Prediction Markets Glossary

A prediction market is a speculative exchange where participants trade contracts whose final value is tied to the outcome of a future event. Unlike opinion polls, prediction markets require participants to put capital behind their beliefs — creating a powerful incentive for accuracy. The price of a contract at any moment reflects the collective probability that the market assigns to that outcome occurring.

An event contract is a financial instrument whose value depends on whether a specific real-world event occurs. If the event happens, the contract pays out a fixed amount (typically $1); if it does not, it expires worthless. Event contracts are the building block of prediction markets — every market on Kalshi and Polymarket is structured as a collection of event contracts.

A binary contract resolves to one of exactly two outcomes: yes or no, 1 or 0. It pays $1 if the event occurs and $0 if it does not. Binary contracts are the most common structure in modern prediction markets. Their simplicity makes them easy to price, trade, and aggregate into probability signals.

A conditional market prices the probability of Event B occurring given that Event A has already occurred. For example: "What is the probability of a recession in 2026, conditional on the Fed cutting rates?" Conditional markets are more complex than binary markets but generate richer information — they reveal not just what the market thinks will happen, but why.

A market maker is an entity that continuously quotes both buy and sell prices for a contract, providing liquidity to other participants. In prediction markets, market makers profit from the bid-ask spread while bearing inventory risk. Without market makers, thin prediction markets would have wide spreads and poor price discovery.

Resolution criteria define precisely how and when a prediction market contract will be settled. Ambiguous resolution criteria are one of the most common sources of disputes in prediction markets. A well-designed market specifies: what source will be used to determine the outcome, what date and time the market resolves, and how edge cases will be handled.

Kalshi is a regulated prediction market exchange based in New York, founded in 2018 by Tarek Mansour and Luana Lopes Lara. In 2020, Kalshi became the first CFTC-regulated prediction market exchange in the United States — a regulatory milestone that legitimized the industry. Kalshi offers markets on economics, politics, weather, and finance, with contracts settling at $1 or $0.

Polymarket is a decentralized prediction market platform built on the Polygon blockchain, founded by Shayne Coplan in 2020. Unlike Kalshi, Polymarket operates through smart contracts and uses USDC as its settlement currency. Polymarket gained significant attention during the 2024 US election cycle and has since grown to a valuation exceeding $20 billion, with over $3 billion in monthly trading volume.

Metaculus is a forecasting platform that aggregates probabilistic predictions from a community of forecasters. Unlike Kalshi and Polymarket, Metaculus does not involve real-money trading — participants earn reputation points for accurate forecasts. Metaculus is particularly strong on long-horizon scientific and geopolitical questions, and its community of forecasters has demonstrated consistent calibration.

Manifold Markets is a play-money prediction market platform that allows anyone to create markets on any question. Founded in 2021, Manifold uses a proprietary currency (Mana) rather than real money, removing legal barriers while maintaining forecasting incentives. Manifold is notable for the breadth of its markets and its open API.

PredictIt is a New Zealand-based prediction market focused on US political events, operating under a no-action letter from the CFTC. Founded in partnership with Victoria University of Wellington, PredictIt has operated since 2014 as a research platform. Its legal status has been periodically challenged — the CFTC attempted to revoke its no-action letter in 2022, though PredictIt continues to operate pending legal resolution.

The Logarithmic Market Scoring Rule (LMSR), developed by economist Robin Hanson, is an automated market maker mechanism designed for prediction markets. The LMSR allows a single market maker to provide continuous liquidity by automatically adjusting prices based on the quantity of contracts purchased. The cost function ensures that the market maker's subsidy is bounded, making it practical to run markets even with low participation.

Information aggregation is the core theoretical justification for prediction markets: by giving dispersed individuals an incentive to reveal their private information through trading, markets aggregate knowledge that no single entity possesses. Friedrich Hayek's insight — that prices coordinate decentralized knowledge — is the foundation of information aggregation theory in economics.

Friedrich Hayek's 1945 paper "The Use of Knowledge in Society" argued that economic knowledge is inherently dispersed — no central authority can possess all the information needed to make optimal decisions. Price systems, Hayek argued, aggregate this dispersed knowledge efficiently. Prediction markets are a direct application of Hayek's insight: they create prices that aggregate private information about future events.

Superforecasters are individuals who demonstrate sustained, significantly above-average accuracy in probabilistic forecasting. The concept was developed by Philip Tetlock through the Good Judgment Project, a multi-year forecasting tournament. Superforecasters share common traits: they think in probabilities, update beliefs frequently, aggregate information from multiple sources, and distinguish carefully between what they know and what they are uncertain about.

