QTrade

QTrade is a simple, modular, and highly customizable trading interface capable of handling backtesting, reinforcement learning tasks.

With features ranging from traditional signal-based strategies to reinforcement learning-driven approaches, QTrade allows traders to focus on developing and testing strategies without the burden of implementation details.

Key Features

  • Backtesting: Efficient simulation of trading strategies on historical data.

  • Reinforcement Learning: Provides a highly customizable Gym environment for training and testing AI-driven trading agents.

How to Use

  1. Install QTrade
    Follow the instructions in the Installation Guide to set up QTrade in your Python environment.

  2. Explore Tutorials
    Learn to create strategies, backtest them, and use gym trading environment by following the Getting Started and the Trading Environment.

  3. API Reference
    Dive deeper into QTrade’s core components with the API Reference.

  4. Get Involved
    Contribute to the development or documentation through the links in the Development Section.

Installing

QTrade can be installed with pip:

$ pip install qtrade-lib

Alternatively, you can obtain the latest source code from GitHub:

$ git clone https://github.com/gguan/qtrade.git
$ cd qtrade
$ pip install .

To run the example code:

$ pip install -r examples/requirements.txt
$ python examples/simple_strategy.py

Usage

The User Guide is the place to learn how to use the library and accomplish common tasks. For more advanced customization, refer to the Customization Guide.

The Reference Documentation provides API-level documentation.