TL;DR
Categorical markets cover questions with more than two possible answers, like who will win an election among five candidates.
Key Points
✓Categorical markets list three or more outcome tokens; exactly one wins and the rest expire worthless.
✓The prices of all outcome tokens must sum to approximately $1.00, adjusted for any platform fees or overround.
✓Each outcome token price reflects the market's probability estimate for that specific outcome.
✓Categorical markets are common for elections, award winners, economic policy decisions, and sports tournament brackets.
✓A catch-all "Other" or "None of the above" outcome is often included to keep the outcome set exhaustive.
Structure and Pricing in Categorical Markets
A categorical market mints one outcome token for each listed possibility. Because the outcomes are mutually exclusive and collectively exhaustive, the sum of all token prices equals $1.00 in a frictionless market. For example, a market with four candidates might price them at $0.45, $0.30, $0.18, and $0.07, summing to $1.00. Each price is that outcome's Implied Probability. Trading works through the same Order Book mechanics as a Binary Market, but traders must choose which outcome token to buy or sell. Platforms often implement a Maker and Taker fee model, so the combined prices across all outcomes may sum to slightly more than $1.00 (an Overround). When a categorical market resolves, the Settlement process pays $1.00 per share to holders of the correct outcome and $0.00 to all others.
Categorical Markets vs. Binary and Scalar Formats
Categorical markets generalize the Binary Market by allowing more than two outcomes. A binary market is simply a categorical market with two choices. Unlike Scalar Market structures, categorical markets pay out nothing to incorrect outcome holders -- there is no proportional settlement. This winner-take-all dynamic means low-probability outcome tokens can trade at very cheap prices, creating opportunities for traders who identify Mispricing in tail outcomes. Managing Liquidity across many outcome tokens is harder than in binary markets, which is why platforms often use Automated Market Maker systems to seed initial depth. The Logarithmic Market Scoring Rule scoring rule is particularly well suited to categorical markets because it prices all outcomes simultaneously and adjusts coherently when one outcome's price changes.
Sources & References
Last updated: June 25, 2026
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