Introduction
Welcome to the Investing Algorithm Framework documentation!
The framework allows you to leverage python to build complex bots to trade. The framework aims to implement orders, position, trades and portfolio management. Also, the framework aims to support multiple data sources, exchanges and brokers. Next to that backtesting and live trading is supported.
🔧 Core Features​
- Backtesting: Test strategies using historical market data.
- Deployment: Deploy bots to platforms like Azure and AWS.
- Order management: Use stop-loss, take-profit, and other complex order types.
- Position management: Automatically handle position logic across multiple strategies.
- Trades management: Automatically handle trade logic across multiple strategies.
- Performance evaluation: Track, analyze, and attribute your trading performance.
- Portfolio configuration: Manage your portfolio and market credentials.
- Market data sources: Integrate ticker, OHLCV, and order book from different markets and exchanges.
- Custom data sources: Create custom data sources for your trading strategies.
- Trading strategies: Implement and register your trading strategies.
- Deployment: Deploy your trading bot to various platforms like Azure Functions, AWS Lambda, or run it locally.
Getting Started​
The Investing Algorithm Framework is a Python framework for developing and backtesting investing algorithms.
You might also want to check the quick start guide directly which outlines the fundamentals of creating a simple trading bot.
After that, you can read the basics to learn more about the framework.
What you'll need​
Installation​
You can install the framework using the following command:
pip install investing-algorithm-framework
Contributing​
If you want to contribute to the framework, please read the contributing guide.
Issues​
If you find a bug or have a feature request, please create an issue on GitHub.