The dominant narrative around prediction markets still focuses on elections and sports. Sports represent the majority of the volume in the main venues, and electoral contracts are what put the category at the forefront. But based on what active traders are actually doing with real money, prediction markets are expanding with an even more impactful purpose: They are a place to hedge risks that no existing financial instrument can cleanly value because the assets are new in nature. Its applicability spans geopolitical events, policy changes, combined with commodity-related outcomes, and this market has the potential to eclipse anything sports can produce.
An example: When Kevin Warsh was nominated as the next chairman of the Federal Reserve in January, trading activity at Kalshi and Polymarket increased, and among frequent multi-market traders, the increase in volume dwarfed that of the Super Bowl. More recently, the 24-hour period surrounding the Iran conflict produced more trading activity than any sports day this year. Sports continue to account for the majority of total volume at both venues. But the operators driving growth are creating strategies across categories and locations. These traders are increasingly clustering around geopolitical, macroeconomic and policy-linked contracts. They are not looking for entertainment. They are looking for tools to assess the uncertainty that affects their other positions, their businesses and (in some economies) their family budgets.
Serious institutional voices are now articulating that change. In a February 2026 paper, Federal Reserve economists evaluated Kalshi macroeconomic prediction markets and argued that these markets can provide high-frequency, continuously updated, and “distribution-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 the behavior of traders, and the trend shows an increasing number of participants integrating prediction market contracts into broader financial strategies.
This means that a commodities trader that monitors oil exposure now tracks ceasefire contracts between Russia and Ukraine as a living sign of geopolitical risk that directly affects energy prices. A stock trader managing a concentrated technology position watches tariff-related prediction markets to gauge the risk of events that no stock indicator clearly captures. In both examples, contract prices do something that no traditional instrument offers. They update in real time as the narrative around a specific event changes, and this gives traders a probability signal that they can act on throughout their book.
The raw materials market is a $60 trillion annual market in the United States. The entire category started with farmers hedging their crop yields. This simple premise grew 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 events over time, but the need they address is universal and largely not covered by existing instruments: they allow pricing and acting on uncertainty.
Before prediction markets, there was no clear way to express an opinion on whether a central bank would hold rates, whether a military attack would occur, or whether a trade policy would change. Traders could try to infer these probabilities from currency pairs or futures, but they always traded them as proxies. Even elections, arguably the most closely watched political events, were indirectly discounted, so that a clean energy Democrat leading in the polls would suppress coal reserves. Prediction markets are a superior instrument as they value 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 the prediction market share is international, spread across Europe, Asia and, increasingly, emerging markets. In economies marked by monetary volatility, inflation and policy unpredictability, the ability to price uncertainty is becoming a necessity for investors.
Stablecoins have already demonstrated this principle. In 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 attracted to crypto ideology, but because traditional banking infrastructure struggled with costs and volatility. Stablecoin adoption spread because it solved an everyday problem.
Prediction markets expand 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 can be accessed through the same EVM infrastructure, a small position on the outcome of the fuel price begins to look less like a bet and more like insurance that provides a defined cost for an otherwise unmanageable risk.
Simplicity at the consumer level has not yet arrived, but the trajectory is visible, particularly for traders in high-volatility economies who do not treat prediction markets as entertainment. For them, they serve as a layer of information that is also actionable.
What comes next?
Prediction markets now record hundreds of millions in daily trading volume. Polymarket processed $8 billion in January; Kalshi processed 9 billion dollars. Those numbers have moved in only one direction.
But the most important evolution will be the format. The current generation of prediction markets operate 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 ground because they measure outcomes with direct economic consequences for traders. At this intersection are weather and commodity markets, inflation and monetary policy contracts, and geopolitical risk pricing. Prediction markets are starting to overlap significantly with traditional finance.
Elections have consistently been the category driving the deepest engagement and biggest volume spikes, and that will continue as the US midterm elections approach. Sports generate constant liquidity. But the long-term value of prediction markets will grow to serve a broader population of people and institutions that need to manage uncertainty as part of their daily economic lives.
