The history of prediction markets
Prediction markets grew out of election betting, futures markets, academic experiments, intelligence forecasting tournaments, crypto protocols, and regulated derivatives exchanges.
The short version
The modern story usually begins in 1988, when the University of Iowa launched the Iowa Electronic Markets as an experimental academic program. The CFTC now describes prediction markets as having been around in the United States since 1988 and regulated by the CFTC since 2004.
The broader movement is larger than any single platform. It includes researchers studying collective intelligence, forecasters measuring calibration, crypto builders designing decentralized oracles, and regulated exchanges creating event contracts under federal oversight.
Timeline
19th and early 20th centuries
Election betting before modern polling
Long before modern online exchanges, informal betting markets expressed beliefs about elections, wars, weather, and public events. They were not always regulated or transparent, but they showed a recurring pattern: when people care about uncertain outcomes, prices emerge.
1988
Iowa Electronic Markets
The University of Iowa created the Iowa Electronic Markets as an experimental academic program. It became an important proof point for real-money information aggregation in elections and economics.
1990s to 2000s
Academic and corporate forecasting experiments
Researchers, companies, and policy thinkers tested internal prediction markets to forecast product launches, elections, sales, and geopolitical risks. The central question was whether prices could reveal distributed knowledge faster than meetings or surveys.
2001 to 2013
Intrade and mainstream political markets
Intrade made political prediction markets visible to journalists, analysts, and election watchers. It also showed the fragility of cross-border real-money event markets when regulatory status is unclear.
2011 to 2015
IARPA, Good Judgment, and superforecasting
The U.S. intelligence community's IARPA ACE program studied forecasting at scale. Good Judgment's work helped popularize calibration, Brier scores, base rates, and the idea that forecasting skill can be trained.
2014 to 2020
Crypto prediction markets and Augur
Ethereum made it possible to build decentralized markets and decentralized resolution systems. Augur became an early example of prediction markets as open protocols rather than centralized websites.
2020 to 2022
Kalshi designation and Polymarket enforcement
Kalshi received CFTC designation as a regulated event-contract exchange. In 2022, the CFTC announced a settlement with Polymarket over offering off-exchange event-based binary options without the required registration or designation.
2024 to 2026
A new public cycle
Prediction markets became a mainstream information source for elections, inflation, sports, crypto, geopolitics, media events, and policy questions. That growth also brought sharper debates about gambling law, market manipulation, insider information, and consumer protection.
The organizations and communities that shaped the field
University researchers
The Iowa Electronic Markets, economics departments, and forecasting researchers gave prediction markets academic legitimacy. Their core contribution was measurement: prices, forecasts, outcomes, and calibration.
Forecasting communities
Good Judgment, Metaculus, Manifold, and similar communities made forecasting social and educational. They showed that not every useful prediction platform needs real-money risk.
Crypto builders
Augur, UMA, Polymarket, and related projects brought smart contracts, on-chain settlement, global liquidity, and oracle design into the conversation.
Regulated exchanges
Kalshi and other CFTC-regulated entities reframed event contracts as federally supervised derivatives markets, with rulebooks, surveillance, and customer-protection obligations.
Regulators and courts
The CFTC, state regulators, courts, and lawmakers shape the boundary between forecasting, derivatives, gaming, sports wagering, and consumer finance.
Media and public analysts
Journalists, pollsters, political analysts, economists, and researchers now quote market prices as one input among polls, models, expert judgment, and administrative data.
Why the history matters
Prediction markets sit at an unusual intersection. They are partly about economics, partly about probability, partly about technology, and partly about law. The same market can be discussed as a forecast, a derivative, a game, a public signal, or a consumer risk product depending on who is looking at it.
PolyMath should teach that complexity instead of hiding it. Better users ask better questions: What exactly resolves this market? Who can participate? What are the fees? Is there enough liquidity? Could insiders know more than the public? Is this a research signal, or am I being pulled into a story?