Information Leakage at Population Scale: An Evaluation of the Polymarket Insider-Relevant Subpopulation, 2020–2026

Battle Count: 51

Moderately relevant to quantitative trading. The paper focuses on prediction markets (Polymarket) rather than traditional equity/futures markets, but addresses core quantitative finance concerns: informed trading detection, market microstructure, information asymmetry, and regulatory compliance. The ILSdl framework provides a market-level diagnostic complementary to wallet-level and account-level methods. The hazard-decay baseline correction methodology has transferable relevance to any deadline-contract or binary-outcome pricing context. The paper's primary contribution is methodological (scope discovery, baseline correction) rather than directly actionable for trading strategy development. The 0.7% coverage rate and 12-market anchor-robust sample limit immediate practical deployment. More relevant to market surveillance, regulatory enforcement, and platform integrity than to alpha generation or portfolio construction.

High implementation complexity due to: (1) multi-stage pipeline with sequential filters (resolution-typology classification, deadline-NO exclusion, T_event recovery, CLOB coverage, scope conditions); (2) LLM-assisted T_event recovery requiring multi-tier provider cascade with confidence calibration; (3) Weibull/exponential/lognormal MLE fitting with parametric-bootstrap KS testing; (4) hazard-decay baseline correction requiring survival-function computation per market; (5) anchor-sensitivity matrix computation across four short-window variants; (6) bootstrap CI computation at trade level (B=500-1000); (7) resolution-typology classifier requiring keyword-based taxonomy with regulatory sub-categorization; (8) CLOB price data retrieval and coverage verification. However, the pipeline is modular, well-documented, and code is publicly released. The LLM cascade cost is minimal (~$1.20 for population run). Main complexity lies in the interplay between classification, recovery, and scoring stages rather than in any single algorithmic component.

Exceptional reproducibility: full pipeline code released at https://github.com/ForesightFlow/platform (tag v1.1-paper3a-rev1, MIT license); population-scale dataset released as polymarket-deadline-ils-v3 at https://github.com/ForesightFlow/datasets (CC-BY-4.0); FFIC inventory and resolution-typology dataset also released; fixed random seed 20260430 for all bootstrap operations; snapshot cutoff date documented (2026-04-27); LLM provider cascade, prompt templates, confidence calibration, and per-market provenance records all documented; reproducibility checklist provided in Appendix C.