A3C trading

Note: Sorry for misleading naming - please use A3Ctrading.py for training and testtrading.py for testing.

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

Configuration:

config.py

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

Dataset: download from GDrive

After setting

config.py

Environment:

trader_gym.py

OpenAI.gym-like environment class

Model:

A3C_class.py

This file is containing

AC_network

Worker

Test_Worker

Training:

A3C_training.py

Run this file, preferrable in

tmux

tensorboard_dir

model_dir

Testing:

A3C_testing.ipynb

Jupyter notebook

Cite as:

@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} }