Screen US stocks for high-quality dividend opportunities combining value characteristics (P/E ratio under 20, P/B ratio under 2), attractive yields (3% or higher), and consistent growth (dividend/revenue/EPS trending up over 3 years). Supports two-stage screening using FINVIZ Elite API for efficient

Value Dividend Screener Overview This skill identifies high quality dividend stocks that combine value characteristics, attractive income generation, and consistent growth using a two stage screening approach : 1. FINVIZ Elite API (Optional but Recommended) : Pre screen stocks with basic criteria (fast, cost effective) 2. Financial Modeling Prep (FMP) API : Detailed fundamental analysis of candidates Screen US equities based on quantitative criteria including valuation ratios, dividend metrics, financial health, and profitability. Generate comprehensive reports ranking stocks by composite quality scores with detailed fundamental analysis. Efficiency Advantage : Using FINVIZ pre screening can reduce FMP API calls by 90%, making this approach ideal for free tier API users. When to Use Invoke this skill when the user requests: "Find high quality dividend stocks" "Screen for value dividend opportunities" "Show me stocks with strong dividend growth" "Find income stocks trading at reasonable valuations" "Screen for sustainable high yield stocks" Any request combining dividend yield, valuation metrics, and fundamental analysis Workflow Step 1: Verify API Key Availability For Two Stage Screening (Recommended): Check if both API keys are available: If not available, ask user to provide API keys or set environment variables: For FMP Only Screening: Check if FMP API key is available: If not available, ask user to provide API key or set environment variable: FINVIZ Elite API Key: Requires FINVIZ Elite subscription (~$40/month or ~$330/year) Provides access to CSV export of pre screened results Highly recommended for reducing FMP API usage Provide instructions from references/fmp api guide.md if needed. Step 2: Execute Screening Script Run the screening script with appropriate parameters: Two Stage Screening (RECOMMENDED) Uses FINVIZ for pre screening, then FMP for detailed analysis: Default execution (Top 20 stocks): With explicit API keys: Custom top N: Custom output location: Script behavior (Two Stage): 1. FINVIZ Elite pre screening: Market cap: Mid cap or higher Dividend yield: 3%+ Dividend growth (3Y): 5%+ EPS growth (3Y): Positive P/B: Under 2 P/E: Under 20 Sales growth (3Y): Positive Geography: USA 2. FMP detailed analysis of FINVIZ results (typically 20 50 stocks): Dividend growth rate calculation (3 year CAGR) Revenue and EPS trend analysis Dividend sustainability assessment (payout ratios, FCF coverage) Financial health metrics (debt to equity, current ratio) Quality scoring (ROE, profit margins) 3. Composite scoring and ranking 4. Output top N stocks to JSON file Expected runtime (Two Stage): 2 3 minutes for 30 50 FINVIZ candidates (much faster than FMP only) FMP Only Screening (Original Method) Uses only FMP Stock Screener API (higher API usage): Default execution: With explicit API key: Script behavior (FMP Only): 1. Initial screening using FMP Stock Screener API (dividend yield =3.0%, P/E <=20, P/B <=2) 2. Detailed analysis of candidates (typically 100 300 stocks): Same detailed analysis as two stage approach 3. Composite scoring and ranking 4. Output top N stocks to JSON file Expected runtime (FMP Only): 5 15 minutes for 100 300 candidates (rate limiting applies) API Usage Comparison: Two Stage: ~50 100 FMP API calls (FINVIZ pre filters to ~30 stocks) FMP Only: ~500 1500 FMP API calls (analyzes all screener results) Step 3: Parse and Analyze Results Read the generated JSON file: Key data points per stock: Basic info: symbol , company name , sector , market cap , price Valuation: dividend yield , pe ratio , pb ratio Growth metrics: dividend cagr 3y , revenue cagr 3y , eps cagr 3y Sustainability: payout ratio , fcf payout ratio , dividend sustainable Financial health: debt to equity , current ratio , financially healthy Quality: roe , profit margin , quality score Overall ranking: composite score Step 4: Generate Markdown Report Create structured markdown report for user with following sections: Report Structure Step 5: Provide Context and Methodology Reference screening methodology when explaining results: Key concepts to explain: Why these specific thresholds (3.5% yield, P/E 20, P/B 2) Importance of dividend growth vs. static high yield How composite score balances value, growth, and quality Dividend sustainability vs. dividend trap distinction Financial health metrics significance Load references/screening methodology.md to provide detailed explanations of: Phase 1: Initial quantitative filters Phase 2: Growth quality filters Phase 3: Sustainability and quality analysis Composite scoring system Investment philosophy and limitations Step 6: Answer Follow up Questions Anticipate common user questions: "Why did [stock] not make the list?" Check which criteria it failed (yield, valuation, growth, sustainability) Explain the specific filter that excluded it "Can I screen for specific sectors?" Filtering capability exists in script (modify line 383 388) Suggest re running with sector parameter additions "What if I want higher/lower yield threshold?" Script parameters are adjustable Trade offs between yield and growth Recommend re screening with new parameters "How often should I re run this screen?" Quarterly recommended (aligns with earnings cycles) Semi annually sufficient for long term holders Market conditions may warrant more frequent checks "How many stocks should I buy?" Diversification guidance: minimum 10 15 for dividend portfolio Sector balance considerations