We provide tutorials for simple tasks.
We demonstrate a full pipeline of a stock trading task in NeurIPS 2018 paper.
In the directory ./Stock_NeurIPS2018, the three notebooks: Stock_NeurIPS2018_1_Data.ipynb, Stock_NeurIPS2018_2_Train.ipynb, Stock_NeurIPS2018_3_Backtest.ipynb show a workflow of applying ML/RL in algorithmic trading.
Once you are familiar with the above three files, feel free to run the notebook Stock_NeurIPS2018_SB3.ipynb and Stock_NeurIPS2018_ElegantRL.ipynb that follow a similar process to play with different RL libraries.
The notebook FinRL_PortfolioAllocation_NeurIPS_2020.ipynb shows how to use FinRL do the classic task of portfolio allocation.
FinRL_PortfolioAllocation_NeurIPS_2020.py is a single python file that contains all the codes.
China_A_share_market_tushare.ipynb demonstrates how to trade on China A share market. We connect with the Tushare library to fetch data from China A share market.
Stock_Fundamental.ipynb shows the process of training a deep reinforcement learning agent with companies’ fundamental indicators.
China_A_share_market_tushare.py is a single python file that contains all the codes.
ForexTrading_Demo.ipynb gives the process of foreign exchange market trading.
ForexTrading_Demo.py is a single python file that contains all the codes.