📈 Advanced Stock Screener

A comprehensive stock screening and analysis platform that delivers in-depth market insights through multi-sector analysis, technical indicators, and automated valuation metrics. The platform combines fundamental analysis, technical indicators, and sector-specific metrics to provide detailed investment recommendations across all major market sectors.

Live Application for public usage via Streamlit Community Deployment site: https://better-stonk-screener.streamlit.app/

✨ Enhanced Features

Core Analysis Capabilities:

• 📊 Multi-factor valuation analysis across all market sectors
• 📈 Comprehensive technical indicator integration
• 🎯 Sector-specific metrics and risk analysis
• 📱 Modern, tab-based dashboard interface
• 🔍 Advanced filtering and comparison tools
• 📊 Interactive visualizations with Plotly
• 💾 Enhanced export functionality

Analysis Components:

Fundamental Analysis:

• Industry-adjusted P/E and P/B ratios
• DCF valuation modeling
• Financial health scoring
• Sector-specific performance metrics
• Risk-adjusted valuation scores

Technical Analysis:

• RSI indicators with overbought/oversold signals
• Moving average crossover detection
• Volume analysis with trend confirmation
• Technical score aggregation
• Interactive technical charts

Sector Analysis:

• Sector-specific performance metrics
• Risk factor analysis by sector
• Industry benchmark comparisons
• Sector trend visualization
• Peer comparison tools

Dashboard Features:

• Summary Dashboard with key metrics
• Technical Analysis visualization
• Sector-specific analysis
• Stock Comparison tools
• Detailed Analysis with filtering

Educational Components:

• Built-in metric explanations
• Technical indicator guides
• Sector-specific insights
• Risk factor education

🔄 Current Limitations & Development Opportunities:

Sector Analysis:

• Limited sector-specific metric collection for non-Tech/Energy sectors
• Opportunity to implement detailed metrics for:
  • Financial Services (banking ratios, credit metrics)
  • Healthcare (pipeline analysis, regulatory metrics)
  • Consumer sectors (brand value, market share)
  • Real Estate (occupancy rates, NOI analysis)

Risk Analysis:

• Basic risk factor implementation
• Opportunity to enhance:
  • Sector-specific risk calculations
  • Market risk integration
  • Volatility analysis
  • Correlation studies

Data Integration:

• Currently limited to Financial Modeling Prep API
• Potential to add:
  • Alternative data sources
  • Real-time news integration
  • Social sentiment analysis
  • Economic indicator correlation

Future Enhancement Opportunities:

Technical Analysis:

• Additional technical indicators (MACD, Bollinger Bands)
• Pattern recognition algorithms
• Custom indicator creation
• Backtesting capabilities

Portfolio Analytics:

• Portfolio optimization tools
• Risk-adjusted return calculations
• Correlation analysis
• Diversification metrics

Machine Learning Integration:

• Predictive analytics
• Pattern recognition
• Anomaly detection
• Sentiment analysis

API & Data:

• Multiple data source integration
• Real-time websocket support
• Custom API endpoint creation
• Enhanced data validation

🚀 Installation & Setup

1. Clone the Repository

git clone https://github.com/m-turnergane/stock-screener.git
cd stock-screener

2. Set Up Virtual Environment

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Create .env File

# Create a .env file in the root directory
# Add your FMP API key:
FMP_API_KEY=your_api_key_here

🖥️ Usage Guide

Starting the Application:

streamlit run stock_screener.py

Application Workflow:

1. Stock Selection

   • Enter stock symbols in the sidebar
   • Add multiple stocks for comparison
   • View basic company info upon addition

2. Analysis Options

   • Summary Dashboard: Overall market view
   • Technical Analysis: Detailed technical indicators
   • Sector Analysis: Sector-specific metrics
   • Stock Comparison: Side-by-side analysis
   • Detailed Analysis: Comprehensive metrics with filtering

3. Interactive Features

   • Filter stocks by various metrics
   • Compare multiple stocks
   • Export analysis results
   • Access educational content

📊 Dashboard Components

1. Summary Dashboard

   • Market overview metrics
   • Valuation score distribution
   • Top stock recommendations
   • Key insights summary

2. Technical Analysis

   • RSI visualization with signals
   • Moving average crossover detection
   • Volume analysis
   • Technical signal alerts

3. Sector Analysis

   • Sector-specific metrics
   • Risk factor analysis
   • Industry comparisons
   • Performance distribution

4. Stock Comparison

   • Side-by-side metric comparison
   • Radar chart visualization
   • Relative performance analysis
   • Multiple stock selection

5. Detailed Analysis

   • Comprehensive metrics table
   • Custom filtering options
   • Export functionality
   • Sorting capabilities

🔧 Customization Options

1. Metric Weights

   • Adjust valuation weights
   • Modify technical score components
   • Customize sector-specific weightings

2. Analysis Parameters

   • RSI thresholds
   • Moving average periods
   • Volume significance levels
   • Risk tolerance settings

3. Visualization Options

   • Chart types
   • Color schemes
   • Data display preferences
   • Export formats

👥 Contributing

Development Focus Areas:

1. Sector Analysis Enhancement

   • Implement additional sector metrics
   • Develop sector-specific risk models
   • Create custom sector visualizations

2. Technical Analysis Expansion

   • Add new technical indicators
   • Implement pattern recognition
   • Enhance signal detection

3. Data Integration

   • Additional API integrations
   • Alternative data sources
   • Real-time data handling

4. UI/UX Improvements

   • Mobile responsiveness
   • Custom themes
   • Advanced filtering
   • Interactive tutorials

Contribution Process:

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

Code Standards:

• Follow PEP 8 guidelines
• Include docstrings and comments
• Add unit tests for new features
• Update documentation

🔍 Testing

Running Tests:

python -m pytest tests/

Test Coverage:

• Unit tests for core functions
• Integration tests for API
• UI component testing
• Performance benchmarks

📚 Documentation

Code Documentation:

• Function and class documentation
• API endpoint descriptions
• Configuration options
• Custom metric calculations

User Documentation:

• Installation guide
• Usage tutorials
• Metric explanations
• Troubleshooting guide

🔒 Security & Performance

Security Considerations:

• API key protection
• Rate limiting
• Data validation
• Error handling

Performance Optimization:

• API call caching
• Data preprocessing
• Batch processing
• Memory management

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

🙏 Acknowledgements

• Financial Modeling Prep API
• Streamlit Framework
• Plotly Visualization Library
• Contributing Developers

💡 Support For support, feature requests, or bug reports:

• Open an issue on GitHub
• Review existing issues
• Join discussions
• Contribute solutions