Timely Information from Prediction Markets

TL;DR

This paper explores how prediction markets can be designed to efficiently aggregate timely information from strategic agents, balancing speed, cost, and truthfulness to maximize social welfare.

Contribution

It introduces mechanisms that incentivize agents to acquire and report information at optimal times, considering different value decay models and ensuring truthful participation.

Findings

Markets can be optimized for timely information aggregation.

Mechanisms incentivize appropriate effort levels from agents.

Simulations validate theoretical results.

Abstract

Prediction markets are powerful tools to elicit and aggregate beliefs from strategic agents. However, in current prediction markets, agents may exhaust the social welfare by competing to be the first to update the market. We initiate the study of the trade-off between how quickly information is aggregated by the market, and how much this information costs. We design markets to aggregate timely information from strategic agents to maximize social welfare. To this end, the market must incentivize agents to invest the correct amount of effort to acquire information: quickly enough to be useful, but not faster (and more expensively) than necessary. The market also must ensure that agents report their information truthfully and on time. We consider two settings: in the first, information is only valuable before a deadline; in the second, the value of information decreases as time passes. We use both theorems and simulations to demonstrate the mechanisms.