Gabriel Perez, a teleprompter operator for President Donald Trump, has been ordered to pay $172,000 after using material, nonpublic information from his job to place trades on the prediction market platform Kalshi, according to the Commodity Futures Trading Commission (CFTC) [1]. The CFTC stated that Perez made $107,539.02 in profits from these trades and was also assessed a civil penalty of $65,000 [1]. In addition to the financial penalties, Perez has been banned from trading on prediction markets for three years [1].
The trades in question involved 'presidential mention market contracts,' which are event contracts reflecting words or phrases the President may use during his speeches [1]. The CFTC described the case as insider trading and noted that Kalshi, the platform used by Perez, assisted in the investigation [1]. Bobby DeNault, Kalshi’s lead lawyer, emphasized the seriousness of the violation, stating, 'It doesn’t matter who you are: violate our rules or federal law and you will face the consequences' [1].
The CFTC also highlighted Perez’s 'exemplary cooperation' during the investigation when announcing the penalties [1]. The incident drew condemnation from then-White House press secretary Karoline Leavitt in July, who called the trades a breach of ethics and 'deeply unfortunate and frankly a disgrace' [1]. Perez was placed on leave in July, and Leavitt stated that 'this individual will no longer be here' [1].
Market implications include increased scrutiny on prediction markets and the enforcement of insider trading regulations in non-traditional financial venues. The case underscores the regulatory reach of the CFTC and the compliance measures undertaken by platforms like Kalshi [1].
CONCLUSION
The CFTC's enforcement action against Gabriel Perez highlights the risks and consequences of insider trading in prediction markets. The penalties and trading ban serve as a warning to market participants about the importance of compliance with federal law and exchange rules. The incident may prompt further regulatory attention to prediction markets and their oversight.