By Ahmed Mahrous, Roberto Di Pietro
Using a near-census of 802,863 resolved markets listed on Polymarket between January 2023 and May 2026, and only information available at listing (the market's title and description, named resolution source, and contract metadata), we predict lifetime trading volume and whether settlement is later disputed. Contract information predicts trading volume well (out-of-sample R^2 = 0.747 for log volume), and most of the signal is interpretable: market topic provides the largest gain (+0.289 R^2 over a 0.220 contract-feature baseline), wording and resolution-rule design add smaller but measurable improvements (+0.027 combined), and neural text models add little beyond the interpretable features. This performance does not survive a period of platform change coinciding with a shift in listing formats: accuracy in predicting whether a market reaches $1,000 falls from AUC 0.940 under same-period evaluation to 0.577 when training on past quarters and testing on later ones. The loss concentrates in markets whose question forms were absent from training (76.9% of test markets; on familiar forms the model still reaches 0.778), and a decomposition attributes more of it to a changed relationship between contract characteristics and demand than to an outdated mapping from text to features. Dispute predictors are more stable but less precise: launch-time features rank dispute risk far better than chance (AUC 0.78), yet at a 0.31% base rate precision is too low for case-by-case prediction (average precision 0.012), so the scores suit ranking groups of markets rather than forecasting individual disputes.
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