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market scoring rules

A class of automated market maker mechanisms that subsidize trade by penalizing a market maker according to a proper scoring rule. Traders profit by moving prices closer to their beliefs, ensuring the market maker absorbs losses in exchange for eliciting honest probability estimates. LMSR is the most widely used instance.

Cluster: Mechanism Design

Related Concepts

combinatorial prediction markets — Prediction markets that allow participants to place bets on conditional events and Boolean combinations of base events, not just individual outcomes. By enabling richer betting vocabularies, they can elicit joint probability distributions over related events rather than only marginal probabilities.
LMSR (logarithmic market scoring rule) — An automated market maker that prices trades using a logarithmic cost function, guaranteeing bounded loss.
proper scoring rules — Incentive-compatible functions that reward forecasters most when they report their true beliefs honestly.
forecasting accuracy — Measuring how well predicted probabilities match actual outcome frequencies over many events.
multi-outcome markets — Prediction markets where an event is divided into multiple mutually exclusive outcome ranges (e.g., price brackets), each tradeable. Contrasts with binary markets that only ask yes/no questions.
liquidity provision — Supplying capital so traders can buy and sell positions without excessive price impact or delays.
order book — A list of outstanding buy and sell orders at various prices, showing available liquidity at each level.
binary contracts — Prediction market contracts that resolve to exactly one of two values, typically $1 (yes) or $0 (no), based on whether a specified event occurs. The binary structure eliminates ambiguity at resolution and enables direct probabilistic interpretation of prices.
market making — Continuously quoting bid and ask prices to facilitate trading, earning the spread while managing inventory risk.
adverse selection — Risk that counterparties trade because they have superior information, causing losses for the market maker.
bid-ask spread — The difference between the highest price a buyer will pay and the lowest price a seller will accept, representing the cost of immediacy for traders.

Articles about market scoring rules

Concepts/market scoring rules

market scoring rules

Mechanism Design

Referenced in 3 articles

Related Concepts

combinatorial prediction markets1 LMSR (logarithmic market scoring rule)1 proper scoring rules1 forecasting accuracy1 multi-outcome markets1 liquidity provision1 order book1 binary contracts1 market making1 adverse selection1 bid-ask spread1

Articles

Market Making for Prediction Markets: A Probability-Space Approach

XO Labs·Apr 17, 2026·III·Microstructure

Technical research on adapting the Avellaneda-Stoikov market-making framework for prediction markets. Classical models fail because prediction market prices are bounded probabilities (0 to 1) rather than unbounded asset prices, creating non-constant volatility and guaranteed terminal convergence. After a logit-space transformation lost $1,114 in backtest, XO Labs iterated to a probability-space engine with inventory-skewed spreads, volatility regime detection, and multi-outcome coordination that turned profitable at $453. Includes the full mathematical framework and open problems.

The World's Biggest Risk Event Just Exposed Prediction Markets' Biggest Gap

Jo Lim·Mar 24, 2026·II·Design

Uses the March 2026 Strait of Hormuz crisis to argue that binary order-book prediction markets hit an architectural ceiling when pricing granular, multi-outcome risk. Compares how traditional options solve this for tradable assets, then explains how automated market scoring rules (LMSR/CLMSR) offer protocol-native liquidity, coherent pricing, and capital efficiency for events without underlying assets. Walks through a concrete WTI crude oil scenario showing how scoring-rule markets reward precise thesis expression over simple directional bets.

Combinatorial Prediction Markets: An Experimental Study

Powell, Hanson, Laskey & Twardy·Sep 16, 2013·III·Design

Investigates combinatorial prediction markets, which extend the standard model to support forecasts on conditional events (e.g., A given B) and Boolean combinations of events rather than only base events. Reports experimental results comparing combinatorial versus flat market structures on forecasting accuracy and calibration. Co-authored by Robin Hanson, whose LMSR underpins most automated prediction markets.