Releases: philippdubach/polymarket-microstructure
Releases · philippdubach/polymarket-microstructure
v1.0 — replication package for arXiv v1
First public release of the replication package for The Anatomy of a Decentralized Prediction Market: Microstructure Evidence from the Polymarket Order Book.
What's included
- Compiled paper (
paper/build/anatomy.pdf) - Full LaTeX source, figures, tables, and bibliography (
paper/) - Python package for orderbook replay, on-chain trade joining, microstructure measures, and stylized-fact computations (
polydata/) - End-to-end pipeline scripts (
scripts/) - pytest suite (
tests/) - 600-market pre-registered panel + per-market measure parquets (
data/panel.parquet,data/panel_metadata.parquet,data/panel_trade_measures.parquet,data/panel_quote/*) - Stylized-fact tables and figures (
artifacts/sf*.{parquet,png}), STRICT-vs-on-chain comparison panels, Glosten-Harris decomposition, sign-agreement robustness, and sample-step sensitivity grid - Locked pre-registration document (
docs/preregistration_plan3c.md) with the panel SHA-256
What's not included
- The 30-billion-event raw WebSocket archive (623.8 GB across 1,262 hourly Parquet files). Acquisition is described in §3.1 of the paper; the collector configuration is sufficient to reproduce.
- The 14 GB on-chain
OrderFilledscrape (242 slice Parquets). Reproducible viascripts/scrape_onchain_fills.pyagainst any Polygon archive RPC provider. - The 99 MB
clob_token_map.parquettoken mapping (over GitHub's 100 MB file limit). Regenerate withscripts/pull_token_ids_clob.py(~6 minutes).
Headlines
- 8 cross-sectional stylized facts on a pre-registered 600-market panel.
- Trade-direction inference from Polymarket's public WebSocket feed agrees with on-chain ground truth on only ~59% of comparable buckets.
- This translates to a 67% sign-flip rate on the effective half-spread and a 60% sign-flip rate on Kyle's λ between feed-inferred and on-chain estimates within the comparable subset of the top-100 panel.
A DOI is being minted for this release via Zenodo and will be added to the README + paper in a follow-up release.