Prediction Markets: Limit Order Books, Information Aggregation, and Settlement Risk
Price formation, information aggregation, and settlement uncertainty in prediction markets
Ongoing work.
I study how prediction-market prices form and what they reveal about the events being traded. This research connects two aspects of these markets: how trading aggregates information, and how uncertainty about settlement affects the interpretation of prices.
Limit order books and information aggregation
I develop models of limit order books for binary prediction contracts, where traders and liquidity providers differ in their beliefs, wealth, and risk preferences. Traders choose how much to buy or sell against the available book, while liquidity providers choose the prices and quantities they offer.
The goal is to understand how these individual decisions shape liquidity, price formation, and learning from order flow. I examine when observed trades reveal private information, how differences in wealth and risk preferences complicate that inference, and how the structure of the order book affects information aggregation over time.
Settlement uncertainty
A prediction contract pays according to its settlement rules, which can introduce uncertainty beyond the underlying event itself. I model the distinction between an event’s outcome and the contract’s eventual payoff, allowing settlement to be clean or contested.
Using stochastic models and filtering, I study how public information updates beliefs about both the event and its settlement. This framework characterizes the gap between event probabilities and expected contract payoffs, and examines why prices can continue to move after the event has occurred but before settlement is final.