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A collection of Python-based trading strategies and analysis tools for algorithmic trading. This repository focuses on Python scripts and libraries that can be integrated into various trading platforms, research pipelines, and backtesting frameworks. Contributions are welcome!

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quant-py

A collection of Python-based trading strategies and analysis tools for algorithmic trading. 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

Introduction

quant-python 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

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.

Example (Running a Sample Strategy):

python strategies/sample_strategy.py

Customize parameters within the script or pass command-line arguments if supported.

Integration with Trading Platforms

Many Python-based trading frameworks (e.g., Backtrader, Zipline, or freqtrade) allow easy integration of custom strategies and indicators. Refer to the documentation of the specific platform to incorporate these scripts directly.

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.

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A collection of Python-based trading strategies and analysis tools for algorithmic trading. This repository focuses on Python scripts and libraries that can be integrated into various trading platforms, research pipelines, and backtesting frameworks. Contributions are welcome!

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