Turns split-conformal price forecasts on public EIA WTI crude data into probabilities for threshold questions like 'will WTI close above $X by date Y?', with backtests and a dated forward track record. Analysis only; it never touches a Kalshi account.
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Turns split-conformal price forecasts on public EIA WTI crude data into probabilities for threshold questions like 'will WTI close above $X by date Y?', with backtests and a dated forward track record. Analysis only; it never touches a Kalshi account. See the source for setup, usage and current status.
Tools: PythonPyTorchconformal prediction+1
Difficulty: advanced
Platforms: Kalshi
Turns split-conformal price forecasts on public EIA WTI crude data into probabilities for threshold questions like 'will WTI close above $X by date Y?', with backtests and a dated forward track record. Analysis only; it never touches a Kalshi account. It is listed under Data & analytics in this directory.
According to its source, it works with Kalshi.
The source lists: Python, PyTorch, conformal prediction, EIA data.
It was published by danielwork12121-lab. The public source is at github.com/danielwork12121-lab/kalshi-commodity-forecaster.
This directory rates it advanced (beginner, intermediate or advanced).
It had 0 GitHub stars as of Oct 15, 2026.
The repository was last updated on Oct 15, 2026, as checked on Oct 23, 2026. Check the source for current status.
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