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Kalshi investigates suspicious bets on Trump's new White House press secretary

Prediction market Kalshi is investigating small, well-timed bets that correctly predicted Katie Zacharia would be named White House press secretary, the Wall Street Journal reported on 9 October.

3 outlets · 1L · 1C · 1R First reported Account updated

Updated (version 2). New coverage since the last version from Raw Story.

Image: CNA
Image: New York Post

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The story, neutrally told

Mixed · 2Kalshi, a prediction market platform, has opened an investigation into suspicious trades on the selection of Katie Zacharia as President Donald Trump's new White House press secretary, the Wall Street Journal reported on Friday 9 October, citing a Kalshi spokesperson. Left · 1Zacharia, a conservative media commentator who briefly worked at the Department of Homeland Security, had not been seen as a top contender; Kalshi gave her roughly a 1 percent chance in the days before the news, according to Raw Story's account of the Journal report. Right · 1The New York Post, summarising the Journal, said the wagers accurately predicted that the conservative commentator would get the role and that at least three small, precisely timed bets were placed shortly before news outlets began reporting the appointment.

Right · 1According to the Post's account of the Journal's review of publicly available Kalshi data, one $19 bet was placed around 10:43 p.m. Thursday and stood to win $1,896. Right · 1Two more bets, of $74 and $80, were reportedly placed around 1:41 p.m. Friday and stood to win $7,712 in total. Left · 1Raw Story, also relaying the Journal, put the two later bets' payouts at $3,689 and $4,023, which sum to the $7,712 the Post reported.

Left · 1News outlets began reporting the pick around 2 p.m. Friday, and Trump confirmed it on Truth Social, writing: "I am confident that Katie will deliver strong results for our Country." Right · 1A Kalshi spokeswoman declined to discuss the bets with the Post, saying, "We can't comment on ongoing investigations." The Post said it had also sought comment from the White House. Left · 1The Journal's reporting does not say who placed the trades or whether they had inside knowledge; Kalshi's trades are anonymous to the public, though the company keeps records of who traders are. The White House did not respond to Raw Story's request for comment.

Right · 1The Post placed the case against a background of other questionable trading on prediction markets. It cited a US special forces soldier charged in the spring with using classified information about the mission to capture Venezuelan President Nicolas Maduro to win more than $400,000 on Polymarket. Right · 1It also noted a reported probe by the Commodity Futures Trading Commission into unusual Kalshi trading, after billions of dollars of near-identical crypto trades raised questions about possible "wash trading", and said Kalshi and rival Polymarket face heavy litigation from state authorities. Left · 1Raw Story linked the episode to earlier cases: Trump's teleprompter operator, Gabriel Perez, was fired after winning over $100,000 on bets about the president's speeches and settled with the CFTC in August, and the White House told staff in a memo not to profit from nonpublic information after a string of well-timed Iran war bets.

Every sentence links to the reporting it rests on. The pill in front of each says where its sources sit: Left, Centre or Right when one side supplies at least half of them, Mixed when they are evenly split. The number is how many outlets it cites.

Left1 outlet

Framing
Raw Story leads on the long-shot nature of the pick and the question of 'who knew in advance', tying it to earlier White House betting episodes.
Emphasis
Zacharia's roughly 1 percent odds, the bet timings and payouts, the Perez teleprompter case and the White House memo on nonpublic information.
Leaves out or plays down
Does not mention the CFTC probe into possible wash trading on Kalshi or state litigation against prediction markets.
Charged language
“strangely well-timed wagers”
For example
“The prediction market Kalshi is examining some strangely well-timed wagers that anticipated President Donald Trump's selection of Katie Zacharia” — Raw Story
“Prediction markets, a fast-growing and controversial form of gambling platform” — Raw Story

Centre1 outlet

Framing
CNA runs a brief wire-style item relaying the Journal's report that Kalshi has launched an investigation.
Emphasis
The fact of the investigation and its source, a Kalshi spokesperson.
Leaves out or plays down
Gives none of the bet sizes, timings or wider context of other prediction-market cases.
Charged language
“suspicious trades”
For example
“Prediction market Kalshi has launched an investigation into a series of suspicious trades on their platform” — CNA

Right1 outlet

Framing
The New York Post calls them 'shady bets' and sets them among a run of prediction-market scandals and legal troubles.
Emphasis
Bet amounts and timing, Kalshi's no-comment, and the Maduro and CFTC cases.
Leaves out or plays down
Does not give Zacharia's pre-announcement odds, or say the Journal does not identify the bettors.
Charged language
“shady bets”“mountain of litigation”
For example
“Kalshi is probing a series of shady bets about the new White House press secretary” — New York Post
“which are facing a mountain of litigation from state authorities” — New York Post