Position sizing based on risk tolerance Resources scripts/screen dividend stocks.py Comprehensive screening script that: Interfaces with FMP API for data retrieval Implements multi phase filtering logic Calculates growth rates (CAGR) over 3 year periods Evaluates dividend sustainability via payout ratios and FCF coverage Assesses financial health (debt to equity, current ratio) Computes quality scores (ROE, profit margins) Ranks stocks by composite scoring system Outputs structured JSON results Dependencies: requests library (install via pip install requests ) Rate limiting: Built in delays to respect FMP API limits (250 requests/day free tier) Error handling: Graceful degradation for missing data, rate limit retries, API errors references/screening methodology.md Comprehensive documentation of screening approach: Phase 1: Initial Quantitative Filters Dividend yield = 3.5% rationale and calculation P/E ratio <= 20 threshold justification P/B ratio <= 2 valuation logic Phase 2: Growth Quality Filters Dividend growth (3 year CAGR = 5%) Revenue positive trend analysis EPS positive trend analysis Phase 3: Quality & Sustainability Analysis Dividend sustainability metrics (payout ratios, FCF coverage) Financial health indicators (D/E, current ratio) Quality scoring methodology (ROE, profit margins) Composite Scoring System (0 100 points) Score component breakdown and weighting Interpretation guidelines Investment Philosophy Why this approach works What this strategy avoids (dividend traps, value traps) Ideal candidate profile Usage Notes & Limitations Best practices for portfolio construction When to sell criteria Historical context for threshold selection references/fmp api guide.md Complete guide for Financial Modeling Prep API: API Key Setup Obtaining free API key Setting environment variables Free tier limits (250 requests/day) Key Endpoints Used Stock Screener API Income Statement API Balance Sheet API Cash Flow Statement API Key Metrics API Historical Dividend API Rate Limiting Strategy Built in protection in script Request budget management Best practices for free tier Error Handling Common errors and solutions Debugging techniques Data Quality Considerations Data freshness and gaps Data accuracy caveats When to verify with SEC filings Advanced Usage Customizing Screening Criteria Modify thresholds in scripts/screen dividend stocks.py : Line 383 388 Initial screening parameters: Line 423 Dividend CAGR threshold: Sector Specific Screening Add sector filtering after initial screening: Excluding REITs and Financials REITs and financial stocks have different dividend characteristics (higher payouts, different metrics): Exporting to CSV Convert JSON results to CSV for Excel analysis: Troubleshooting "ERROR: requests library not found" Solution: Install requests library "ERROR: FMP API key required" Solution: Set environment variable or provide via command line "ERROR: FINVIZ API key required when using use finviz" Solution: Set environment variable or provide via command line Note: FINVIZ Elite subscription required (~$40/month or ~$330/year) "ERROR: FINVIZ API authentication failed" Possible causes: 1. Invalid FINVIZ API key 2. FINVIZ Elite subscription expired 3. API key format incorrect Solution: Verify FINVIZ Elite subscription is active Check API key for typos (should be alphanumeric string) Log into FINVIZ Elite account and verify API key in settings Try accessing FINVIZ Elite screener manually to confirm subscription "ERROR: FINVIZ pre screening failed or returned no results" Possible causes: 1. FINVIZ API connection issue 2. Screening criteria too restrictive (no stocks match) 3. Market conditions (bear market may yield fewer results) Solution: Check internet connection Verify FINVIZ Elite website is accessible Try FMP only method as fallback: "WARNING: Rate limit exceeded" Solution: Script automatically retries after 60 seconds. If persistent: Wait until next day (free tier resets daily) Reduce number of stocks analyzed (modify line 394 limit) Consider upgrading to paid FMP tier "No stocks found matching all criteria" Solution: Criteria may be too restrictive Relax P/E threshold (increase from 20) Lower dividend yield requirement (decrease from 3.5%) Reduce dividend growth requirement (decrease from 5%) Check market conditions (bear markets may have fewer qualifiers) Script runs slowly Expected behavior: Script includes 0.3s delay between API calls for rate limiting 100 stocks analyzed = ~8 10 minutes First 20 30 qualifying stocks usually found within first 50 70 analyzed Performance & Cost Optimization API Call Comparison Two Stage Screening (FINVIZ + FMP): FINVIZ: 1 API call FMP Quote API: ~30 50 calls (one per pre screened symbol) FMP Financial Data: ~150 250 calls (5 endpoints × 30 50 symbols) Total FMP calls: ~180 300 FMP Only Screening: FMP Stock Screener: 1 call (returns 100 1000 stocks) FMP Financial Data: ~500 5000 calls (5 endpoints × 100 1000 symbols) Total FMP calls: ~500 5000 Savings: 60 94% reduction in FMP API usage Cost Analysis FINVIZ Elite: Monthly: $39.50 Annual: $299.50 (~$24.96/month) FMP API: Free tier: 250 calls/day (sufficient for two stage screening) Starter tier: $29.99/month for 750 calls/day Professional tier: $79.99/month for 2000 calls/day Recommendation: For free FMP tier users : Use two stage screening (FINVIZ + FMP free tier) For paid FMP tier users : Either approach works; two stage is faster Budget option : FMP only with free tier (run screening every few days) Optimal option : FINVIZ Elite ($330/year) + FMP free tier = Complete solution Version History v1.1 (November 2025): Added FINVIZ Elite integration for two stage screening v1.0 (November 2025): Initial release with comprehensive multi phase screening

value-dividend-screener