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| Main Author: | |
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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2026
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.18700972 |
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Table of Contents:
- <p>Prediction markets aggregate probabilistic beliefs about future events through continuous trading, yet coherent, rapid probability shifts—particularly those preceding public announcements—may signal early information access by informed participants. We present Polyoracle, a system for detecting statistically significant shifts in binary prediction market probability streams using a four-factor composite signal score: KL divergence, log-volume weighting, historical signal-to-noise ratio (SNR), and trajectory consistency (TC). The system incorporates a two-stage pre-filter tuned to the structural characteristics of Polymarket—the dominant decentralized prediction market venue—and employs cooldown deduplication with a deterministic zone override. Empirical evaluation on 500 live events (8,219 markets, 105,653 snapshots over a 6-hour observation window) demonstrates that the composite score achieves a 130× dynamic range between genuine signals and the noise floor. A factor ablation study confirms that all four components are necessary: removing volume weighting introduces 88% more false positives; removing SNR eliminates 61% of genuine signals.</p>