Prediction markets are having a moment. Again. Monthly trading volume in September more than doubled to $4.28 billion, Robinhood is expanding its prediction products global after successful U.S. debut. Even South Park dedicated an episode to them. But beyond the buzz, what makes these markets move? And do they represent a sophisticated new information economy or just another "degen trench" for online speculators? The answer reveals something profound about how we find truth in the age of infinite takes.
Pricing Probability
The basic mechanics are simple: you can buy a contract that pays $1 if an event occurs and $0 if it doesn't. The contract's current price reflects the market's probability estimate. So your profit comes from being right when the market is wrong.
"If you think that Trump has a 70% chance of winning, and you go to the market and you see that the price of that asset is $0.55 cents, you're gonna wanna buy! Because you're buying something you think is worth $0.70 cents... and you can buy it for $0.55 cents, you expect to make $0.15 cents. And by doing that, you push the price closer to $0.70 cents."— Alex Tabarrok, economist at George Mason University, a16zcrypto podcast
Traders seeking quick, binary payoffs are finding them more and more in election odds, macro prints, sports, and pop-culture markets. These markets offer perps-like dynamics with news-driven volatility.
When Markets Know More
Friedrich Hayek demonstrated that markets better aggregate dispersed knowledge than centralized planning.
"What Hayek said is that markets do this. Because markets give people an incentive – through their buying and selling – to reveal this kind of information. To pull this dispersed information for millions of people... And kind of remarkably, the price can sort of know more than any person in the market." — Alex Tabarrok in a16zcrypto podcast
Prediction markets weaponize this insight: thousands of traders, each holding fragments of information, collectively generate forecasts that outperform experts.
But crowd wisdom has its limits. Specifically, markets need organic demand to function. As economist Alex Tabarrok notes:
"If you didn't have the organic demand, then you're gonna have a market with just sharks in it – no farmers, and just sharks. And who wants to be in a market where you're only with other sharks, right?" — Alex Tabarrok in a16zcrypto podcast
This explains why election betting markets thrive due to natural interest, whereas obscure prediction markets fail (where only pros trading against other pros).
Platforms actively incentivize users who provide liquidity by placing limit orders close to the market midpoint, narrowing the spread and making the market more efficient for everyone. The closer to the spread, the larger the rewards. It's active market-making — a system that incentivizes building a robust market, not just placing a winning bet.
The Cypherpunk Prophecy
Although prediction markets have existed for over a century, their current revival is closely tied to the cypherpunk movement's dream emerged decades ago.
Back in the 1990s, they grabbed onto this idea, viewing prediction markets not just as forecasting tools but as powerful mechanisms for finding truth and resisting centralized power. But they quickly hit a wall when governments freaked out about "terrorism betting," which essentially pushed the whole concept underground for years.
The cypherpunk dream only came back to life with cryptocurrencies and smart contracts, which provided the missing piece: a way to build global, censorship-resistant markets. Platforms like Polymarket and Augur can now run without traditional middlemen, executing contracts automatically. This makes them nearly impossible for any single government to shut down completely.
This is where cryptography stops being theater and becomes real infrastructure. Censorship-resistant markets allow Chinese citizens to bet on their own politics. Smart contracts enable markets on "illegal" topics (will X be arrested?). Global liquidity means a trader in Buenos Aires can bet against someone in Bangkok without trusting intermediaries.
Truth and Limits
Psychology and social sciences face a replication crisis — most published findings can't be replicated. Enter prediction markets: scientists now bet on which papers will replicate.
"It's a way to make science better, faster and more accurate," Alex Tabarrok notes. Markets predict replication outcomes with roughly 70% accuracy, saving millions on repeat studies.
But prediction markets aren't an infallible way to find truth. They have some notable failures, like missing the Brexit referendum result and Donald Trump's 2016 victory. This points to a key limitation of prediction markets: they are good at aggregating known unknowns but fail with unknown unknowns.
"It is not a useful mechanism for actually figuring out the future in terms of what to invent. Because it doesn’t address a case of ‘you don’t know what you don’t know’. You only know what you know." — Sonal Chokshi in a16zcrypto podcast
Beyond this conceptual blind spot, there are also practical challenges. These include the risk of manipulation by large players who can distort prices, the problem of "thin" markets on niche topics that turn into echo chambers, and the persistent "oracle problem" — how to reliably verify real-world events on the blockchain.
“While prediction markets can help us root out truth or information in ways that traditional reporting and polling can’t, we have to remember that prediction markets are simply a financialized form of consumer sentiment aggregation.” — Loxley Fernandes, Dastan CEO, for Decrypt
The AI-Powered Future
The next frontier is corporate governance. Picture a continuous market for a public company answering one question: "Would our stock price go up if we fired the CEO?" Instead of watching shares soar after a leader leaves (like Microsoft did post-Steve Ballmer), the board could have a real-time signal of their actual value.
If you scale this idea, you get futarchy — economist Robin Hanson's radical proposal to replace politicians with markets. Citizens vote on goals (like "GDP + happiness"), and markets determine which policies will most likely get us there.
While futarchy may seem like a distant future, the artificial intelligence revolution is happening right now and is poised to change prediction markets.
AI will play three roles: as a tireless trader, wiping out inefficiencies around the clock; as a superhuman analyst, processing world news faster than any human; and even as an increasingly reliable oracle, verifying outcomes to settle blockchain disputes. In this last role, AI is already changing the game. For instance, Elon Musk's xAI is working with Kalshi on AI-based verification of event outcomes.
As Vitalik Buterin noted in his essay "From prediction markets to info finance," this could create virtually infinite liquidity.
"Because if you can have a lot of AIs trying to predict things, well that lowers the cost tremendously. And that opens up the space of possibilities of what you can use prediction markets for." — Alex Tabarrok in a16zcrypto podcast
"A bet is a tax on bullshit," as Alex Tabarrok put it in the podcast. In a world of "post-truth," endless opinions and reckless claims, they make you put something real on the line. They attach a price to being wrong.
MetaTalks disclaims responsibility for any investment advice that may be contained in this article. All judgments expressed are solely the personal opinions of the author and the respondents. Any actions related to investing and trading in crypto markets involve the risk of losing funds. Based on the data provided, you make investment decisions in a balanced, responsible manner and at your own risk.