- DDPG.ipynb: Run this notebook to train and test DDPG-based portfolio as baseline
- QFPIS-1.ipynb: Run this notebook to train and test using one Quantum price level(QPL)
- QFPIS-2.ipynb: Run this notebook to train and test using two QPL
- backtest.ipynb: Run this notebook to do back test
- ./data: Contain the training and testing data
- ./environment: Contain the reinforcement learning enviroment:1)QF_env: enviroment for DDPG 2)QF_env_1: environment for QFPIS-1 3) environment for QFPIS-2
- ./model: Contain the trained models
- ./config/config.json: configure the training settings:
{
"episode": 100,
"max step": 1000,
"buffer size": 100000,
"batch size": 64,
"tau": 0.001,
"gamma": 0.99,
"actor learning rate": 0.0001,
"critic learning rate": 0.001,
"policy learning rate": 0.0001
}
- GPU/TPU Only
- Change Forex to Crypto Data, Top 20 Volume
- Training 2018-2020/ Testing 2021
- All data features training
- Up to 10 QPL instead 2
- Backtest
- Future: Implement on terminal. Compare with AlphaZero