Investing Algorithm Framework
Framework for developing, backtesting, and deploying automated trading algorithms and trading bots.
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⚡ Investing Algorithm Framework
🚀 Build. Backtest. Deploy. Quantitative Trading Strategies at Scale
The fastest way to go from trading idea to production-ready trading bot
> ⭐ **If you like this project, please consider [starring](https://github.com/coding-kitties/investing-algorithm-framework) it!** Your support helps us build better tools for the community.
💡 Why Investing Algorithm Framework?
Stop wasting time on boilerplate. The Investing Algorithm Framework handles all the heavy lifting:
✨ From Idea to Production — Write your strategy once, deploy everywhere 📊 Accurate Backtesting — Event-driven and vectorized engines for realistic results ⚡ Lightning Fast — Optimized for speed and efficiency 🔧 Extensible — Connect any exchange, broker, or data source 📈 Production Ready — Built for real money trading
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🔌 Plugins & Integrations
Extend your trading bot with powerful plugins:
| Plugin | Description |
|---|---|
| 🎯 [PyIndicators](https://github.com/coding-kitties/PyIndicators) | Technical analysis indicators for strategy development |
| 🏪 [Finterion Plugin](https://github.com/Finterion/finterion-investing-algorithm-framework-plugin) | Monetize & share your strategies with the public on Finterion's marketplace |
🌟 Powerful Features
| Feature | Description |
|---|---|
| 🐍 Python 3.10+ | Cross-platform support for Windows, macOS, and Linux |
| ⚙️ Event-Driven Backtest | Accurate, realistic backtesting with event-driven architecture |
| ⚡ Vectorized Backtest | Lightning-fast signal research and prototyping |
| 📊 Advanced Metrics | CAGR, Sharpe ratio, max drawdown, win rate, and 50+ more metrics |
| 📈 Backtest Reports | Generate detailed, comparison-ready reports |
| 🎯 Statistical Testing | Permutation testing for strategy significance evaluation |
| 💱 Live Trading | Real-time execution across multiple exchanges (via CCXT) |
| 💼 Portfolio Management | Full position and trade management with persistence |
| 📉 Market Data | OHLCV, tickers, custom data — Polars & Pandas native |
| 🔗 Data Integrations | PyIndicators, multiple data sources, custom providers |
| ☁️ Cloud Deployment | Azure Functions, AWS Lambda, and more |
| 🌐 Web API | REST API for bot interaction and monitoring |
| 🧩 Fully Extensible | Custom strategies, data providers, order executors |
| 🏗️ Modular Design | Build with reusable, composable components |
🚀 Quickstart
📦 Installation
Don't lose this
Three weeks from now, you'll want Investing Algorithm Framework again. Will you remember where to find it?
Save it to your library and the next time you need Investing Algorithm Framework, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
This plugs directly into your AI and gives it new abilities it didn't have before. Framework for developing, backtesting, and deploying automated trading algorithms and trading bots. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
What's New
Imported from GitHub
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