Stock Screener

A comprehensive tool for screening, analyzing, and reporting on stocks, with a focus on penny stocks.

Features

• Screen stocks based on financial metrics
• Fetch real-time stock data with Yahoo Finance
• Analyze options data for market sentiment
• Generate AI-powered analysis using Llama 3 via Ollama
• Save detailed investment reports and summaries

Project Structure

stock_screener/
│
├── analysis/           # Stock analysis components
├── config/             # Configuration settings
├── data/               # Data retrieval and processing
│   ├── simple_yahoo.py     # Yahoo Finance integration
│   ├── stock_screener.py   # Main screening logic
│   └── test_data.py        # Sample data for testing
├── utils/              # Utility functions
└── main.py             # Main entry point

Installation

1. Clone the repository

git clone https://github.com/yourusername/stock_screener.git
cd stock_screener

2. Create a virtual environment

python -m venv venv

3. Activate the virtual environment:

   • Windows: venv\Scripts\activate
   • Mac/Linux: source venv/bin/activate

4. Install requirements

pip install -r requirements.txt

5. Install Ollama (for local LLM support)
   • Follow instructions at Ollama's GitHub
   • Pull the Llama 3 model:

   ollama pull llama3:latest

Configuration

1. Copy the example environment file:

cp .env.example .env

2. Edit the .env file and add your configuration:

YAHOO_MAX_RETRIES=3
YAHOO_TIMEOUT=10

Usage

Running the Full Screener

# Run the full stock screener
python -m stock_screener.main

Running Individual Components

# Run stock fetching component
python run_specific_component.py --fetch

# Run stock screening component
python run_specific_component.py --screen

# Run AI analysis component
python run_specific_component.py --analyze

Testing

# Run a single stock analysis test
python test_ai_analysis.py --single

# Test stock scoring
python test_stock_scoring.py

Output Files

The screener generates several output files:

• selected_tickers_[date].json: Basic information about all selected stocks
• investment_summary_[date].md: Detailed investment summary with analysis
• penny_stocks_analysis_[date].md: Comprehensive analysis of screened stocks

Contributing

1. Fork the repository
2. Create your 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.

AI Analysis Integration

The stock screener uses Llama 3 via Ollama for generating stock analyses. This provides:

• Local processing of analyses (no API costs)
• Privacy (data stays on your machine)
• Customizable analysis through prompt engineering
• Fast response times

Requirements

• Ollama installed and running
• Llama 3 model pulled (ollama pull llama3:latest)
• Sufficient system resources for LLM inference