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* Intermediate version * Fix yaml template & Successfully run rolling * Be compatible with benchmark * Get same results with previous linear model * Black formatting * Update black * Update the placeholder mechanism * Update CI * Update CI * Upgrade Black * Fix CI and simplify code * Fix CI * Move the data processing caching mechanism into utils. * Adjusting DDG-DA * Organize import
Introduction
This is the framework of periodically Rolling Retrain (RR) forecasting models. RR adapts to market dynamics by utilizing the up-to-date data periodically.
Run the Code
Users can try RR by running the following command:
python rolling_benchmark.py run
The default forecasting models are Linear. Users can choose other forecasting models by changing the model_type parameter.
For example, users can try LightGBM forecasting models by running the following command:
python rolling_benchmark.py --conf_path=workflow_config_lightgbm_Alpha158.yaml run