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ai-finance-cookbooks

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This repository contains a curated collection of notebooks and lightweight applications demonstrating Generative AI in financial analysis and investment research.

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# Gen AI in Finance Cookbook

![Python](https://img.shields.io/badge/Python-3.9%2B-blue)
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://drive.google.com/drive/folders/10_LOo0zek_IPiqdHZzy2iVHoiKj4vxJO?usp=sharing)
[![LinkedIn](https://img.shields.io/badge/LinkedIn-Profile-blue?logo=linkedin)](https://linkedin.com/in/yakshb)
[![Twitter/X](https://img.shields.io/badge/Twitter-Profile-blue?logo=twitter)](https://x.com/yaksh_birla)

## 🚀 Overview
This repository is a collection of Jupyter and Google Colab notebooks demonstrating the application of LLMs, AI Agents, RAG and other frameworks in financial analysis and research. Each notebook is designed well-documented, and ready to use, showcasing practical applications of modern AI techniques in finance.

## 📚 Featured Notebooks

### Claude & FMP AI Agents
- [**Stock/Investment Analyst AI Agent**](notebooks/ai-agents/Claude-FMP-Stock-Analyst_(Starter).ipynb)
  - Analyzes key financial metrics and statements for any publicly-listed stock using Claude Agents
  - Tool calling, function calling and parallel operations enabled
  
- [**AI Agent Analysis of Politicians' Stock Trades**](notebooks/ai-agents/Claude-FMP-Political-Trades-Tracker_(Starter).ipynb)
  - Analyzes key stocks that are being traded by politicians

- [**LLM-Enhanced Commodities Research and Trading Signals**](notebooks/ai-agents/Claude-FMP-Commodities-Tracker_(Starter).ipynb)
  - Analyzes key commodities with user-driven insights against global news using Claude Agents

- [**Evaluating Financial Insights Across LLMs**](notebooks/ai-agents/Anthropic/Claude-OAI-Commodities-Eval-Framework.ipynb)
  - Utilizes the commodities research framework to evaluate Claude Sonnett 3.5 against OpenAI's GPT 4o
  - Framework can be used across different model providers and financial asset types (stocks, bonds, crypto)

## 🚗 Getting Started
1. Click the "Open in Colab" badge on any notebook
2. Make a copy of the notebook in your Google Drive
3. Run the setup cell to install required packages
4. Follow the markdown instructions in each notebook

## 🔍 Project Structure
```
notebooks/
├── ai_agents/      # AI Agent Implementation notebooks
├── multimodal-ai/ # Multimodal AI notebooks
└── techniques/     # Techniques for portfolio optimization, backtesting, sentiment analysis, etc.
```

## 📖 Usage Guidelines
- All notebooks are self-contained with required package installation
- Data is sourced from public APIs and datasets
- Examples use real market data where possible
- Clear documentation and comments throughout

## 🤝 Connect & Follow
- [Personal Website](https://yakshb.com) - Portfolio and blog posts
- [LinkedIn Profile](https://linkedin.com/in/yakshb) 
- [Twitter/X Profile](https://x.com/yaksh_birla)

## 🎯 Future Updates
- Crypto market analysis notebooks
- ESG scoring implementations
- Real-time market monitoring
- Prediction and backtesting agents

## 📝 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## ⭐ Support
If you find these notebooks helpful, please star the repository and share it with others!

---
*Disclaimer: These notebooks are for educational purposes only. Always do your own research and due diligence before making investment decisions.*

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