Original Title: And The Winner Is… Kalshi? Prediction Markets Soar On Oscars
Original Author: Jason Brett, Forbes
Original Translator: Saoires, Foresight News

Reality show "Shark Tank" star Kevin O'Leary, known as "Mr. Wonderful," appears on the red carpet of the 98th Academy Awards at the Dolby Theatre in Los Angeles. The investor later publicly stated that he personally bet $1000 on the Kalshi platform, wagering on Timothée Chalamet to win the Oscar for Best Actor. (Image source: Getty Images)
On the evening of March 15, local time in the United States, the 98th Academy Awards were held at the Dolby Theatre in Los Angeles. Meanwhile, one platform has been stealing the spotlight - it is Kalshi.
While Conan O'Brien hosted the award ceremony live on ABC and Hulu, traders on Kalshi and Polymarket had already invested over $120 million in Oscar-related event contracts. This marks the largest betting frenzy ever seen in regulated prediction markets during award season. What drove all this was the groundbreaking guidance and regulatory rules released by the Commodity Futures Trading Commission (CFTC) just three days prior.
The trading volume on Kalshi alone has already surpassed $58 million and continues to rise in real-time throughout the ceremony; Polymarket contributed the remaining volume, bringing the total beyond $120 million. This figure is approximately 6 to 7 times the entire trading volume of Kalshi during the last award season, representing a tremendous leap compared to 2025.
Kalshi's PR director Elisabeth Diana told me in an email: "The Oscars are so popular in the trading market because they are the ultimate test of 'collective intelligence.'
Many celebrities also participated personally. On the Oscars red carpet that night, reality show "Shark Tank" star Kevin O'Leary - who also starred in Timothée Chalamet's "The King" (also known as "The Last Duel") - publicly announced that he personally bet $1000 on Kalshi, wagering on Timothée Chalamet to win Best Actor. This action was entirely spontaneous, with no commercial cooperation, paid promotion, or prior arrangements.
The flow of funds on the Kalshi platform clearly shows the concentrated money on the following awards:
· Best Actor: About $25 million (the most competitive award, also the one Kevin O'Leary bet on);
· Best Picture: About $24 million (the market is more optimistic about "1917");
· Best Director: About $7 million;
· Best Supporting Actor, Best Supporting Actress: Each about $5 million.
This demonstration of collective intelligence unfolded spectacularly that night, even integrating into the award ceremony itself.
Host Conan O'Brien jokingly referenced artificial intelligence and Timothée Chalamet's controversial statements regarding ballet and opera in his opening monologue. This incident once shifted the odds for Best Actor on Kalshi until traders remembered the Oscar voting had already closed and the market corrected itself.
Similar real-time price fluctuations played out in each category of awards, turning what was originally a passive audience into active players participating in real-time from a market perspective.
The timing of this explosion is nothing short of perfect. The CFTC's staff guidance and proposed rules announcement on March 12 provided a clear federal regulatory path for properly registered platforms like Kalshi. Traders finally gained the long-awaited regulatory certainty and responded with record trading volume.
Kalshi's connection with Rotten Tomatoes and its user-friendly mobile app made it unprecedentedly easy for the general public to participate. The result is: Oscar night is no longer just about the red carpet and acceptance speeches; it has transformed into a regulated, data-driven event, merging collective intelligence with Hollywood allure.
As the final awards were revealed one by one, each envelope opening impacted market trends in real-time. Whether "1917" swept the major awards or an upset occurred, one thing has become very clear:
The real winner of the 2026 Oscars is the compliance prediction market experiencing explosive growth.
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