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Automated Stock Trading: An Ensemble Strategy

​ A Reproducibility Study of Hongyang Yang et al. paper.

Prerequisites

  1. python 3.7
  2. ubuntu or WSL

How to Setup

You'll need to install python 3.7 to use our code. Below you'll find a way to install python 3.7 with venv. This will allow you to create a specified virtual environment for this project called rl_env.

sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt update
sudo apt upgrade -y
sudo apt install python3.7 python3.7-dev python3.7-venv
sudo apt install libopenmpi-dev
python3 -m venv rl_env
source rl_env/bin/activate

When you are finished, you can now install the required python libraries for this project:

pip install -r requirements.txt
pip install git+https://github.com/AI4Finance-LLC/FinRL-Library.git

​ :warning:FinRL only works on ubuntu like systems.:warning:

How to run the script

The file auteurs.json in the folder configs has all the parameters used in the original experiment of the paper. To run it you must copy the command below:

python3 preprocessandtrainenv.py --ConfigName=auteurs

Different trading environments

It is possible to run the algorithms on the following stock groups: dow_30, nas_100, sp_500, faang, crypto (BTC, ETH, LTC, BCH Vs USD), memes (ETH, LTC, BCH, DOGE, SHIB, UNI3 Vs BTC).

Authors

Jean-Charles LAYOUN. Can be contacted at [email protected].
Alexis ROGER. Can be contacted at [email protected].

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A Reproducibility Study of Hongyang Yang et al.'s paper.

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