AutoQuant: Your Financial Research Agent 🧠📈

AutoQuant is your intelligent assistant for stock research automation. It helps you quickly analyze public companies, generate backtested trade setups, and even export findings as PDF deliverables — all powered by LLMs + LangChain.

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🚀 Features

• SmartSwingSignal
  Combines 50/200 SMA trend, RSI pullback, and Inside Bar breakout logic to generate execution-ready swing trade setups with stop loss, target, and RRR.

• SMA Crossover Strategy Tool
  Simulates golden cross (50 > 200 SMA) for any stock, showing buy/sell signal counts and price trend.

• Compare Strategy Tool
  Compares performance between two tickers using SMA crossover logic.

• Stock Summary Tool
  Fetches current price, P/E ratio, market cap, and daily stats from Yahoo Finance.

• PDF Export (Optional)
  Export trade ideas and summaries for sharing or documentation.

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📊 Demo

👉 Try it Live: Streamlit App Link
💻 Repo: AutoQuant on GitHub

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🛠️ How It Works

This app is built using:

• LangChain agents with tools
• OpenRouter API for LLMs
• Yahoo Finance (yfinance) for market data
• Streamlit for UI
• Plotly (optional) for interactive charts

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🧱 File Structure

├── app.py                  # Streamlit frontend
├── agent.py                # LangChain agent + tools
├── main.py                 # Optional CLI/testing
├── test_strategy.py        # Strategy simulation tests
├── requirements.txt
└── README.md

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📦 Setup (Locally)

git clone https://github.com/Rohanrsp14/AutoQuant.git
cd AutoQuant
pip install -r requirements.txt
streamlit run app.py

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⚖️ License

MIT License

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👨‍💻 Author

Rohan
Senior Product Manager | Data-Driven | Passionate about Trading, Tech & Automation
LinkedIn · GitHub