dividend-growth-pullback-screener
Use this skill to find high-quality dividend growth stocks (12%+ annual dividend growth, 1.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI ≤40). This skill combines fundamental dividend analysis with technical timing indicators to identify buying opportunities in strong dividend growers during short-term weakness.
What this skill does
# Dividend Growth Pullback Screener ## Overview This skill screens for dividend growth stocks that exhibit strong fundamental characteristics but are experiencing temporary technical weakness. It targets stocks with exceptional dividend growth rates (12%+ CAGR) that have pulled back to RSI oversold levels (≤40), creating potential entry opportunities for long-term dividend growth investors. **Investment Thesis:** High-quality dividend growth stocks (often yielding 1-2.5%) compound wealth through dividend increases rather than high current yield. Buying these stocks during temporary pullbacks (RSI ≤40) can enhance total returns by combining strong fundamental growth with favorable technical entry timing. ## When to Use This Skill Use this skill when: - Looking for dividend growth stocks with exceptional compounding potential (12%+ dividend CAGR) - Seeking entry opportunities in quality stocks during temporary market weakness - Willing to accept lower current yields (1.5-3%) for higher dividend growth - Focusing on total return over 5-10 years rather than current income - Market conditions show sector rotations or broad pullbacks affecting quality names **Do NOT use when:** - Seeking high current income (use value-dividend-screener instead) - Requiring immediate dividend yields >3% - Looking for deep value plays with strict P/E or P/B requirements - Short-term trading focus (<6 months) ## Prerequisites - **FMP API key** (required): Set `FMP_API_KEY` environment variable or pass `--fmp-api-key`. Free tier (250 calls/day) is sufficient for FMP-only mode (≤40 stocks). [Sign up](https://site.financialmodelingprep.com/developer/docs). - **FINVIZ Elite API key** (optional, recommended): Set `FINVIZ_API_KEY` environment variable or pass `--finviz-api-key`. Reduces execution time from 10–15 min to 2–3 min. [Sign up](https://elite.finviz.com/). - Python 3.8+ with `requests` and `pandas` libraries installed. ## Screening Workflow ### Step 1: Set API Keys #### Two-Stage Approach (RECOMMENDED) For optimal performance, use FINVIZ Elite API for pre-screening + FMP API for detailed analysis: ```bash # Set both API keys as environment variables export FMP_API_KEY=your_fmp_key_here export FINVIZ_API_KEY=your_finviz_key_here ``` **Why Two-Stage?** - **FINVIZ**: Fast pre-screening with RSI filter (1 API call → ~10-50 candidates) - **FMP**: Detailed fundamental analysis only on pre-screened candidates - **Result**: Analyze more stocks with fewer FMP API calls (stays within free tier limits) #### FMP-Only Approach (Original Method) If you don't have FINVIZ Elite access: ```bash export FMP_API_KEY=your_key_here ``` **Limitation**: FMP free tier (250 requests/day) limits analysis to ~40 stocks. Use `--max-candidates 40` to stay within limits. ### Step 2: Execute Screening **Two-Stage Screening (RECOMMENDED):** ```bash python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py --use-finviz ``` This executes: 1. FINVIZ pre-screen: Dividend yield 0.5-3%, Dividend growth 10%+, EPS growth 5%+, Sales growth 5%+, RSI <40 2. FMP detailed analysis: Verify 12%+ dividend CAGR, calculate exact RSI, analyze fundamentals **FMP-Only Screening:** ```bash python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py --max-candidates 40 ``` **Customization Options:** ```bash # Two-stage with custom parameters python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py \ --use-finviz --min-yield 2.0 --min-div-growth 15.0 --rsi-max 35 # FMP-only with custom parameters python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py \ --min-yield 2.0 --min-div-growth 10.0 --max-candidates 30 # Provide API keys as arguments (instead of environment variables) python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py \ --use-finviz --fmp-api-key YOUR_FMP_KEY --finviz-api-key YOUR_FINVIZ_KEY ``` ### Step 3: Review Results The script generates two outputs: 1. **JSON file:** `dividend_growth_pullback_results_YYYY-MM-DD.json` - Structured data with all metrics for further analysis - Includes dividend growth rates, RSI values, financial health metrics 2. **Markdown report:** `dividend_growth_pullback_screening_YYYY-MM-DD.md` - Human-readable analysis with stock profiles - Scenario-based probability assessments - Entry timing recommendations ### Step 4: Analyze Qualified Stocks For each qualified stock, the report includes: **Dividend Growth Profile:** - Current yield and annual dividend - 3-year dividend CAGR and consistency - Payout ratio and sustainability assessment **Technical Timing:** - Current RSI value (≤40 = oversold) - RSI context (extreme oversold <30 vs. early pullback 30-40) - Price action relative to recent trend **Quality Metrics:** - Revenue and EPS growth (confirms business momentum) - Financial health (debt levels, liquidity ratios) - Profitability (ROE, profit margins) **Investment Recommendation:** - Entry timing assessment (immediate vs. wait for