Gym Trading Env is an Gymnasium environment for simulating stocks and training Reinforcement Learning (RL) trading agents. It was designed to be fast and customizable for easy RL trading algorithms implementation.

| Documentation |

Key features

This package aims to greatly simplify the research phase by offering :

• Easy and quick download technical data on several exchanges
• A simple and fast environment for the user and the AI, but which allows complex operations (Short, Margin trading).
• A high performance rendering (can display several hundred thousand candles simultaneously), customizable to visualize the actions of its agent and its results.

Installation

Gym Trading Env supports Python 3.9+ on Windows, Mac, and Linux. You can install it using pip:

Or using git :

git clone https://github.com/donghui-0126/Gym-Trading-Env.git

tensorboard --logdir ./pistar/log

Documentation available here

Repository 개선점

• 한글 주석 / 코드 주석 추가
• fiat borrow fee / asset borrow fee 구분
• reward function 추가
• Stable-Baseline3를 사용한 실습파일 추가 (PISTAR)