This week, two U.S.-regulated, dollar-denominated prediction markets began accepting bets on the presidential race, with just a month left until Election Day. Kalshi, a platform that fought a lengthy legal battle with the Commodity Futures Trading Commission (CFTC) to offer election contracts in the U.S., launched its presidential markets on Friday. A day earlier, Wall Street’s Interactive Brokers (IAB) introduced its ForecastEx platform for the same purpose.
So far, trading volumes at both CFTC-supervised exchanges remain modest, with $344,101 worth of contracts traded on Kalshi and $346,000 on ForecastEx. In comparison, the crypto-powered Polymarket, which has banned U.S. users under a CFTC settlement, has recorded over $1.2 billion in bets on the Kamala Harris vs. Donald Trump race. Polymarket’s record volumes continue to grow, even though Kalshi and IAB had to wait for legal clarity before launching.
Koleman Strumpf, an economics professor at Wake Forest University, believes it’s possible for Kalshi and IAB to gain traction, though catching up to Polymarket will be challenging. Some traders, he noted, may switch from Polymarket to these regulated platforms. Additionally, “more than half of all trades will happen between now and Election Day,” which historically drives higher trading volumes.
Polymarket’s Competitive Advantages
Despite the launch of Kalshi and ForecastEx, Polymarket maintains several key advantages. Aaron Brogan, managing attorney at Brogan Law, points out that Polymarket’s global accessibility and lack of strict position limits make it more appealing to users. While Kalshi restricts access to “foreign nationals” and other excluded groups, Polymarket has no such limitations. Additionally, Kalshi imposes explicit position limits, which could potentially restrict the total market size, though the current limits are quite high.
On Friday afternoon in New York, Kalshi’s odds showed Kamala Harris with a 51% chance of winning, while Trump stood at 50%. ForecastEx reflected a wider margin, with Harris leading Trump 53-47. Meanwhile, Polymarket had the two candidates in a dead heat at 49% each.
Harry Crane, a statistics professor at Rutgers University, cautions against overanalyzing these differences, as they fall within the typical margin of error seen in election forecasting. He also notes that markets may have a “margin of inefficiency,” meaning the potential profits from arbitraging price differences may not justify the effort. However, over time, prediction markets can still provide valuable data for forecasting elections, with some markets potentially proving to be more predictive than others.
Fariha Karim