“Prediction markets are online exchanges where people trade contracts on the outcomes of future events, aggregating collective wisdom to forecast results, with contract prices reflecting the market’s perceived probability of an event, like an election or economic data, occurring.” – Prediction market
Prediction markets are online platforms where participants trade contracts tied to the outcomes of future events, such as elections, economic indicators, or corporate milestones. These contracts, often binary in nature, pay out a fixed amount-typically $1-if the event occurs and nothing otherwise, with their prices directly reflecting the market’s collective assessment of the event’s probability.1,2,3 This mechanism harnesses the wisdom of crowds, incentivising traders with financial stakes to reveal their information, often outperforming expert forecasts or polls due to the skin-in-the-game dynamic.1,2
How Prediction Markets Function
Trading occurs via mechanisms like continuous double auctions, automated market makers, or parimutuel pools, enabling efficient price discovery.1 For instance, a contract trading at 72 cents implies a 72% perceived probability of the event.3 Contract types include:
- Winner-take-all: Binary yes/no payouts, most common for discrete events.1,6
- Index contracts: Payouts varying continuously, e.g., based on vote shares or sales figures, reflecting expected values.1,6
- Combinatorial markets: Bets on outcome combinations, enhancing conditional probability incorporation.2
Markets can use real or virtual currency, with public examples like PredictIt (politics/finance), Polymarket (decentralised on blockchain), and Metaculus (reputation-based forecasting).2,4
Applications and Evidence of Efficacy
Corporations leverage internal prediction markets for project timelines, sales forecasts, risk assessment, and strategic planning.1,2 Eli Lilly used them in 2005 to predict drug trial success; Google for product launches and office openings.2 Studies show superior accuracy, e.g., forecasting Iowa flu outbreaks weeks ahead.2 Eric Zitzewitz notes their efficiency akin to financial markets.2
Key Theorist: Robin Hanson and the Genesis of Formal Prediction Market Theory
Robin Hanson, an economist renowned for pioneering prediction markets as tools for information aggregation, stands as the preeminent theorist. Born in 1958 in Chicago, Hanson earned a physics BS from the University of California, Riverside (1981), followed by astrophysics study at the University of Chicago. Shifting to social sciences, he obtained an MA in physics (1984) and PhD in social science from Caltech (1990), with a thesis on ‘The Dynamics of an Astronomy Research Project’.2
Hanson’s seminal contributions began in the 1990s at Lockheed and NASA, modelling organisations via market processes. In 1998, his paper ‘Shall We Vote on Values, But Bet on Outcomes, Or Both?’-later titled ‘Combinatorial Information Market Design’-proposed log scoring rules for subsidised markets, enabling cheap, truth-revealing forecasts even without skin in the game.2 As research associate at Future of Humanity Institute and professor at George Mason University, Hanson developed Futarchy: governance by betting on policies’ outcomes rather than voting on values. His 2003 paper ‘Shall We Vote on Values but Bet on Outcomes?’ formalised this, arguing prediction markets elicit honest beliefs better than surveys. Books like The Age of Em (2016) extend his futurology. Hanson’s work underpins platforms like Augur and theoretical validations of market efficiency in aggregating dispersed knowledge.1,2
Critics highlight risks like manipulation or thin liquidity, yet empirical evidence affirms their forecasting prowess across politics, business, and science.1,2,3
References
1. https://corporate.jasoncollins.blog/prediction-markets
2. https://en.wikipedia.org/wiki/Prediction_market
3. https://www.metrotrade.com/what-is-a-prediction-market/
5. https://www.greenbook.org/marketing-research/prediction-markets-for-concept-testing-04799
6. https://wifpr.wharton.upenn.edu/blog/a-primer-on-prediction-markets/
7. https://a16zcrypto.com/posts/podcast/prediction-markets-explained/
