Semantic Non-Fungibility and Violations of the Law of One Price in Prediction Markets

TL;DR

Prediction markets face semantic non-fungibility issues causing price deviations across platforms, which hinder effective information aggregation and create arbitrage opportunities, highlighting the need for explicit event identity alignment.

Contribution

We introduce a semantic alignment framework for cross-platform event identity, construct a validated dataset, and demonstrate its importance in reducing price deviations and arbitrage.

Findings

6% of events are listed across multiple platforms

Semantically equivalent markets show 2-4% price deviations

Structural frictions, not information, drive arbitrage opportunities

Abstract

Prediction markets are designed to aggregate dispersed information about future events, yet today's ecosystem is fragmented across heterogeneous operator-run platforms and blockchain-based protocols that independently list economically identical events. In the absence of a shared notion of event identity, liquidity fails to pool across venues, arbitrage becomes capital-intensive or unenforceable, and prices systematically violate the Law of One Price. As a result, market prices reflect platform-local beliefs rather than a single, globally aggregated probability, undermining the core information-aggregation function of prediction markets. We address this gap by introducing a semantic alignment framework that makes cross-platform event identity explicit through joint analysis of natural-language descriptions, resolution semantics, and temporal scope. Applying this framework, we construct the first human-validated, cross-platform dataset of aligned prediction markets, covering over 100 000 events across ten major venues from 2018 to 2025. Using this dataset, we show that roughly 6% of all events are concurrently listed across platforms and that semantically equivalent markets exhibit persistent execution-aware price deviations of 2-4% on average, even in highly liquid and information-rich settings. These mispricings give rise to persistent cross-platform arbitrage opportunities driven by structural frictions rather than informational disagreement. Overall, our results demonstrate that semantic non-fungibility is a fundamental barrier to price convergence, and that resolving event identity is a prerequisite for prediction markets to aggregate information at a global scale.