quant-py

A collection of Python-based trading strategies and analysis tools for algorithmic trading, designed to integrate seamlessly with QuantConnect's Lean engine. This repository focuses on Python scripts and libraries that can be integrated into various trading platforms, research pipelines, and backtesting frameworks. Contributions are welcome!

Table of Contents

• quant-py
  • Table of Contents
  • Introduction
  • Requirements
  • Installation
  • Usage
    • Strategies and Indicators
    • Integration with QuantConnect
  • Contributing
  • License

Introduction

quant-py provides ready-to-use Python scripts and modules that help traders and analysts build algorithmic trading systems, conduct technical analysis, and perform robust backtesting. By leveraging the flexibility and power of Python, you can easily integrate these tools into your existing workflow, whether it’s for live trading, paper trading, or historical market analysis.

Requirements

• Python 3.8+
• Dependencies:
  Common Python libraries such as pandas, numpy, matplotlib, ta (for technical analysis), and any other specified dependencies required by individual scripts.

Installation

1. Clone the Repository:

   git clone https://github.com/your-username/quant-python.git

2. Install Dependencies:

   cd quant-python
   pip install -r requirements.txt

3. Install Pre-Commit Hooks

   pre-commit install

4. Run Tests

   pytest tests/

5. Run Linting

   black .
   flake8 .
   isort .

Usage

Strategies and Indicators

Inside the strategies and indicators directories, you’ll find Python scripts and modules that you can run or import into your own projects.

Integration with QuantConnect

To integrate your strategies with QuantConnect, follow these steps:

1. Authenticate with QuantConnect

   lean login

2. Authenticate with QuantConnect

   lean cloud push "algorithms/(portfolio)/(strategy).py"

3. Run Backtests with QuantConnect Lean

lean backtest "algorithms/(portfolio)/(strategy).py"

Contributing

Contributions are welcome! If you have developed a Python strategy, indicator, or tool that you’d like to share:

1. Fork the repository and create a new branch.
2. Add your script along with a brief README in the appropriate directory.
3. Ensure your code is well-documented and follows the project’s coding standards.
4. Open a Pull Request, providing a clear description of what your contribution does and how it can be used.

License

This repository is released under the MIT License. You are free to use, modify, and distribute the scripts as long as you comply with the license terms.