A forecaster or prediction market is well-calibrated if events assigned 70% probability occur approximately 70% of the time, events assigned 30% probability occur approximately 30% of the time, and so on. Calibration is distinct from accuracy — you can be accurate on average but poorly calibrated, or well-calibrated but wrong on specific high-stakes questions.

The Brier Score is a proper scoring rule for evaluating probabilistic forecasts. It measures the mean squared difference between predicted probabilities and actual outcomes. A perfect Brier Score is 0; the worst possible score is 2. Unlike simple accuracy measures, the Brier Score penalizes both overconfidence and underconfidence — rewarding forecasters who correctly express uncertainty.

The Efficient Market Hypothesis holds that asset prices fully reflect all available information. In its strong form, no trader can consistently achieve above-market returns because prices already incorporate all known information. Prediction markets are often described as highly efficient — but they exhibit systematic biases, including favorite-longshot bias (overpricing low-probability outcomes) and anchoring effects.

The wisdom of crowds, popularized by James Surowiecki's 2004 book, holds that the aggregated judgments of many independent individuals often outperform expert opinion. The conditions for crowd wisdom are: diversity of opinion, independence of participants, decentralized knowledge, and an effective aggregation mechanism. Prediction markets are designed to satisfy all four conditions.

The Commodity Futures Trading Commission is the US federal regulatory agency with jurisdiction over derivatives markets, including futures, options, and swaps. The CFTC's authority over prediction markets derives from the Commodity Exchange Act, which classifies prediction market contracts as "event contracts" — a form of commodity derivative. Kalshi became the first CFTC-regulated prediction market exchange in 2020.

The Commodity Exchange Act is the primary federal legislation governing derivatives markets in the United States. Amended significantly by the Dodd-Frank Act in 2010, the CEA grants the CFTC authority to regulate "event contracts" — the legal category under which prediction market contracts fall. Section 5c(c)(5)(C) of the CEA gives the CFTC authority to prohibit event contracts it deems contrary to the public interest.

Federal preemption is the constitutional doctrine, derived from the Supremacy Clause, that federal law supersedes conflicting state law. In the context of prediction markets, federal preemption is the primary legal argument against state attempts to regulate prediction markets as gambling. If the CFTC has jurisdiction over prediction market contracts as event contracts under the CEA, state gambling laws cannot simultaneously apply.

A no-action letter is a communication from a regulatory agency stating that it will not take enforcement action against a specific entity for a specific activity. In prediction markets, no-action letters have been used by the CFTC to permit certain platforms (notably PredictIt) to operate outside the full regulatory framework. No-action letters provide limited protection — they can be revoked and do not constitute formal regulatory approval.

An order book is a real-time list of buy and sell orders for a contract, organized by price. Buyers post bids (the maximum price they will pay) and sellers post asks (the minimum price they will accept). The market price is determined by where bids and asks overlap. Kalshi uses an order book model. Order books provide transparent price discovery but require sufficient participants to function well.

An Automated Market Maker is an algorithm that provides continuous buy and sell quotes for a contract without requiring a human counterparty. AMMs use mathematical formulas (such as the LMSR or constant product formula) to set prices based on contract inventory. Polymarket uses an AMM model, which allows it to provide liquidity on markets with few active traders.

Arbitrage is the simultaneous purchase and sale of equivalent assets to profit from price discrepancies. In prediction markets, arbitrage opportunities arise when the same event is priced differently across platforms (e.g., Kalshi pricing a Fed rate cut at 65% while Polymarket prices it at 72%). Arbitrageurs who exploit these gaps push prices toward convergence, improving overall market efficiency.

A thin market is one with low trading volume and few active participants. Thin prediction markets have wide bid-ask spreads, high price impact for individual trades, and less reliable price signals. Many prediction markets on niche topics are thin — which limits their usefulness as probability aggregators. Liquidity is the lifeblood of prediction market accuracy.

Implied probability is the probability of an outcome as implied by the current market price. In a binary prediction market, a contract trading at $0.65 implies a 65% probability that the event will occur. Implied probability is derived from prices rather than stated explicitly — it is what the market "believes," expressed as a number between 0 and 100%.

Gambity Prestige is Gambity's proprietary probability system — the first AI-native editorial probability engine in prediction markets journalism. Where other outlets report market prices, Gambity Prestige generates independent probability estimates from five analysts, each applying a distinct methodology: model discipline (Eleanor Ashworth), tail risk pricing (James Harrington), structural intelligence (Diana Pemberton), market positioning (Sebastian Montague), and legal framework analysis (Victoria Blackwell).