Paper: arXiv 2610.06412

Authors: Philipp D. Dubach

Abstract

Trade-sign errors can change measured trading costs even when classification accuracy is high. We validate the side of Polymarket’s public trade prints against the taker leg of each print’s on-chain settlement. On twelve selected days between April and August 2026, spanning both exchange generations, 92.1% to 100.0% of prints match a settled taker leg, with exact side and token agreement on all 24.5 million matched pairs. Mint-and-merge settlement makes that taker leg essential: pooling maker and taker legs changes the measured buy share. Signing the full cached tape before settlement selection yields 16.6 million prints signed by every rule; equal-day balanced accuracy is 0.942 for Lee-Ready, 0.768 for the tick test and 0.670 for retrospective bulk volume classification. On 16.4 million identical eligible fills, Lee-Ready raises effective spread by 0.429 cents per share under equal-fill weights; its realised-spread difference is -0.209 cents. Under share-volume weights, taker five-minute midpoint impact is 0.689 cents, while tick and bulk classifications give -0.374 and -0.119 cents. That aggregate sign reversal disappears when tied print rows are excluded. Distortion depends on error-weighted signed outcomes, sample selection and weighting. Receipt-time ordering and unobserved future-quote age limit these delivered-quote accounting quantities; they do not identify causal impact or private information. Supporting venue and collector analyses provide descriptive diagnostics.

Complexity vs Empirical Score

  • Math Complexity: 3.0/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: This paper demonstrates strong empirical rigor through extensive data validation and statistical analysis of trade direction. While the mathematical complexity is moderate, the novel application of blockchain ground truth to a critical microstructure problem is highly valuable.

Research Flowchart

  flowchart TD
    A[Research Goal: Measure Trade Direction in a Prediction Market] --> B{Key Methodology Steps};
    B --> C[Validate Polymarket Trade Prints vs. On-Chain Settlement];
    C --> D[Apply Trade Classification Algorithms (Lee-Ready, Tick Test, Bulk Volume)];
    D --> E[Data/Inputs: Polymarket Public Trade Prints, On-Chain Settlement Data, Cached Tapes];
    E --> F{Computational Processes: Matching, Classification, Spread & Impact Calculation, Error Analysis};
    F --> G[Key Findings: High Print-Settlement Match Rate, Trade-Sign Errors Impact Trading Costs, Algorithm Performance Differs];
    G --> H[Outcomes: Quantified Impact of Sign Errors on Effective Spread and Midpoint Impact, Importance of Settlement Ground Truth];