Empirical Evaluation of Deadline-Resolved Information Leakage on Documented Polymarket Insider Cases
Abstract
This paper reports an end-to-end empirical evaluation of the deadline-Information Leakage Score (ILS-dl) extension introduced in the companion methodology paper. The deadline-ILS extends the original ILS to deadline-resolved prediction-market contracts, the dominant structural form of publicly documented insider trading on Polymarket. We anchor the evaluation in the 2026 U.S.-Iran conflict cluster of the ForesightFlow Insider Cases (FFIC) inventory, the largest documented deadline cluster. The evaluation has four parts: per-category exponential-hazard estimation, a single-case ILS-dl computation, cross-market wallet analysis, and methodological refinements. Hazard-rate estimation produces an adequate exponential fit for military-geopolitics markets (KS p = 0.426, half-life 2.9 days, n = 18) and a preliminary fit for corporate-disclosure markets (n = 5). The regulatory-decision category is rejected as bimodal (p = 0.023). On the largest applicable FFIC contract ("US forces enter Iran by April 30," $269M volume), the article-derived public-event timestamp yields ILS-dl = +0.113 versus a resolution-anchored proxy value of -0.331: a 0.444 shift in magnitude on opposite sides of zero, demonstrating that the extension distinguishes signal from proxy artefact. Pre-event drift is mild, and short-window variants (30-min, 2-hour) are exactly zero. Cross-market wallet analysis identifies 332 wallets active in both major Iran-cluster markets, but the available trade history covers only the resolution-settlement window. v2 (May 2026) corrects the hazard fit to the full Tier-3 population; the v1 estimate lies inside the v2 95% CI.
Cite
@article{arxiv.2605.02286,
title = {Empirical Evaluation of Deadline-Resolved Information Leakage on Documented Polymarket Insider Cases},
author = {Maksym Nechepurenko},
journal= {arXiv preprint arXiv:2605.02286},
year = {2026}
}
Comments
v2 (May 2026): hazard-rate fits updated to full Tier-3 population (n=18 for military_geopolitics, was n=9). v1 estimate lies inside v2 95% CI. Esports taxonomy correction applied. No conclusion changes. 11 pages, 6 tables