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
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.
Referenced in 5 articles
Schema Research breaks down the five mechanisms powering every prediction market: LMSR, central limit order books, AMMs, bonding curves, and parimutuel pools. It explains the math behind each, their trade-offs, and how the strongest modern designs combine several mechanisms across different stages of a market's lifecycle.
Hossain, Andrade, Zang, and Chen introduce evidence markets, a new mechanism that generalizes prediction markets to handle two limitations: prices reveal what the crowd believes but not why, and markets require external resolution events with known dates. The system uses a Logarithmic Market Scoring Rule with dynamic liquidity that responds to evidence quality. The authors prove bounded platform loss, show evidence rewards scale with uncertainty, and demonstrate epsilon-dominant strategy incentive compatibility for truthful reporting. An LLM-as-a-Judge verification layer with staking handles operational deployment.
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.
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.
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.