📈 NSE Stock Research & Analysis System

A sophisticated multi-agent AI system for analyzing Indian NSE-listed stocks using real-time data, technical indicators, news sentiment, and advanced AI reasoning.

🌟 Features

🤖 Multi-Agent Architecture

• Stock Finder Agent: Identifies promising NSE stocks based on liquidity, market cap, and momentum
• Market Data Agent: Gathers real-time pricing, volume, and technical indicators
• News Analyst Agent: Analyzes recent news sentiment and market impact
• Recommendation Agent: Provides actionable BUY/SELL/HOLD recommendations with target prices

📊 Advanced Analytics

• Real-time NSE stock data integration
• Technical indicators (RSI, Moving Averages, MACD)
• Volume and volatility analysis
• News sentiment classification
• Risk-reward assessment

🎯 Smart Recommendations

• Specific entry/exit price points
• Stop-loss levels and risk management
• Confidence scoring for each recommendation
• Time horizon-based analysis (short-term to medium-term)

🎨 Modern UI

• Clean, responsive Streamlit interface
• Interactive charts and visualizations
• Real-time status updates
• CSV export functionality
• Mobile-friendly design

🚀 Quick Start

Prerequisites

• Python 3.8+
• Bright Data API account (Sign up here)
• OpenAI API key (Get one here)

Installation

1. Clone the repository

   git clone https://github.com/rooneyrulz/agentic-stock-research-system
   cd nse-stock-research-system
   

2. Install dependencies

   pip install -r requirements.txt
   

3. Set up environment variables

   cp .env.example .env
   # Edit .env with your API keys
   

4. Install Bright Data MCP

   npm install -g @brightdata/mcp
   

Running the Application

1. Start the Streamlit app

   streamlit run streamlit_app.py
   

2. Access the application

   • Open your browser to http://localhost:8501
   • Enter your API keys in the sidebar
   • Select analysis parameters
   • Click "Start Analysis" and wait for results!

🔧 Configuration

API Keys Setup

Bright Data API Token

1. Sign up at Bright Data
2. Navigate to your dashboard
3. Go to "Zones" → "Web Unlocker"
4. Copy your API token

OpenAI API Key

1. Sign up at OpenAI Platform
2. Go to "API Keys" section
3. Create a new API key
4. Copy the key (starts with 'sk-')

Analysis Types

• Short-term Trading (1-7 days): Focus on momentum, technical breakouts, and news catalysts
• Medium-term Investment (1-4 weeks): Emphasis on earnings, sector trends, and technical setups
• General Market Analysis: Broad market overview with top stock picks across sectors

📈 Sample Output

🎯 TRADING RECOMMENDATIONS
═══════════════════════════════════

RELIANCE - Reliance Industries Limited
─────────────────────────────────
📋 RECOMMENDATION: BUY
🎯 TARGET PRICE: ₹2,650
⏰ TIME HORIZON: 1-3 days
📊 CONFIDENCE: HIGH

📈 ENTRY STRATEGY:
Current Price: ₹2,450
Suggested Entry: ₹2,430 - ₹2,460
Stop Loss: ₹2,380 (3.2% below entry)
Target: ₹2,650 (8.2% upside potential)

💡 RATIONALE:
Technical: Breakout above 50-day MA with strong volume
Fundamental: Positive earnings guidance + new project announcements
Risk-Reward: 1:2.6 ratio

🏗️ System Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Streamlit UI  │────│   Supervisor     │────│  Bright Data    │
│                 │    │     Agent        │    │   MCP Server    │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                              │
                    ┌─────────┼─────────┐
                    │         │         │
            ┌───────▼───┐ ┌───▼───┐ ┌───▼────┐
            │Stock Finder│ │Market │ │News    │
            │   Agent    │ │Data   │ │Analyst │
            └────────────┘ │Agent  │ │Agent   │
                          └───────┘ └────────┘
                                │
                        ┌───────▼────────┐
                        │ Recommendation │
                        │     Agent      │
                        └────────────────┘

🔍 Agent Details

Stock Finder Agent

• Scans NSE universe for liquid, high-potential stocks
• Filters by market cap, volume, and momentum criteria
• Avoids penny stocks and illiquid securities
• Focuses on large-cap and mid-cap opportunities

Market Data Agent

• Real-time price, volume, and market data
• Technical indicators (RSI, MACD, Moving Averages)
• Support/resistance level identification
• Trend analysis and momentum assessment

News Analyst Agent

• Scrapes recent financial news and announcements
• Sentiment classification (Positive/Negative/Neutral)
• Impact assessment on stock prices
• Catalyst identification for price movements

Recommendation Agent

• Synthesizes all data into actionable recommendations
• Provides specific entry/exit strategies
• Risk management and position sizing guidance
• Confidence scoring and time horizon analysis

🛡️ Risk Management Features

• Stop-loss recommendations for every trade suggestion
• Position sizing guidance based on volatility
• Risk-reward ratio analysis (minimum 1:2 ratio)
• Confidence scoring to help with decision making
• Time horizon specification for each recommendation

📊 Export & Reporting

• CSV Export: Download analysis results for further analysis
• Interactive Charts: Visualize current vs target prices
• Performance Tracking: Monitor recommendation accuracy
• Historical Analysis: Compare predictions with actual outcomes

⚠️ Important Disclaimers

• This tool is for educational and research purposes only
• Always consult with a qualified financial advisor before investing
• Past performance does not guarantee future results
• The Indian stock market involves substantial risk of loss
• Do your own due diligence before making any investment decisions

🤝 Contributing

We welcome contributions! Please see our contributing guidelines:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

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

🆘 Support

For support and questions:

• Open an issue on GitHub
• Check the documentation
• Review the troubleshooting guide below

Troubleshooting

Common Issues:

1. API Key Errors

   • Ensure your Bright Data token is valid and has sufficient credits
   • Verify OpenAI API key starts with 'sk-' and has available quota

2. MCP Installation Issues

   # Reinstall MCP globally
   npm uninstall -g @brightdata/mcp
   npm install -g @brightdata/mcp
   

3. Streamlit Issues

   # Clear Streamlit cache
   streamlit cache clear
   

4. Import Errors

   # Reinstall dependencies
   pip install -r requirements.txt --force-reinstall
   

🔄 Version History

• v1.0.0 - Initial release with multi-agent architecture
• v1.1.0 - Added Streamlit UI and export functionality
• v1.2.0 - Enhanced recommendation parsing and visualization

Made with ❤️ for the Indian Stock Market Community