OpenAI Gym for Trading With DQN OpenAI Baseline

An example of Reinforcement Trading using OpenAI Baseline.

This is made by Adrian Portabales based on Mr. Peter Henry and inspired by Tito Ingargiola, hackthemarket.

There are some improvements in code:

• 4 States:

  • 0 = Holding the trade. Only recalculate reward
  • 1 = Buy
  • 2 = Sell
  • 3 = Close position

  The bot only operates with one open position at the same time.

• At the end of every episode, a test is run. The size of train and test set in train_split variable

• Now you can add more features (like indicators, momentums etc) with feature_engineering module.

Tutorial

https://github.com/AdrianP-/gym_trading/blob/master/Baseline%20DQN%20Gym_Trading%20Tutorial.ipynb

References

OpenAI Baseline: https://github.com/openai/baselines

Gym_trading by Peter Henry: https://github.com/Henry-bee/gym_trading/

Also, good thougths in Trading and Q learning: https://github.com/savourylie/Stock-Price-Forecaster

Thanks to all!

Requirements

Requirements: -Pandas -Matplotlib -Numpy -gym -TA-Lib -baselines

This framework was built in Python 3.5.2

Contact

Twitter: @porta4k

Mail: [email protected]