QuantJourney Framework

Introduction

Welcome to the QuantJourney Framework! This comprehensive investing package is designed to streamline your access to financial data, simplify data processing, and enhance data visualization for quantitative analysis and backtesting of financial investments.

Key Features

• Custom Algorithm Development
• Risk Management Strategies
• Backtesting and Optimization
• Real-World Applications
• Community and Support

Installation

To install the QuantJourney client library, simply run:

pip install quantjourney

Usage

Here's a quick example of how to use the QuantJourney client:

import asyncio
from quantjourney import QuantJourney

async def main():
    qj = QuantJourney()
    qj.authenticate("your_username", "your_password")
    df = qj.get_ohlcv("AAPL", "NASDAQ", "2023-01-01", "2023-12-31")
    print(df)

asyncio.run(main())

Documentation

For more detailed information on using the QuantJourney Framework, please refer to our Wiki.

Prerequisites

• Python 3.7 or higher
• Basic understanding of financial markets and quantitative analysis

Contributing

We welcome contributions! Please see our Contributing Guide for more details.

Issues

If you encounter any issues, please report them on our Issue Tracker.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any questions or support, please email contact@quantjourney.pro.

Happy coding and investing!