Prediction markets: The price of truth
Terms like Polymarket and Kalshi have increasingly been popping up in the world of finance over the last few months, causing confusion at times. The talk is about prediction markets, where people can bet on the outcome of future real-world occurrences ranging from sports events and US Federal Reserve interest-rate decisions to Nobel prize winners. What sounds at first like pure gambling could in fact effectively supplement surveys and expert opinions as forecasting tools in the future.
The principle of tradable probability
On January 3 this year, before the first breaking reports reached news agencies, the probability of an immediate change of power in Venezuela skyrocketed on the Polymarket prediction platform while the country’s ruler, who has since been forced into retirement, was still fast asleep in bed. Mere hours later, official reports confirmed the arrest of Nicolás Maduro through a US-led operation. While diplomacy was still groping for words, markets had already priced in the incident.
The trading volume on prediction markets has multiplied since their establishment in the course of the US presidential election in 2024, during which they foretold the Republican victor much earlier than electoral polls did. While the monthly trading volume in August 2025 amounted to USD 1 billion, by March 2026 it had already surged to USD 10 billion on Polymarket alone. Some individual contracts by now exhibit bid volumes amounting to several hundred millions of dollars. What started out as a niche for crypto enthusiasts and gamblers has since evolved into a global fever chart of reality.
The rise of prediction markets | From niche market to hype
Monthly trading volume on Polymarket (in USD billion)
Sources: Dune Analytics, Kaiser Partner Privatbank
A fascinatingly simple logic lies behind this phenomenon. A prediction market in essence is a trading venue for binary events. On prediction platforms – Kalshi and Polymarket being the two most prominent ones – participants trade contracts that take on a value of either 1 dollar (if the specified event outcome occurs) or 0 dollars (if the specified event outcome does not occur). The probability aggregated by the market thus can be directly deduced from the current market price of a contract of that kind. If a “yes contract” for a certain election outcome, for instance, costs 72 cents, this signifies a (theoretical) 72% chance of occurrence. Classical sports betting, in contrast, does not operate on the principle of supply and demand, but instead has odds that are set by the bookmaker. The odds, in principle, are set to the disadvantage of the bettor, for it’s well-known that the house always wins in the long run.
Wagers rather than words |Probabilities on the platform PredictIt
Comparing election forecasts in the 2024 US presidential election
Sources: Bloomberg, PredictIt, Kaiser Partner Privatbank
The prediction market principle can be carried to extremes. Anyone betting on Polymarket right now that Jesus Christ will return to Earth in 2026 pays 4 cents for that contract. The market is pricing in a paltry 4% probability of a Second Coming this year. Whoever, though, possesses an information advantage – such as in the form of divine intuition – and accordingly bets USD 1,000 on “yes” can rejoice over a biblical return of USD 25,000 if that hunch proves true.
Economic profit as a truth filter
The decisive advantage over classical surveys or expert opinions lies in the economic incentive structure. Whereas responses from survey participants often reflect social desirability, disinterest, or incompetence, prediction markets force speculators to be painfully honest in the literal sense of putting their money where their mouth is. Anyone who bets wrong on prediction markets loses money. Whoever possesses information that is not yet reflected in the market has a financial incentive to divulge it by trading. Every bet influences the probability and adds new data to a public indicator that reflects the societal consensus. To an economist, this is market efficiency par excellence because predictions of this kind measure what people actually believe while surveys only measure what people say.
A rocky road to a global standard
Polymarket fired the starting gun for its entry into the prediction business in the year 2020, though the platform’s decentralized blockchain foundation quickly ran afoul of US regulatory authorities. The bets were legally classified as a form of event-based binary options and were placed under strict transparency rules for futures exchanges. Without a corresponding designated contract market license, prediction markets were considered illegal over-the-counter businesses. Recent court rulings in favor of the platforms and the establishment of regulated operators like Kalshi marked a preliminary end to the “Wild West” era of prediction markets. A milestone in this evolution was the acquisition of a strategic stake in Polymarket by stock-exchange operator Intercontinental Exchange, the parent company of the New York Stock Exchange. Legal uncertainties nonetheless continue to exist: in the USA, the platforms are increasingly coming under pressure on matters concerning politically sensitive topics while a uniform framework is missing in Europe. Prediction markets mostly operate in Europe in a legal gray zone between tacit tolerance and national bans. Their technology transcends borders, but there is still a long road to the establishment of a global standard.
