📈 US Stock Analyzer - Three-Factor Buy Signal System

A comprehensive stock analysis system that combines Value Investing (DCF), Trend Trading (Livermore Rules), and Market Sentiment (VIX) to generate buy signals only when all three factors align.

Quick Start

# Install dependencies
pip3 install yfinance pandas numpy matplotlib pyyaml requests

# Set API key (optional, for enhanced financial data)
export FMP_API_KEY="your_key_here"

# Run analysis
python3 scripts/decision_engine.py AAPL

Three-Factor Framework

1️⃣ Value Factor (DCF) - 40% Weight

• Buy Condition: Price < Intrinsic Value × (1 - Margin of Safety)
• Key Metrics: Free Cash Flow, WACC, growth rates, ROE, debt levels
• Output: Value score 0-100, fair value estimate

2️⃣ Trend Factor (Livermore) - 35% Weight

• Buy Conditions:
  • Break above resistance with volume confirmation (1.5x avg)
  • Sector alignment (ETF in uptrend)
  • Price > MA20 > MA60
• Output: Trend score 0-100, key support/resistance levels

3️⃣ Sentiment Factor (VIX) - 25% Weight

• Buy Conditions:
  • VIX < 25 (non-panic)
  • VIX percentile < 70% (not expensive)
  • Market breadth positive (SPY uptrend)
• Output: Sentiment score 0-100, market regime

Final Buy Signal

BUY = Value ≥ 60 AND Trend ≥ 60 AND Sentiment ≥ 60 AND Composite ≥ 70

Usage

Basic Analysis

from scripts.decision_engine import StockAnalyzer

analyzer = StockAnalyzer(config_path="config.yaml")
result = analyzer.analyze("TSLA")
print(result['report'])

With Chart Output

analyzer.plot_analysis(result['result'], save_path="tsla_analysis.png")

Data Sources

Configuration

Edit config.yaml to customize:

• DCF discount rate (default: 10%)
• Margin of safety threshold (default: 20%)
• VIX panic threshold (default: 30)
• Factor weights
• Position sizing rules

Output

The system generates a formatted report including:

• Executive summary with composite score
• Individual factor scores with visual bars
• Buy/hold signal with confidence level
• Position sizing recommendation
• Target price and stop loss levels
• Risk assessment

File Structure

us-stock-analyzer/
├── SKILL.md                 # This file
├── config.yaml             # Configuration
├── requirements.txt        # Python dependencies
├── scripts/
│   ├── data_fetcher.py    # Data retrieval
│   ├── dcf_analyzer.py    # DCF valuation
│   ├── trend_analyzer.py  # Livermore trend analysis
│   ├── sentiment_analyzer.py # VIX sentiment
│   └── decision_engine.py # Three-factor engine
├── references/
│   └── methodology.md     # Detailed methodology
└── examples/
    └── sample_report.md   # Example output

Methodology

See references/methodology.md for:

• Detailed DCF calculation methodology
• Livermore trading rules implementation
• VIX sentiment scoring algorithm
• Position sizing formulas

Disclaimer

This tool is for informational purposes only and does not constitute investment advice. Always conduct your own research and consider consulting a financial advisor before making investment decisions.

License

MIT-0 (Public Domain)