Ex-White House teleprompter operator ordered to pay $172,000 for Trump speech bets

A former White House teleprompter operator has been ordered to pay more than $172,000 for using insider information to bet on what President Donald Trump would say in his speeches. The Commodity Futures Trading Commission (CFTC) announced Friday that Gabriel Perez must forfeit $107,539.02 in profits and pay an additional $65,000 civil penalty. Perez, who worked at the White House between December 2025 and February 2026, placed trades on the prediction market platform Kalshi, where users bet on real-world events.

The CFTC found that Perez "misappropriated" his access to advance knowledge of Trump’s speech content to place bets in violation of his duty of trust and confidentiality. His penalty was reduced due to full cooperation with the investigation. He has also been banned from trading on prediction markets for three years.

Kalshi, a regulated U.S.-based prediction market platform, reported Perez’s unusual betting activity in March. Analysts noticed a pattern of bets on "mention markets," which are contracts predicting whether a speaker will use specific words, phrases, or countries. Kalshi traced the account to a federal employee responsible for operating White House teleprompters and reported the activity to the CFTC.

The company stated that political leaders’ words can significantly impact financial markets, including currency exchange rates, oil futures, and stock prices. In July, the White House Management Office sent a memo to staff warning against placing bets on prediction markets.

At the time, then-White House press secretary Karoline Leavitt confirmed that Perez was on unpaid leave and would not return to his position. The White House has not yet issued a new statement following the CFTC’s decision.

Kalshi’s lead lawyer, Bobby DeNault, praised the ruling on social media platform X, emphasizing accountability for rule violations. The case highlights regulatory scrutiny of insider trading in prediction markets, particularly when involving government employees.

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