Note: Sorry for misleading naming - please use A3C_trading.py for training and test_trading.py for testing.

Trading with recurrent actor-critic reinforcement learning - check paper and more detailed old report

This file contains all the pathes and gloabal variables to be set up

After setting config.py please run this file to download and preprocess the data need for training and evaluation

OpenAI.gym-like environment class

This file is containing AC_network, Worker and Test_Worker classes

Run this file, preferrable in tmux. During training it will create files in tensorboard_dir and in model_dir

Jupyter notebook contains all for picturing

@article{ponomarev2019using, title={Using Reinforcement Learning in the Algorithmic Trading Problem}, author={Ponomarev, ES and Oseledets, IV and Cichocki, AS}, journal={Journal of Communications Technology and Electronics}, volume={64}, number={12}, pages={1450--1457}, year={2019}, publisher={Springer} }