In this guide
Within academic circles, they are termed "information markets." Those actively trading refer to them as "prediction markets." Silicon Valley and technology innovators favour "futarchy." Despite the nomenclature variation, each label points to an identical concept: a marketplace that harnesses monetary incentives to synthesise scattered knowledge held across many participants into a unified probability assessment visible to all.
The Core Insight: Prices Carry Information
Friedrich Hayek's seminal 1945 work "The Use of Knowledge in Society" demonstrated that price mechanisms address the central challenge of pooling knowledge distributed across countless independent actors. Prediction markets extend this principle to uncertain future events: the cost of a YES contract encapsulates the collective understanding of all market participants regarding that event's likelihood.
Each market participant brings distinct proprietary insights: a political strategist understands survey methodology and reliability, a sports analyst monitors team health and roster changes, a researcher grasps experimental progress and timelines. As these participants execute trades, their exclusive knowledge becomes embedded within the market price. That resulting price functions as a collective data point synthesising information no individual trader could possess on their own.
Applications Beyond Trading
Information markets have been piloted and implemented across numerous domains:
- Corporate decision-making: Organisations establish internal markets where staff stake capital on product launches and business outcomes
- Scientific forecasting: Markets tracking whether published research findings will replicate successfully
- Policy evaluation: Robin Hanson's "futarchy" framework — deploying prediction markets as the mechanism for assessing governmental and institutional policy choices
- Intelligence community: CIA's Analysis of Competing Hypotheses initiative incorporated market-based analytical methodologies
- Supply chain management: HP implemented internal markets to forecast demand and sales velocity
Prediction Markets vs Expert Panels
Conventional forecasting methodologies depend on specialist committees who synthesise perspectives through dialogue and agreement-building. Information markets present several structural benefits:
- Anonymity eliminates social pressure: Specialists tend toward prevailing opinion within their group; market participants incur no social penalty for minority positions
- Continuous updating: Prices shift in real-time as new data emerges; specialist committees typically gather infrequently
- Financial incentive: Accurate traders earn returns; accurate panellists rarely receive tangible compensation
- No chairperson effect: The most influential or senior panellist cannot steer collective judgment toward their preferred conclusion
Trade Information Markets on PolyGram
PolyGram operates hundreds of information markets where domain-specific expertise translates into measurable trading advantage. Explore live markets organised by subject area to identify opportunities aligned with your knowledge base.
FAQ
- Are prediction markets the same as information markets?
- Correct — "information market," "prediction market," "idea futures," and "event contract" function as synonyms within the literature. Each terminology denotes the identical trading mechanism centred on event outcomes.
- Who invented prediction markets?
- Robin Hanson at George Mason University authored the bulk of theoretical work during the 1990s. The Iowa Electronic Markets, launched in 1988, represented the earliest operational deployment.
- Can prediction markets be manipulated?
- Temporary price distortion is feasible but economically costly to maintain over time. Empirical evidence demonstrates that actors attempting artificial price movements ultimately suffer losses when informed traders correct the mispricing. Sufficiently large and actively traded markets demonstrate substantial resilience against manipulation attempts.