Trading the prediction markets
Prediction markets have finally gone mainstream. Some estimates show total market liquidity exceeding $60B in 2026. While they are nothing new – the Hollywood Stock Exchange opened 30 years ago – they are now readily available and easy to use as built-in features of popular apps like Coinbase. But they carry significant risks from a user perspective, even putting aside the question of whether we should be betting on certain events. And regulators have taken notice.
The market is shaped by US regulation
The market is growing rapidly in 2026. In addition to Kalshi and Polymarket, adjacent platforms such as FanDuel, Coinbase, Robinhood, and Fanatics are entering the field. In the US, regulation has shaped the competitive landscape, with Kalshi operating as a CFTC-regulated exchange, unlike the other markets.
Regulation in the US has been driven by gambling restrictions and historical distinctions between different forms of betting, with respect to elections, sports, and other events.
Last week, on March 16th, the Arizona state Attorney General filed criminal charges against Kalshi for violating statutes prohibiting gambling. The charges quickly turned political as the head of the CFTC came to Kalshi’s defense and criticized the decision to bring a criminal case as “entirely inappropriate.”
Insider trading and other compliance risks
Prediction markets intuitively raise risks related to insider information. Participants are arguably much more likely to bet on an event where they have more information about the potential outcome. And this simple fact has been cited as a problematic incentive driving insiders to platforms such as Polymarket, which offers 113 markets (for individual predictions) related to stocks as of the date of this post.
The popularity of the major platforms has increased in the past few months, no doubt with Super Bowl LX and major geopolitical changes spurring betting interest. The US Senate has noticed. On Monday, March 23rd, a bipartisan group of senators introduced the “Prediction Markets Are Gambling Act,” which would amend the Commodity Exchange Act to ban sports betting on registered platforms (so Kalshi, due to its decision to register with the CFTC, would be impacted, whereas the unregistered Polymarket would likely not be affected).
Kalshi and Polymarket both quickly moved to document their own policies against insider trading by adopting “Market Integrity” rules. Kalshi goes into detail about screening new users for special trading restrictions based on their profiles. The company also states that its internal compliance team monitors trades and has hired a vendor to conduct additional trade surveillance.
If insiders do bet on events related to stocks (such as earnings or closing prices) on these platforms, their wagers are only part of the total mix of activity that yields odds and creates a prediction market, as with insider activity in the stock market itself. The aggregated prediction market data – the odds and volumes for specific bets - is publicly available on the platform sites, including via API. So arguably the insider risks in these platforms are quite different with respect to (a) the users (who may or may not be trading against insiders) and (b) data users (who factor prediction market data into separate investment decisions).
Interestingly, some firms are blurring the line between (a) and (b) by setting up their own prediction market trading desks. Liquidity is a primary constraint on these businesses, and it may materially limit them if the US regulatory environment tightens.
Settlement risk
Many users have unfortunately already encountered the complexities involved in resolving a bet on a prediction market. Events that seem straightforward (“Did a specific celebrity attend the Super Bowl?”) may in fact be difficult to determine. Others, such as an Iran ceasefire (currently trading at 49% “yes” by April 30, 2026), are clearly more complex. The platforms need to enforce dense contracts and rely on sometimes limited public information, while making quick payments and collections to keep users engaged, often in real-time. As the markets expand to cover new types of events and information sources multiply, settlement risk increases.
API vs. web scraped data
The platforms now offer APIs in addition to sharing much of their data on public sites that do not require an account. Presumably sophisticated users and institutions will rely on these APIs rather than scrape the market data; however, institutional accounts are subject to closer scrutiny, documentation, and more extensive terms and conditions. Kalshi, for example, has a clear prohibition on training AI models on its data.
The use of prediction market data as a foundation for reporting news
Finally, prediction market data is impacting news reporting. The data on outcomes of political events and major sport events is a clear draw for journalists. Glacier is also aware of anecdotal evidence that traders are using swings in prediction market data to monitor the news. Dow Jones announced an exclusive deal with Polymarket in January 2026 to distribute data such as prediction markets for company earnings.
Whether this data has staying power remains to be seen.
Don D'Amico
Founder & CEO, Glacier Network
Further reading
· Arizona AG Criminal Case Against Kalshi (filed 3/16/26)
· Polymarket Market Integrity rules
· Kalshi Market Integrity rules
· Kalshi FAQ for Finance Professionals
· Prediction Markets Are Gambling Act (proposed 3/23/26)
©2026 Glacier Network LLC d/b/a Glacier Risk (“Glacier”). This post has been prepared by Glacier for informational purposes and is not legal, tax, or investment advice. This post is not intended to create, and receipt of it does not constitute, a lawyer-client relationship. This post was written by Don D’Amico without the use of generative AI tools. Don is the Founder & CEO of Glacier, a data risk company providing services to users of external and alternative data. Visit www.glaciernetwork.co to learn more.