Dataset and reproducibility code for a submitted research paper on forecasting Polymarket contract prices using related contracts in the same event. The public release separates a 303-event test set from the historical training pool, checks the archive checksum before unpacking, and replays the paper's non-LLM model metrics against archived reference results. It does not call any language-model API. Paper is under review; findings are the authors' own.
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Polymarket relational forecasting dataset and replay code (research paper) is an advanced-level data & analytics project for Polymarket, published by GR33N-WCL and built with Python, GitHub release dataset and unittest. Its source dates from Oct 23, 2026 and was last updated Oct 23, 2026. Data and analytics projects collect, store and visualize prediction-market data: historical prices, order books, trades and resolutions.
Dataset and reproducibility code for a submitted research paper on forecasting Polymarket contract prices using related contracts in the same event. The public release separates a 303-event test set from the historical training pool, checks the archive checksum before unpacking, and replays the paper's non-LLM model metrics against archived reference results. It does not call any language-model API. Paper is under review; findings are the authors' own. See the source for setup, usage and current status.
Tools: PythonGitHub release datasetunittest
Difficulty: advanced
Platforms: Polymarket
Dataset and reproducibility code for a submitted research paper on forecasting Polymarket contract prices using related contracts in the same event. The public release separates a 303-event test set from the historical training pool, checks the archive checksum before unpacking, and replays the paper's non-LLM model metrics against archived reference results. It does not call any language-model API. Paper is under review; findings are the authors' own. It is listed under Data & analytics in this directory.
According to its source, it works with Polymarket.
The source lists: Python, GitHub release dataset, unittest.
It was published by GR33N-WCL. The public source is at github.com/GR33N-WCL/polymarket-forecasting.
This directory rates it advanced (beginner, intermediate or advanced).
It had 0 GitHub stars as of Oct 24, 2026.
The repository was last updated on Oct 23, 2026, as checked on Oct 24, 2026. Check the source for current status.
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