Could Kalshi become a new tool for political analysts?

Part of that success has been sports contracts - which many local regulators believe are sports betting, even if the platforms are regulated as financial trading federally by the American Commodity Futures Trading Commission. However, another part of their rise has been their market positioning. The platforms posit themselves as a quantified modern day way of using the ancient wisdom of the crowds, and Kalshi's partnerships with news orgs like CNBC and CNN have served to somewhat cement that idea in the mainstream. But how accurate are they really?

Kalshi is a prediction market. While they were not the first to run with the concept - the idea has been around since at least the early 2000s - they were the first to get a CFTC license and start general retail trading.

The model goes as follows:

This model means that there is no "house" that is incentivized to win against the traders, and the buying/selling element moves it closer to stock trading than existing betting models.

While markets initially focused on economic, geopolitical and cultural events - Kalshi focuses mostly on sports. This has proved among the most controversial of its moves, and has been challenged by local gambling regulators across the US.

The core idea behind prediction markets as a tool for economic, political and other analysts is that people are more honest when they have money down on the outcome. In essence, they are the modern day "wisdom of the crowd" quantified into a nice, neat number.

One example Kalshi has used is that it correctly predicted the election of President Trump in 2024, despite initial polling suggesting a tight race that could go either way. The argument is that Trump voters were less willing, for whatever reasons, to speak to or be honest with traditional political pollsters - while the money down on the markets spoke for itself.

Another is that similar models are actually used by insurance traders, a sector that has accurately predicting future events at the core of its own business model. Interestingly, this has caused problems in some states that have attempted to make legal moves against prediction markets.

You might also see a big glaring hole in the operation here. While trading on inclement weather or an NFL coin toss is something no person can influence to a precise degree, election markets or very personal markets (like whether or not someone might say a particular word during a speech for example) are very much influenceable by people. And when the outcome is up to people, some of them will have inside information that others don't.

Kalshi is now all over the broadcast media world, offering its markets' opinions as information for people interested in the likelihood of an event occurring. That positioning, as well as sports contracts, helped it trade many billions of dollars a month. During the World Cup Kalshi traded more than $40 billion, with $9 billion traded across July alone.

This can be seen as smart positioning from Kalshi. It has managed to somewhat legitimize itself through its use as a political and financial tool in the media, while also capturing the sports betting and gambling market.

Kalshi says that, on average, its markets line up with results. For example, a 60% contract on a Yes event will actually happen 60% of the time. However research has found that low-priced contracts (under 10%) suffer from longshot bias - which means they are priced higher than they might be because traders find the potential longshot winnings worth the risk. These events are usually right less often than the implied odds suggest.

For example, imagine putting down money on a politician to win. An individual could, if they had the money and were so inclined, spend lots of money to support the campaign of that politician - making it more likely they will win.

Is that money on the market now telling the "truth" - or the version of the truth the market wants to believe?

Because prediction markets are swayed by big money, the argument goes, traders with lots of liquidity in the market can have an outsized influence on the market price.

There are also all the concerns mooted above about insider trading. Something Kalshi says it does not allow and has been hot on stopping. However, critics argue that insider trading is impossible to stamp out from the model and may actually be a core feature behind the claims of accuracy.

However, the biggest potential problem for prediction markets is their sports contracts. Many countries are currently taking legal challenges against prediction market models, claiming they violate local sports betting laws. Although operators are supported by the CFTC, and generally backed by the President Trump Administration, these legal battles will shape prediction markets' futures as legitimate political analysis tools