The wisdom of the crowd
But why are these markets often more accurate than panels of experts are? Behavioral economics provides an answer in the “wisdom of the crowd,” the collective sapience of the general public. When a diverse group of individuals make decisions independently from one another and risk their own money in the process, individual errors and ideological biases balance each other out. In the best case, emotions get filtered out of the market. Unlike classical stock markets, which are often driven by narrative overstatement and by speculation on falling or rising prices, prediction markets correct on new information usually within fractions of a second, because whoever deliberately wants to skew a bet mainly creates a chance of winning for better-informed wagerers by doing so.
A new toolkit for managing risk?
Institutional investors, particularly hedge funds and banks, have also recognized the potential of prediction markets in the meantime. They are being used primarily not as a speculation instrument (although that possibility is surely also being looked into), but as a highly sensitive supplemental risk management tool. In a world in which portfolios are increasingly threatened by event risks such as court rulings, corporate data releases, populist currents, and geopolitical escalations, prediction markets provide an implied probability curve. They act as an early warning system that enables hedging strategies to be assessed more precisely and implemented immediately. If, for example, an escalation of the conflict in the Middle East looms that would drive up the price of petroleum, one can bet on the occurrence of a military clash on Polymarket or Kalshi. The winnings from a prediction of that kind could partially offset the losses caused by the oil shock. In contrast to classical hedges like gold that rise only in general in times of market uncertainty, the prediction market pays out only if a specific event takes place.
One particular advantage here is temporal continuity. Whereas many conventional surveys deliver data only on a monthly or quarterly basis, prediction markets provide probabilities in real time, which can be beneficial especially during crises. That’s why the platforms are increasingly finding their way into analytic and research processes in the financial sector and into politics and general research. Even a recent report by the US Federal Reserve affirms their potential as a valuable supplement to conventional forecasting tools.1 They have particularly high potential to aid in forecasting policy interest rate decisions and headline inflation.
Accuracy comparison |Kalshi vs. futures market in forecasting US federal funds rate
Forecast error over time ahead of the next Fed meeting
Sources: Board of Governors of the Federal Reserve System, Kaiser Partner Privatbank
It’s worthwhile also for individual private investors to take a look at Polymarket, Kalshi, and the like for the purpose of gathering information. The value here lies not in betting, but in capturing signals in real time. However, anyone entertaining thoughts of betting his or her own money on future event outcomes should beware that wagers of that kind normally are not worth it financially, particularly not if one lacks extensive expertise in a specialized field that can beat the market. On top of that, there are also platform-specific fees to pay and an additional fact to bear in mind: people with information advantages are particularly the ones that profit while uninformed investors get the short end of the stick.
A psychological dilemma
Despite their potential, prediction markets are still in their infancy and sometimes harbor downsides. Criticism, for instance, has been leveled that individual contracts often have scant trading liquidity, which leads to vague probabilities. A single order can influence the price, and bid-ask spreads can widen. In addition, a moral dilemma arises when wagerers bet on catastrophes or political instability. Critics also find fault with the contradiction that unethical insider trading paradoxically can increase prediction accuracy and thus enhance market efficiency. Here’s a thought experiment to illustrate this: Suppose that a football player has disclosed that he would like to leave his current club to join another one. (Purported) experts and gamblers will bet on his most probable next club address on prediction markets. But what prevents the player from anonymously betting his own money on the club of his dreams or from even intentionally transferring to an improbable club to maximize his profit?
This seemingly trivial example has an important implication. It shows that prediction markets have the potential to “read the crystal ball” by indirectly influencing reality or, in other words, by actuating a self-fulfilling prophecy, except in the case of exogenous, non-reflexive events like the weather, for instance. However, insider trading, although it’s unfair to those not in the know, helps markets to learn faster. When the odds change, it is often a sign that somebody somewhere knows something, and that signal becomes public long before any corresponding announcement does. Nevertheless, prediction markets do not always correctly foretell the future. The wisdom of the crowd can also be wrong. Individual investors remain faced with the challenge of distinguishing between genuine signals and pure noise.
The financial market in the age of digitalization
In all probability, prediction markets are not a passing fad, but rather a natural progression of financial markets in the information age. They are a testament to the fact that information itself has become a tradable good, no longer just in betting offices, but as a public indicator for everyone. In the future, the ability to interpret signals correctly will become a core competency in asset management. Signals give us no certainty about future occurrences, but they provide us with an additional market-based seismograph for a world increasingly affected by event risks.
1 Diercks, Anthony M., Jared Dean Katz, & Jonathan H. Wright (2026). “Kalshi and the Rise of Macro Markets,” Finance and Economics Discussion Series 2026-010. Washington: Board of Governors of the Federal Reserve System.