AlgoTrading101/Conformal-Prediction-MAPIE-Algotrading101
Conformal Prediction - A Practical Guide with MAPIE
This project helps quantitative traders and financial analysts incorporate reliable uncertainty measures into their predictive models. It takes your existing market data and model outputs to generate prediction intervals with guaranteed accuracy. This allows you to understand the risk associated with each forecast, making it especially useful for algorithmic trading strategies.
No commits in the last 6 months.
Use this if you need to quantify the uncertainty of your financial predictions and avoid overconfidence in high-stakes trading decisions.
Not ideal if your primary goal is simply to achieve the highest possible point-prediction accuracy without concern for quantifying forecast uncertainty.
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Jupyter Notebook
License
MIT
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Last pushed
Feb 18, 2024
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