Paper: arXiv 2605.11640
Authors: Maksym Nechepurenko
Abstract
Prediction markets cannot exist without market makers, arbitrageurs, and other non-retail liquidity providers, yet the supply-side microstructure of Polymarket-class venues has not been characterized at on-chain pseudonymous-address scale. This paper studies non-retail participation on Polymarket using an empirical run on the PMXT v2 archive over 2026-04-21 through 2026-04-27 (13,356,931 OrderFilled events; 77,204 addresses with five+ fills; 43,116 markets). We report three findings. First, Polymarket’s off-chain CLOB architecture renders address-level quote-lifecycle attribution permanently unavailable: OrderPlaced and OrderCancelled events are off-chain and absent from public archives, so quote-intensity, two-sided-ratio, and posted-spread features cannot be built at address level. We document this as a structural validity-gate failure (G-QUOTE-LIFE universal fail) and restrict analysis to a six-feature fill-side vector. Second, density-based clustering (DBSCAN, fifteen sensitivity configurations) on the fill-side vector produces a single dense cluster with zero noise: fill-side behavior in the empirical window is uni-modal under the six-feature vector, contradicting the pre-registered hypothesis of four-to-five separable archetypes. Third, robust retail vs non-retail separation is achievable through clustering-independent feature-tier stratification: whale-tier, high-frequency-operator, and power-trader tiers jointly hold 81.4% of total notional across 12.6% of addresses. Address-level market-making and liquidity-provision claims are withdrawn per the G-QUOTE-LIFE failure; spoof-by-non-fill manipulation detection is downgraded to market-level book diagnostics. A privacy-respecting derived-dataset deposit accompanies the paper as Bundle 3 of the PMXT family. Fourth paper in a four-paper programme on event-linked perpetuals and leveraged prediction-market microstructure.
Complexity vs Empirical Score
- Math Complexity: 3.5/10
- Empirical Rigor: 8.5/10
- Quadrant: Street Traders — practical and empirical, lighter on theory
Why this score: The paper is highly focused on large-scale data processing, on-chain event log extraction, and empirical microstructure diagnostics rather than advanced mathematical derivations. While it employs clustering methodologies, the core contribution is an heavy-lifting empirical audit of trading behaviors and market participant stratification.
Research Flowchart
flowchart TD
A[<b>Goal:</b> Characterize non-retail microstructure on Polymarket] --> B[<b>Data:</b> PMXT v2 Archive (13.3M OrderFilled events)]
B --> C[<b>Process:</b> Feature Engineering & G-QUOTE-LIFE Evaluation]
C --> D{<b>Audit:</b> Structural Validity Gate}
D -- Fail --> E[<b>Finding 1:</b> Quote-attribution unavailable; 6-feature vector restriction]
D -- Pass --> F[<b>Findings 2 & 3:</b> Uni-modal fill-side distribution & Tier-based stratification (81.4% notional concentration)]
F --> G[<b>Outcome:</b> Derived-dataset deposit & revised market-level diagnostics]
Cited References (12)
- Stock-Price Manipulation (1992)
- A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise (1996)
- Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders (1985)
- Empirical Market Microstructure (2007)
- Continuous Auctions and Insider Trading (1985)
- Interpreting the Predictions of Prediction Markets (2006)
- Resolution-Aware Perpetual Futures on Binary Prediction Markets (2026) — link
- A Taxonomy of Event-Linked Perpetual Futures (2026) — link
and 4 more
0 of 12 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.