qlib/examples/rl

This folder contains a simple example of how to run Qlib RL. It contains:

.
├── experiment_config
│   ├── backtest       # Backtest config
│   └── training       # Training config
├── README.md          # Readme (the current file)
└── scripts            # Scripts for data pre-processing

Data preparation

Use AzCopy to download data:

azcopy copy https://qlibpublic.blob.core.windows.net/data/rl/qlib_rl_example_data ./ --recursive
mv qlib_rl_example_data data

The downloaded data will be placed at ./data. The original data are in data/csv. To create all data needed by the case, run:

bash scripts/data_pipeline.sh

After the execution finishes, the data/ directory should be like:

data
├── backtest_orders.csv
├── bin
├── csv
├── pickle
├── pickle_dataframe
└── training_order_split

Run training

Run:

python ../../qlib/rl/contrib/train_onpolicy.py --config_path ./experiment_config/training/config.yml

After training, checkpoints will be stored under checkpoints/.

Run backtest

python ../../qlib/rl/contrib/backtest.py --config_path ./experiment_config/backtest/config.py

The backtest workflow will use the trained model in checkpoints/. The backtest summary can be found in outputs/.