Skill: lyflyd/us-stock-analyzer (version 1.0.0)

--- 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: - FMP_API_KEY bins: - python3 - pip3 primaryEnv: FMP_API_KEY emoji: "📈" homepage: https://github.com/yourusername/us-stock-analyzer install: - kind: uv package: yfinance bins: [python3] - kind: uv package: pandas bins: [python3] - kind: uv package: numpy bins: [python3] - kind: uv package: matplotlib bins: [python3] - kind: uv package: pyyaml bins: [python3] - kind: uv 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 ```bash # 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 ```python from scripts.decision_engine import StockAnalyzer analyzer = StockAnalyzer(config_path="config.yaml") result = analyzer.analyze("TSLA") print(result['report']) ``` ### With Chart Output ```python 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 output ``` ## Methodology See [references/methodology.md](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)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)