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Wendi Li cd4ab998fb Update on Dynamic Benchmark (#1539) 
* move config file to benchmark_dynamic & switch default sim task model to GBDT

* Update benchmark_dynamic results

* Change the default value of alpha of DDG-DA
2023-06-03 08:42:24 +08:00
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README.md
DDG-DA paper code (#743)
2022-01-10 16:52:37 +08:00
rolling_benchmark.py
Update on Dynamic Benchmark (#1539)
2023-06-03 08:42:24 +08:00
workflow_config_lightgbm_Alpha158.yaml
Update on Dynamic Benchmark (#1539)
2023-06-03 08:42:24 +08:00
workflow_config_linear_Alpha158.yaml
Update on Dynamic Benchmark (#1539)
2023-06-03 08:42:24 +08:00

README.md

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_all

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 --model_type="gbdt" run_all