Why prediction markets matter

They're suddenly everywhere. In December, CNN and CNBC both signed deals to put a prediction market's odds on air — CNN's chief data analyst now reads them out next to the polls, and not everyone is happy about it.¹ Monthly trading volume across the leading venues has climbed from under $100M two years ago to more than $13 billion.² Kalshi, the first U.S.-regulated exchange, was just valued at $11B; the owner of the New York Stock Exchange has committed up to $2B to Polymarket — not to place bets, but to distribute its data.³ A product that was an academic curiosity for thirty years became real infrastructure in about twenty-four months.

But what is a prediction market, and why should anyone outside a trading desk care? The short version: it is a market where you trade contracts that pay out on whether something happens — an election, a rate decision, an airport opening on time. And the reason it matters is that the price of that contract is a number you can't get any other way: a continuously-updated, money-weighted estimate of how likely the future is. Not an opinion. A forecast, with capital behind every revision.

A price is a probability

Start with the simplest possible contract. It pays $1 if some event resolves YES, and $0 if it resolves NO. What should it cost today?

A trader who thinks the event is 62% likely will buy at any price below 62¢ and sell above it. So will everyone else, each at their own number. The price stops moving only when it sits exactly at the crowd's collective estimate — because at that point there's no edge left to trade on. The fair price is the probability:

That equation is the whole idea. A contract trading at 62¢ is the market saying 62% — no translation, no spin. The order book is a probability distribution you can read directly, and it re-prices the instant the world changes. Every other forecast — a poll, a pundit, a committee memo — is a snapshot. This one is live.

Why the number is accurate

A poll costs nothing to answer, and nothing to answer wrong. A market is the opposite: every view is a position, and being wrong costs money. That single difference — skin in the game — is what makes the price sharp.

Suppose the market sits at 50¢ but you've done the work and believe the true probability is 67%. You have a 17¢ edge on every share, so you buy — and your buying pushes the price up toward your estimate. The edge any trader sees is just the gap between their belief and the price:

Mispricings are money lying on the floor. The better-informed you are, the more you bet, and the harder you pull the price toward the truth. Money doesn't just measure confidence — it weights it, handing the loudest voice to whoever is most willing to be wrong in public for cash. In the 2024 U.S. election, one trader reportedly ran his own private polls — paying for better information than the public had — and moved size on the result, making tens of millions when he was right.⁴ A poll could never reward that work. A market pays for it.

The effect shows up in the shape of the signal. A poll arrives every few days, lurches with sampling noise, and lags the news. A market is a line that moves the second something happens — because the first trader to understand the news has a profit waiting if they act before everyone else.

Market · continuous Polls · periodic, lagging

This isn't only intuition. Decades of research on market-based forecasting find that, when they're liquid enough to function, prediction markets beat polls, expert panels, and statistical models on a wide range of questions.⁵ The reason is structural, not magical — and it's the next idea.

It aggregates what no one knows alone

In 1945, Friedrich Hayek pointed out that the knowledge a society needs to make good decisions is never held in one place. It's scattered — "dispersed bits of incomplete and frequently contradictory knowledge" spread across millions of people, none of whom sees the whole picture.⁶ A price, he argued, is the device that pulls all those private fragments into one public number, so people can act on what others know without ever being told it directly.

A prediction market is that idea aimed straight at the future. Thousands of people each hold a sliver of relevant information — a poll a campaign hasn't released, a supplier's quiet warning, a doctor's read on a trial. None of them can forecast the outcome alone. The market lets each one stake their sliver, and the price collapses all of it into a single, living probability.

Because anyone can create a market, this sensor points at questions no exchange ever bothered with. Will this AI model top the benchmark next quarter? Will this scientific result replicate? Will the new airport open by June? Firms already run internal markets to forecast their own launch dates; researchers have used them to predict which experiments will hold up.⁷ Anyone can stand up a market for a question worth answering — and the crowd will price it. This is far older than the apps, too: as far back as the 16th century, bettors in Rome were quoting live odds on papal succession,⁸ and election betting was front-page news decades before scientific polling existed.

A forecast, not a bet

This is where most people get prediction markets wrong, so it's worth being precise. A casino and a prediction market both involve money and uncertainty. They are opposites in the one way that counts.

