The dominant narrative around prediction markets still centers on elections and sports. Sports account for the majority of volume at major venues, and election contracts are what put the category on the front page. But based on what active traders are actually doing with real money, prediction markets are expanding for an even more impactful purpose: they’re a place to hedge risks that no existing financial instrument can price cleanly because the assets are new in nature. Their applicability spans geopolitical events, policy shifts, combined with commodity-linked outcomes, and this market has the potential to dwarf anything sports will ever produce.

Case in point: when Kevin Warsh was nominated as the next Federal Reserve chair in January, trading activity on Kalshi and Polymarket surged, and among frequent, multi-market traders, the volume spike dwarfed that of the Super Bowl. More recently, the 24-hour window around the Iran conflict produced more trading activity than any single sports day this year. Sports still account for the majority of the overall volume on both venues. But the traders driving the growth edge are building strategies across categories and venues. These traders are increasingly clustering around geopolitical, macro and policy-linked contracts. They are not looking for entertainment. They are looking for tools to price uncertainty that affects their other positions, their businesses, and (in some economies) their household budgets.

Serious institutional voices are now articulating that shift. In a February 2026 paper, Federal Reserve economists evaluated Kalshi’s macroeconomic prediction markets and argued that these markets can provide high-frequency, continuously updated, “distributionally rich” expectations data that could be valuable to researchers and policymakers.

From entertainment to infrastructure

To see where prediction markets are headed, we only need to monitor trader behavior, and the trend shows a growing number of participants integrating prediction market contracts into broader financial strategies.

This means a commodity trader monitoring oil exposure now tracks Russia-Ukraine ceasefire contracts as a live signal for geopolitical risk that directly affects energy prices. An equity trader managing a concentrated tech position watches tariff-related prediction markets to calibrate event risk that no single stock indicator captures cleanly. In both examples, contract prices are doing something no traditional instrument offers. They’re updating in real time as the narrative around a specific event shifts, and this gives traders a probability signal they can act on across their wider book.

The commodities market is a $60 trillion annual market in the United States. The entire category began with farmers hedging crop yields. This simple premise scaled because the underlying need was real. Prediction markets are approaching a similar threshold. The format is simplistic: what we currently have are binary yes/no contracts on time-elapsed events, but the need they address is both universal and largely unserved by existing instruments: they allow you to price and act on uncertainty.

Before prediction markets, there was no clean way to express a view on whether a central bank would hold rates, whether a military strike would occur or whether a trade policy would shift. Traders could try to infer these probabilities from currency pairs or futures, but they were always trading them as a proxy. Even elections, arguably the most closely watched political events, were priced indirectly, so that a clean-energy Democrat leading in the polls would suppress coal stocks. Prediction markets are a superior instrument as they price the event itself. That makes them useful as hedging tools, which is an order of magnitude more applicable.

The international dimension

The fastest-growing segment of prediction market participation is international, spread across Europe, Asia and, increasingly, emerging markets. In economies marked by currency volatility, inflation and policy unpredictability, the ability to price uncertainty is becoming a necessity for investors.

Stablecoins have already demonstrated this principle. Across Latin America and parts of Africa and Southeast Asia, digital dollars have become a mainstream store of value and remittance tool, not because users were drawn to crypto ideology, but because traditional banking infrastructure struggled with costs and volatility. Stablecoin adoption spread because it solved an everyday problem.

Prediction markets extend that applicability by providing a contract on whether a currency will depreciate next quarter, whether fuel subsidies will be cut, or whether a central bank will intervene. When such contracts are accessible through the same EVM infrastructure, a small position on a fuel price outcome starts to look less like a bet and more like insurance that provides a defined cost for a risk that is otherwise unmanageable.

Consumer-grade simplicity is not yet there, but the trajectory is visible, particularly for traders from high-volatility economies who are not treating prediction markets as entertainment. For them, they serve as an information layer that is also actionable.

What comes next

Prediction markets are now posting hundreds of millions in daily trading volume. Polymarket processed $8 billion in January; Kalshi processed $9 billion. Those figures have moved in only one direction.

But the more important evolution will be in format. The current generation of prediction markets operates on simple binary outcomes. As the category matures, expect conviction-weighted instruments, conditional contracts and markets that reference real economic indices, making these tools more useful for hedging and less dependent on novelty for adoption.

Prediction markets are gaining traction because they measure outcomes with direct economic consequences for traders. Weather and commodity-linked markets, inflation and monetary policy contracts, and geopolitical risk pricing all sit at this intersection. Prediction markets are beginning to overlap meaningfully with traditional finance.

Elections have consistently been the category that drives the deepest engagement and the largest volume spikes, and that will continue as the US midterms approach. Sports generate steady liquidity. But the long-term value of prediction markets will grow to serve a larger population of people and institutions that need to manage uncertainty as part of their daily economic lives.

A class action lawsuit has been filed against prediction market Kalshi, alleging that the death carveout in the “Ali Khamenei out as Supreme Leader” market was not properly disclosed to users and that the platform failed to pay out winning trades.

The plaintiffs said that the death carveout policy was “not incorporated into the user-facing rules summary,” and was not displayed in a way that would notify a “reasonable consumer” of the policy or its effects.

“Defendants, themselves, later acknowledged that their prior disclosures were ‘grammatically ambiguous,’” the lawsuit filing said.

Kalshi voided trading positions for the market after the death of Khamenei, the former Iranian Supreme Leader, was confirmed, meaning the market did not resolve to a “yes.”

“We don’t list markets directly tied to death. When there are markets where potential outcomes involve death, we design the rules to prevent people from profiting from death,” Kalshi co-founder Tarek Mansour said.

The plaintiffs characterized the carveout policy as “predatory” and an “unfair” business practice for this specific market. The lawsuit said:

“With an American naval armada amassed on Iran’s doorstep and military conflict not merely foreseeable but widely anticipated, consumers understood that the most likely, and in many cases the only realistic, mechanism by which an 85-year-old autocratic leader would ‘leave office’ was through his death. Defendants understood this as well.”

Mansour also announced reimbursements for users affected by the carveout policy, calculated using the “last traded price” for the market before the death of Khamenei was confirmed. The reimbursement policy also drew significant pushback from users. 

The plaintiffs in the lawsuit say that the methodology and precise timestamps used to calculate the “last traded price” for the prediction market were not disclosed or transparent. 

Related: Kalshi bans US politician over alleged insider trading violation

Kalshi co-founder fires back against lawsuit claims

Mansour maintained that Kalshi was simply adhering to its policy of not allowing “death markets” and said the policy was clearly stated in the market rules.

“Kalshi made no money here and even reimbursed all losses out of pocket. Not a single user walked away losing money from this market,” he said.

The incident came amid trading volumes on prediction markets surging to record highs in 2026, as the platforms gain popularity.

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