). They repeatedly demonstrate that prediction markets, as an efficient information-processing system, have a voracious appetite for “information,” especially from non-public channels. As prediction markets grow in influence, conflicts with insider trading laws, national security regulations, and election laws will only intensify. This legislative proposal can be seen as a necessary regulatory response to this long-standing tension, aiming to draw a clear red line in this ambiguous territory.