A Soldier and a Google Employee Faced Federal Charges for Prediction Market Insider Trading. The White House Teleprompter Operator Got a Settlement Offer and Kept His Job.
In November 2025, the Department of Justice charged Army Special Forces soldier Gannon Ken Van Dyke with wire fraud after he allegedly made $400,000.
Van Dyke was charged with betting on Kalshi and Polymarket markets tied to the removal of Venezuelan President Nicolás Maduro, using classified intelligence he had access to through his military assignment. Van Dyke pleaded not guilty. The DOJ described the case as the first criminal insider trading prosecution involving prediction markets.
In January 2026, the DOJ charged Google software engineer Michele Spagnuolo with wire fraud after she allegedly used internal company search trend data to make approximately $1 million on Kalshi contracts tied to whether specific terms would trend on Google Search. Spagnuolo pleaded not guilty.
Both cases were prosecuted criminally. and both drew CFTC referrals. Currently, both defendants remain under federal indictment.
Gabriel Perez, President Trump’s longtime teleprompter operator, allegedly made more than $100,000 betting on Kalshi’s Mentions market using advance knowledge of the contents of Trump’s speeches, including the State of the Union address in February. Investigators say he placed bets on more than a dozen speeches over a three-month period. In at least some instances, he reportedly canceled bets mid-speech when Trump deviated from the teleprompter, suggesting a level of real-time market management that goes beyond a single opportunistic trade. The CFTC learned of the activity after Kalshi flagged the suspicious trading to its regulator. Perez sat for an interview with investigators and acknowledged some of the trades.
The DOJ declined to open a criminal investigation, and the CFTC is offering a civil settlement. Perez continues to operate Trump’s teleprompter. The variance of punishment for three insider trading cases on prediction markets certainly raises some questions.
The Enforcement Framework Around Each Insider Trading Case
The gap between those three outcomes is worth examining against the public statements regulators have made about prediction market insider trading.
CFTC enforcement director David Miller said in early 2026 that insider trading on prediction markets was the agency’s top priority, that the myth it is permissible is wrong, and that the agency would pursue it vigorously. Those statements accompanied the Van Dyke and Spagnuolo criminal referrals and appeared to signal a consistent, zero-tolerance posture toward market manipulation, regardless of who committed it.
The cases share a structural similarity. Each defendant had access to non-public information through their professional role. Each used that information to trade on Kalshi contracts that other market participants were pricing without that same information advantage. And each made a significant amount of money doing so. The CFTC’s own stated definition of the problem, using information obtained by virtue of your job to trade on markets that other participants cannot access on equal terms, applies to all three cases with equal force.
The legal distinction the DOJ appears to have drawn is the misappropriation theory: criminal wire fraud charges in the Van Dyke and Spagnuolo cases presumably rest on the argument that each defendant misappropriated information they had a legal duty to protect. Van Dyke misappropriated classified military intelligence, and Spagnuolo misappropriated proprietary Google data. The question the Perez case raises is whether a White House staffer who bets on the contents of a presidential speech using advance knowledge obtained through his government role is misappropriating information he had a duty to protect.
The White House issued an internal memo in March warning staff against using nonpublic information to place bets on prediction markets, shortly after investigators identified Perez’s trading. That memo suggests the administration itself recognized the conduct was problematic. Whether it crosses the legal threshold for criminal misappropriation is a genuine legal question. That the DOJ chose not to find out, while Perez remains employed, is a simple factual observation.
The Perez Case Takes a Step Beyond Insider Trading
The Mentions market Perez traded on is designed to price the probability that specific words or phrases will appear in a public speech. Its entire premise is that participants have equal access to public information about what a speaker might say, and that the market aggregates those views into a probability.
Perez had access to the teleprompter text before the speech. That is clearly not public information. Other market participants were pricing probabilities based on Trump’s past speeches, his known rhetorical habits, and any current available context. Perez was pricing based on the actual script of the prepared speech, with last-minute edits from Trump himself.
The mid-speech cancellation behavior makes the case more analytically distinctive than a simple insider trade case. Backing out of a position mid-event because you have real-time knowledge the market does not have is not a one-time opportunistic bet. It describes the active, dynamic exploitation of an information advantage that is continuously updated throughout each speech. A trader who can cancel bets in real time based on live teleprompter data is not merely trading on inside information. He is functioning as a human real-time data feed connected to a derivative market.
That behavior describes something the Kalshi Mentions market was not designed to accommodate and cannot defend against without structural changes. It is also behavior that, if replicated by others with access to advanced speech text, congressional testimony, or any other scheduled government communication, would systematically undermine every Mentions-style market any platform offers.
Kalshi’s Flagging System is Working, But Punishments Are Inconsistent
The CFTC, under Chairman Brian Quintenz-era leadership, and now under Chairman Selig, has been the prediction markets’ most important institutional protector. The agency has sued states that tried to restrict the platforms, approved Kalshi’s Bitcoin perpetual contracts overnight, and publicly characterized state enforcement efforts as attempts to nullify federal law. Kalshi’s legal team includes former acting Solicitor General Neal Katyal. Donald Trump Jr. has documented financial relationships with both major platforms.
Against that backdrop, the decision by the DOJ to decline criminal investigation of a Trump administration staffer for conduct that produced criminal charges against a soldier and a Google employee will draw scrutiny regardless of whether the legal distinctions are ultimately valid. The CFTC is simultaneously the agency that champions prediction markets against state regulators and the agency that chose a civil settlement for conduct it has, in other contexts, described as requiring vigorous criminal prosecution.
The Van Dyke and Spagnuolo cases established that insider trading in prediction markets can result in federal charges. The Perez case established that proximity to the administration that controls the CFTC and the DOJ produces a different outcome. Whether that difference reflects genuine legal distinctions about the misappropriation theory, the strength of the evidence, or something less principled is a question the settlement terms, when they become public, may help answer.
Kalshi’s surveillance system caught all three cases, which is a good thing. The platform flagged Perez’s trading, cooperated with investigators, and is implementing new employment verification requirements that we covered earlier this year. The platform’s behavior has been consistent. Unfortunately, it appears the enforcement response has not.
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