Price as Focal Point: Prediction Markets,Conditional Reflexivity, and the Politics of Common Knowledge

TL;DR

This paper examines prediction markets as coordination tools influencing behavior and politics, emphasizing their social and behavioral effects over mere forecasting accuracy, with evidence from the 2024 U.S. election.

Contribution

It introduces the Signal Credibility Index (SCI) to assess when market signals influence behavior, shifting focus from accuracy to social and political coordination effects.

Findings

Market signals depend on persistence, trader diversity, and consensus.

Superficial similarities in shocks can lead to different behavioral effects.

Visible markets may lack epistemic robustness despite high visibility.

Abstract

Prediction markets are widely treated as forecasting devices that reveal collective expectations about uncertain futures. This article argues that under specifiable conditions they also function as coordination mechanisms: public probabilities that organize the behavior of voters, donors, journalists, traders, and institutions in ways that can be self-fulfilling or self-defeating. Most existing work asks whether prediction markets forecast accurately; this paper asks whether accurate forecasting is even the right criterion for a market that has become a public coordination device. Drawing on transaction-level evidence from the 2024 U.S. presidential election, we show that the social force of a market signal depends less on its size than on its persistence, the breadth of responding trader types, and cross-platform consensus. We introduce a Signal Credibility Index (SCI) -- combining the variance ratio VR(6), a two-sidedness diagnostic, and a trader-concentration adjustment -- as a microstructure-grounded criterion for predicting when price moves acquire behavioral traction. Applied to three major 2024 political shocks, the framework reveals that superficially similar events generated qualitatively distinct signal types with different implications for elite coordination. A cross-platform comparison establishes a systematic decoupling of social authority from epistemic robustness: the most visible market produced the least accurate forecasts. The framework carries direct implications for regulating prediction markets as democratic information infrastructure.