- name
- us-stock-analyzer
- description
- Three-factor stock analysis combining DCF valuation, Livermore trend trading rules, and VIX market sentiment to generate high-confidence buy signals for US equities. Use when analyzing US stocks for investment decisions, determining optimal entry points, or evaluating buy opportunities with multi-factor confirmation.
- version
- 1.0.0
- metadata
- openclaw
- requires
- env
- bins
- primaryEnv
- FMP_API_KEY
- emoji
- 📈
- homepage
- https://github.com/yourusername/us-stock-analyzer
- install
- package
- yfinance
- bins
- [python3]
- package
- pandas
- bins
- [python3]
- package
- numpy
- bins
- [python3]
- package
- matplotlib
- bins
- [python3]
- package
- pyyaml
- bins
- [python3]
- package
- requests
- bins
- [python3]
📈 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 AAPLThree-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 ≥ 70Usage
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
| Data | Source | Required |
|---|---|---|
| Price/Volume | Yahoo Finance (yfinance) | Free |
| Financials | FMP API | Optional (free tier) |
| VIX | CBOE via Yahoo | Free |
| Sector ETFs | Yahoo Finance | Free |
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 outputMethodology
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)