A former White House teleprompter operator has been ordered to pay $172,539 after federal authorities found that he used advance access to President Donald Trump’s speeches to place bets on what the president would say.
Gabriel Perez, who worked as a White House technical adviser and teleprompter operator, used the prediction-market platform Kalshi to trade contracts tied to words and phrases expected to appear in Trump’s speeches.
The trades took place between December 2025 and February 2026, according to the Commodity Futures Trading Commission (CFTC).
The case is unusual because Perez was not simply betting on a political event from the outside. According to the CFTC, his White House position gave him access to information about presidential speeches before they were delivered.
How did the White House staffer make money betting on Trump?
The key to the case was something known as a “mention market.”
Instead of predicting who would win an election or whether a major political event would happen, these contracts allow traders to bet on whether a particular person will mention a specific word or phrase.
For example, a contract could be based on whether a president uses a particular country, policy term or campaign phrase during a speech.
Perez traded these types of contracts involving Trump’s speeches, according to the CFTC.
Because his job involved operating the presidential teleprompter, authorities said he had advance access to the president’s remarks.
That created the central problem identified by regulators: the information available to him was not equally available to ordinary traders.
The CFTC said Perez “misappropriated” his prior knowledge of Trump’s speeches in breach of his duty of trust and confidence.
The amount he made was more than $107,000
According to the federal settlement, Perez made $107,539.02 in profits from the trades.
He has been ordered to surrender those profits in full.
On top of that, he must pay a $65,000 civil penalty.
That brings the total financial obligation to:
$107,539.02 in profits + $65,000 penalty = $172,539.02
Perez has also agreed to a three-year ban from trading.
The CFTC said the civil penalty was reduced because of his “exemplary cooperation” with the investigation.
How was Perez caught?
The unusual trading activity was first detected by Kalshi.
The prediction-market company said its surveillance systems noticed trading activity that did not fit typical buying and selling patterns.
Kalshi subsequently investigated the account and determined that the trader was a federal employee working with White House teleprompters.
The company froze the account, locking more than $90,000 in profits, according to information previously provided by a Kalshi spokesperson.
Kalshi then referred the matter to the CFTC.
That investigation ultimately resulted in the settlement announced Friday.
Why Trump’s speeches became a betting opportunity
The case highlights how prediction markets have expanded beyond traditional political forecasting.
A person does not necessarily have to predict a major election result to make money from a prediction market.
In a “mention market,” even a single word can become the subject of a contract.
That creates an obvious information advantage for someone who can see a speech before it is delivered.
For ordinary traders, the question might be:
Will Trump say this word?
For someone who has already seen the speech, however, the uncertainty can be dramatically different.
That is what made Perez’s position particularly significant to regulators.
White House staff had already been warned about prediction-market bets
The Perez case also comes after warnings to White House employees about using nonpublic information to trade on prediction markets.
In March, the White House Management Office sent a letter to aides warning them against placing bets on prediction markets using nonpublic information, according to administration officials cited by CBS News.
The warning came as prediction markets such as Kalshi and Polymarket attracted increasing attention in Washington and among traders.
The issue is particularly sensitive when government employees have access to information before it becomes public.
Perez is no longer working at the White House
Perez was previously placed on unpaid leave following the investigation.
A White House official said in July that he was no longer in his position, although the official did not specify whether he had been fired or resigned.
The White House has not immediately commented on the new settlement.
Records cited by CBS News show that Perez worked for the Trump administration during both the president’s first and second terms.
He began working as a technical adviser for the White House office in January 2025.
What the $172,000 penalty actually means
The headline figure of $172,539 can make the case sound like a single fine, but it is actually made up of two different amounts.
| Amount | What it represents |
|---|---|
| $107,539.02 | Profits Perez made from the trades |
| $65,000 | Civil penalty imposed by the CFTC |
| $172,539.02 | Total amount to be paid |
| 3 years | Trading ban |
So Perez is not simply being fined $172,539 for making the bets.
He is being required to give up the profits he made and pay an additional civil penalty.
Why the case matters beyond one White House employee
The case raises a broader question about prediction markets as they become more sophisticated.
These platforms are designed to allow people to trade contracts based on future events. But when a participant has confidential or advance information unavailable to the wider market, the advantage can become fundamentally different from ordinary forecasting.
That is why the CFTC’s action focuses not simply on the fact that Perez placed bets, but on where the information behind those bets came from.
Kalshi’s lead lawyer, Bobby DeNault, said the company welcomed the decision and emphasized that its rules and federal law apply regardless of who is involved.
For Perez, the outcome is clear: he must surrender his trading profits, pay the civil penalty and stay away from trading for three years.
But the bigger lesson from the case may be even simpler:
Knowing what the president is about to say can be valuable. Using that information to bet on it can be very costly.
