/R2-SAC

a novel framework for stock portfolio trading that employs a 'Relaxation and Refinement' strategy to boost the Soft Actor-Critic (SAC) agent

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

R2-SAC

a novel framework for stock portfolio trading that employs a 'Relaxation and Refinement' strategy to boost the Soft Actor-Critic (SAC) agent

  1. PLEASE NOTE: Find the basic version of the Hawkes scripts, which can be founded in the https://github.com/HongtengXu/PoPPy/

  2. TCN_GAT_zz1000.py is the training program for TCN and GAT, which introduced the scripts model.py for TCN model and gat.py for GAT model.

  3. SAC_zz1000.py is the traning program for SAC model, which introduced the scripts StockEnv_zz1000.py for trading environment and StcokAgent.py for agent model.

  4. To run R2-SAC, you should rewrite the test procedure for your trading strategy and get the hawkes scripts from the https://github.com/HongtengXu/PoPPy/.

  5. For some suggetions, we built AI4QTrading-patch-1 branch to help reproducing the strategy. And for commercial reason, some data need to be downloaded from the public data source.