At a casino, the house sets the odds and builds in a margin, so the average player loses by design and no information is produced — the roulette wheel knows nothing about the world. In a prediction market, nobody sets the odds; the price floats to the crowd's best estimate, the most accurate forecasters win money from the least, and the by-product is something valuable to everyone, player or not: a public, real-time probability.

The casino

House odds · fixed margin

• The operator sets the odds
• Luck-driven — no information value
• The house wins on average, by design
• A wager that simply wins or loses

The prediction market

Yes 62¢ · No 38¢ · the crowd's price

• The market discovers the price
• Information-driven — the better forecast wins
• The most accurate traders win, not the house
• A position you can buy or sell anytime

That distinction is what makes an event contract a financial instrument rather than a game — and it unlocks the most underrated use of all: hedging. If your business depends on a central-bank decision, a port opening on schedule, or a mild winter, you can take the other side of that risk and offload it. A prediction is something you watch. A hedge is something you own. Event contracts let you insure outcomes that no insurer will write a policy for.

Now, be honest about what this looks like today: most of the volume is sports. On Kalshi, sports contracts have made up around 80% of trading since they launched.⁹ Plenty of people are using these markets to bet on games, and the "it's just gambling" headlines aren't wrong about that. But the mechanism is still the thing that matters. Even a market on the Super Bowl is priced by the crowd, not set by a house — and it leaves behind a public probability a sportsbook never will. The sports volume is the on-ramp; the forecast, and the hedge, are where it goes next.

The money moving in is buying infrastructure

For most of its life this was a fascinating idea with no liquidity. Then the institutions arrived — and what they bought says what they think it is. The Intercontinental Exchange, which owns the New York Stock Exchange, committed up to $2B to Polymarket — structured not as a wager but as a deal to become the global distributor of its event data, piping crowd-implied probabilities to institutions alongside its securities feeds.¹⁰ Kalshi, the first federally-regulated exchange, was just valued at $11B; CME and Cboe are building their own event-contract products. This is infrastructure money, not novelty money — and it is buying the rails, not a seat at the table.

ICE → Polymarket

up to $2B

For the data, not the bets — ICE becomes the global distributor of Polymarket's event feed. Oct 2025.

Kalshi

~$11B

The first U.S.-regulated exchange, valued in its latest round. Dec 2025.

CME · Cboe

entering

The established derivatives exchanges are building their own event-contract products.

What's still hard

None of this means the machine runs itself. Three problems stand between a clever idea and a market you can trust.

Liquidity. A new market is empty — you want to trade, but there's no one to trade against. The fix is an automated market maker: a formula that always quotes a price, with a known, finite cost to the operator. The mechanics — Robin Hanson's market-scoring rule, and why a market maker's losses are mathematically bounded — are their own essay; I walk through them in Prediction markets, explained.¹²

Resolution. Someone has to declare what actually happened, cleanly and without dispute. If the outcome can be gamed or argued, the price means nothing. The answer is disciplined settlement — multiple independent sources, an auditable trail, fully collateralised payouts so nothing defaults.

Trust. A market is only a sensor if its price is honest, which means defending against manipulation and insider trading. The reassuring part is that a market fights back on its own: push the price away from the truth and you hand every other trader a profit for shoving it back. The unreassuring part is that self-correction isn't enough at scale — you need real surveillance, position limits, and someone accountable for the integrity of the book.

That last point is the one we spend our days on at Seeker. Two of these three problems are engineering. The third — trust — is mostly regulatory: in most countries a market that pays out on real-world events is a licensed financial product, and the right to run one is granted one jurisdiction at a time. That's the part people underrate. The mechanism is universal and copyable; the license is neither. It's the pattern crypto exchanges walked a decade ago — the US legitimized the asset class, then every market opened it one regulator at a time, and the first licensed venue took most of the liquidity. Our bet is that prediction markets run that same playbook, and that the venue people trust in each market is the one that showed up early, built the surveillance and settlement in from the first trade, and won the license to operate inside the rules rather than around them.¹³

The deeper reason to care has nothing to do with any one company. A society that can see its own best guess about the future — priced in the open, updated in real time, with money keeping everyone honest — makes better decisions than one arguing over stale polls and confident pundits. If we get the trust problems right, prediction markets stop being a place to gamble on the news and become part of the infrastructure we use to navigate what's coming. That's why they matter.