Kalshi, a U.S.-based prediction marketplace, has expanded its offerings with new political betting markets following the recent presidential election. The platform now allows users to bet on various outcomes related to President-elect Donald Trump’s administration, including the likelihood of an impeachment, as detailed in regulatory filings with the Commodity Futures Trading Commission (CFTC).
Political prediction markets saw a significant surge in betting interest leading up to the U.S. election on November 5, with total betting volumes reaching nearly $4 billion. Although the majority of wagers were placed on Web3-native Polymarket, Kalshi’s recently launched political event contracts also drew considerable attention, accumulating over $250 million in trading volume by election day.
Kalshi’s rise in popularity follows a pivotal legal victory over the CFTC, which challenged Kalshi’s ability to list political event contracts. The court’s decision marked the first time a prediction market platform could legally offer election contracts in the U.S., potentially paving the way for competitors to enter the market.
In addition to U.S. political bets, Kalshi has expanded its offerings to include contracts on international elections, such as upcoming races in Canada and Ireland. On October 28, Kalshi introduced USD Coin (USDC) deposits, catering to crypto-focused users and further strengthening its appeal within the Web3 community.
Trump’s victory odds on Kalshi stood at 58% as election day unfolded, a reflection of betting sentiment that leaned in favor of his win. Other platforms, including Robinhood and Interactive Brokers, also launched political betting markets for select users in October, joining Kalshi in tapping into the growing demand for real-time political wagering.
The CFTC remains wary of political prediction markets, suggesting they may impact the integrity of the democratic process. However, some industry analysts argue that these markets can capture voter sentiment with more accuracy than traditional polling, as they reflect real-time, financially-backed predictions.
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