How Did He Bet on Trump’s Speeches?
Gabriel Perez had access to presidential speeches before they were delivered because of his role as a White House teleprompter operator.
According to the CFTC, he used that access to trade on Kalshi, a prediction-market platform, between December 2025 and February 2026. The contracts involved whether specific words or phrases would appear in presidential speeches.
These so-called “mention markets” allow traders to take positions based on whether a particular word or phrase will be spoken.
Because Perez had access to the prepared material before the public heard the speeches, he had information that ordinary market participants did not have.
The CFTC found that the trades generated $107,539.02 in profits.
CFTC Says Non-Public Information Was Misused
The CFTC said Perez had access to presidential speeches before they were publicly delivered and misappropriated that information for his personal financial benefit.
The agency described the conduct as a breach of his duty of trust and confidence, rather than simply ordinary prediction-market betting.
The case therefore highlights a growing regulatory concern: prediction markets can create opportunities for people with privileged access to information to gain an advantage over ordinary traders.
$172,539 in Total Payments
Under the settlement, Perez is required to make two major payments:
$107,539.02 — repayment of trading profits
$65,000 — civil penalty
Three years — trading ban
The CFTC said the civil penalty was substantially reduced because Perez provided what the agency described as “exemplary cooperation” during the investigation.
He also agreed to cease and desist from further violations of the Commodity Exchange Act and CFTC regulations.
How Did Kalshi Detect the Trading?
Kalshi’s surveillance systems detected trading activity that did not match typical buying and selling patterns.
The company investigated Perez’s account and froze it, locking more than $90,000 in profits he had made on the platform, according to a Kalshi spokesperson cited by CBS.
After completing its investigation, Kalshi referred the matter to the CFTC.
The case demonstrates how prediction-market platforms are increasingly relying on automated monitoring systems to identify unusual trading behaviour.
Perez’s Role at the White House
Perez had worked with Trump for several years and held positions including technical adviser and teleprompter operator during the president’s first and second terms.
Government staff records show that he began working as a technical adviser for the White House Office in January 2025 before performing teleprompter-related duties.
His access to presidential speeches was central to the CFTC’s case because it allowed him to see material before it was publicly delivered.
After the betting activity came to light, Perez was placed on unpaid leave. He is no longer employed by the federal government, although officials have not clearly stated whether he resigned or was dismissed.
White House Reaction
The White House had previously condemned Perez’s conduct after reports about the betting emerged.
Press Secretary Karoline Leavitt described the situation as “unfortunate” and “a disgrace,” according to reports.
The White House also moved to reinforce guidance for staff regarding the use of non-public information in prediction markets.
The episode has highlighted the difficulty of separating personal trading from official responsibilities when employees have access to sensitive government information.
Growing Attention on Prediction Markets
Platforms such as Kalshi allow users to trade contracts linked to real-world events, including politics, sports, economics and public events.
The popularity of prediction markets has grown significantly, but the sector is also attracting greater regulatory scrutiny.
The Perez case is particularly notable because the information involved was not a general political forecast. He allegedly had direct access to the actual prepared material that would determine the outcome of the contracts.
Why “Mention Markets” Matter
A speech may contain hundreds or thousands of words, but prediction markets can place financial value on whether one specific word or phrase will be spoken.
For an ordinary trader, determining that outcome may involve analysing public information.
For someone who has already seen the prepared speech, however, the uncertainty can be dramatically reduced.
That difference is at the heart of the CFTC’s enforcement action.
Ethical Responsibilities of Government Employees
Government employees who have access to confidential or non-public information are expected to protect that information and avoid using it for personal financial gain.
The Perez case illustrates why those responsibilities are particularly important when employees have access to information that can immediately affect a financial market.
Using privileged information could give one trader an advantage that other participants have no reasonable way of obtaining.
Why the Case Matters
The case is significant beyond the individual penalty.
It demonstrates that even a single word in a presidential speech can become financially valuable when prediction markets create contracts around it.
It also raises questions about how prediction-market platforms should identify users with privileged access to information and how government employees should be restricted from trading on events connected to their official duties.
What Could Happen Next?
The case could contribute to stronger restrictions on government employees participating in prediction markets.
Trading platforms may also increase scrutiny of users’ employment information, unusual trading patterns and transactions involving events where a trader could possess privileged information.
Kalshi’s detection of Perez’s activity and subsequent referral to the CFTC also shows how exchanges and regulators can work together to identify potential misconduct.
Conclusion
Former White House teleprompter operator Gabriel Perez was found to have used advance access to Donald Trump’s speeches to trade on Kalshi’s prediction markets and earn $107,539.02 in profits. Under a CFTC settlement, he must repay those profits, pay a $65,000 civil penalty and comply with a three-year trading ban. The total financial penalty comes to $172,539.02.
The case highlights the growing intersection between government information, personal trading and prediction markets. It also reinforces the need for strong ethical rules and surveillance systems when individuals with access to non-public information participate in markets where that information can have direct financial value.
