Market Type
In prediction markets, market type determines how an event is modeled. Common types include binary markets, multiple-choice markets, and range-based markets.
The market type affects how participants trade. Binary markets concentrate belief into Yes/No prices, while multi-outcome markets distribute probability across several possibilities. Market type also shapes probability interpretation. In some formats, probabilities are independent per outcome, while in others they must sum to one.
Different market types behave differently under uncertainty. Some converge quickly, while others show prolonged dispersion across outcomes. Market type is critical context in prediction markets data. It explains why probability paths, volume patterns, and forecast stability differ across markets.
Choosing the right market type improves clarity and reduces disputes. Poorly matched types can distort signals or complicate resolution.
Why It Matters
Market type determines how belief is expressed and measured. Understanding it prevents misinterpretation of prediction markets data.
How do different market types affect probability interpretation in prediction markets?
Different market types encode probability in different ways. Binary markets express belief as a single probability per outcome. Multi-outcome markets spread belief across several possibilities. Analysts must adjust interpretation based on structure.
What market types are most common in prediction markets?
Binary markets are the most common because they are simple and easy to resolve. Multiple-choice markets are used for elections or ranked outcomes. Range markets are used for numeric forecasts like economic data. Each type serves a different forecasting need.
How does market type influence prediction markets data analysis?
Market type affects how probabilities are aggregated, compared, and evaluated. Analysts use different metrics depending on whether outcomes compete or stand alone. Misreading market type can lead to incorrect conclusions. Correct classification improves modeling and accuracy analysis.
Real-World Example
On Polymarket, many political questions use binary market types, while economic forecasts may use range-based market types to represent numeric outcomes.
Market Type and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides market metadata that identifies market type. Analysts use this information to correctly interpret prediction markets data, structure models, and compare markets across formats. Market type metadata ensures that probabilities and outcomes are analyzed consistently across prediction markets.