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Information Markets vs Prediction Markets: How Forecasting Aggregates Knowledge

Information markets and prediction markets are the same thing by different names. Learn how they aggregate dispersed knowledge into accurate probability estimates.

Marc Jakob
Senior Editor — Prediction Markets · · 3 min read
✓ Fact-checked · 📅 Updated 1 May 2026 · 3 min read
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Academics refer to them as "information markets." Those who trade call them "prediction markets." Software engineers and technologists use the term "futarchy." Each label points to an identical concept: a marketplace that harnesses financial incentives to consolidate scattered personal knowledge into a collective probability assessment.

The Core Insight: Prices Carry Information

Friedrich Hayek's seminal 1945 essay "The Use of Knowledge in Society" demonstrated that price mechanisms address the core challenge of synthesising information spread across many independent agents. Prediction markets extend this principle to uncertain future outcomes: a YES share's market value encodes the combined understanding of all participants regarding that event's likelihood.

Each participant in a prediction market holds some exclusive insight: a political researcher understands survey reliability, a sports enthusiast tracks player availability, an academic monitors experimental progress. Through their trading activity, they encode that exclusive understanding into the prevailing price. The resulting market equilibrium becomes a collective signal containing insights no individual could generate independently.

Applications Beyond Trading

Information markets have been trialled and implemented across numerous domains:

  • Corporate decision-making: Organisations establish internal markets where staff wager on product success
  • Scientific forecasting: Markets predicting whether published findings will replicate
  • Policy evaluation: Robin Hanson's "futarchy" — leverage prediction markets to assess policy effectiveness
  • Intelligence community: The CIA's Analysis of Competing Hypotheses initiative incorporated market-based methodologies
  • Supply chain management: Hewlett-Packard deployed internal markets to forecast sales volumes

Prediction Markets vs Expert Panels

Conventional forecasting depends on specialist committees who synthesise perspectives through dialogue and collective agreement. Information markets provide several structural benefits:

  • Anonymity eliminates social pressure: Specialists frequently gravitate toward prevailing opinion; market participants incur no social penalty for unorthodox positions
  • Continuous updating: Prices shift instantaneously; specialist committees assemble infrequently
  • Financial incentive: Successful forecasters capture profits; successful panellists rarely receive tangible rewards
  • No chairperson effect: The most influential person in the room cannot steer collective judgment toward their own assessment

Trade Information Markets on PolyGram

PolyGram operates dozens of information markets where your particular expertise yields a meaningful advantage. Explore current markets filtered by subject matter to discover opportunities within your specialisation.

FAQ

Are prediction markets the same as information markets?
Correct — "information market," "prediction market," "idea futures," and "event contract" serve as synonyms. They all denote the identical practice of exchanging contracts tied to uncertain outcomes.
Who invented prediction markets?
Robin Hanson at George Mason University authored substantial theoretical work during the 1990s. The Iowa Electronic Markets, launched in 1988, represented the first operational instantiation.
Can prediction markets be manipulated?
Temporary price distortion is feasible but economically costly to sustain. Academic literature demonstrates that those attempting manipulation typically suffer losses when knowledgeable traders restore equilibrium. Mature, well-capitalised markets demonstrate strong resilience against manipulation attempts.
Marc Jakob
Senior Editor — Prediction Markets

Marc has covered prediction markets and crypto order flow since 2018. Writes for PolyGram on market structure, on-chain settlement, and regulatory developments.