confirmation) - Risk factors specific to the stock - Upside scenarios based on dividend growth compounding ## Output The script saves two files to the current working directory (or `--output-dir` if specified): | File | Description | |---|---| | `dividend_growth_pullback_results_YYYY-MM-DD.json` | Structured data with all metrics (yield, dividend CAGR, RSI, composite score, etc.) | | `dividend_growth_pullback_screening_YYYY-MM-DD.md` | Human-readable report with stock profiles, entry timing, and investment recommendations | **Report structure (Markdown):** - Executive summary (number of candidates, market conditions) - Ranked stock profiles with dividend growth profile, technical timing, and quality metrics - Entry recommendations based on RSI zone (extreme oversold / strong oversold / early pullback) - Disclaimers ## Screening Criteria Details ### Phase 1: Fundamental Screening (FMP API) **Initial Filter:** - Dividend Yield ≥ 1.5% (calculated from actual dividend payments) - Market Cap ≥ $2 billion (liquidity and stability) - Exchange: NYSE, NASDAQ (excludes OTC/pink sheets) **Dividend Growth Analysis:** - 3-Year Dividend CAGR ≥ 12% (doubles dividend in 6 years) - Dividend Consistency: No cuts in past 4 years - Payout Ratio < 100% (sustainability check) **Financial Health:** - Positive revenue growth over 3 years - Positive EPS growth over 3 years - Debt-to-Equity < 2.0 (manageable leverage) - Current Ratio > 1.0 (liquidity) ### Phase 2: Technical Screening (RSI Calculation) **RSI Calculation:** - 14-period RSI using daily closing prices - Formula: RSI = 100 - (100 / (1 + RS)) - RS = Average Gain / Average Loss over 14 periods - Data source: FMP historical prices (past 30 days) **RSI Filter:** - RSI ≤ 40 (oversold/pullback condition) - RSI interpretation: - < 30: Extreme oversold (potential reversal) - 30-40: Early pullback (uptrend correction) - > 40: Not oversold (excluded) ### Phase 3: Ranking and Output **Composite Scoring (0-100):** - Dividend Growth (40%): Reward higher CAGR and consistency - Financial Quality (30%): ROE, profit margins, debt levels - Technical Setup (20%): Lower RSI = better entry opportunity - Valuation (10%): P/E and P/B for context (not exclusionary) Stocks ranked by composite score. Top scorers combine exceptional dividend growth with attractive technical entry points. ## Understanding the Results ### Interpreting RSI Levels **RSI 25-30 (Extreme Oversold):** - Often indicates panic selling or negative news - Higher risk but potentially highest reward - Recommended: Wait for RSI to turn up (sign of stabilization) - Entry: Scale in with 50% position, add on RSI >30 **RSI 30-35 (Strong Oversold):** - Normal correction in strong uptrend - Lower risk than extreme oversold - Recommended: Can initiate position immediately - Entry: Full position acceptable, set stop loss 5-8% below **RSI 35-40 (Early Pu
Related in Ads & Marketing
ads
IncludedMulti-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Ads. 250+ checks with scoring, parallel agents, industry templates, and AI creative generation.
banana
IncludedAI image generation Creative Director powered by Google Gemini Nano Banana models. Use this skill for ANY request involving image creation, editing, visual asset production, or creative direction. Triggers on: generate an image, create a photo, edit this picture, design a logo, make a banner, visual for my anything, and all /banana commands. Handles text-to-image, image editing, multi-turn creative sessions, batch workflows, and brand presets.
rpg-migration-analyzer
IncludedAnalyzes legacy RPG (Report Program Generator) programs from AS/400 and IBM i systems for migration to modern Java applications. Extracts business logic from RPG III/IV/ILE source code, identifies data structures (D-specs), file operations (F-specs), program dependencies (CALLB/CALLP), and converts RPG constructs to Java equivalents. Generates migration reports, complexity estimates, and Java implementation strategies with POJO classes, JPA entities, and service methods. Use when modernizing AS/400 or IBM i legacy systems, analyzing RPG source files (.rpg, .rpgle, .RPGLE), converting RPG to Java, mapping data specifications to Java classes, planning legacy system migration, or when user mentions RPG analysis, Report Program Generator, RPG III/IV/ILE, AS/400 modernization, IBM i migration, packed decimal conversion, or mainframe application rewrite.
brand-library-architect
IncludedBuild a complete brand library for a product — visual asset render pipeline, brand documentation set (BRAND, COPY, MANIFESTO, BIOS, FAQ, GLOSSARY, TONE, PRICING), open-source convention files (README, CONTRIBUTING, SECURITY, CODE_OF_CONDUCT), and a self-contained press kit. This skill should be used when the user asks to "build a brand library / brand kit / press kit / brand assets" for a product, "set up a brand library workflow," "create a positioning manifesto plus visual identity," or any combination of brand documentation + visual asset pipeline. Apply phase-by-phase or run end-to-end. Templates are product-agnostic and use {{TOKEN}} placeholders the skill prompts the user to fill.
writing-tech-post
IncludedAuthors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces an evidence cadence (diagrams, benchmarks, profiles, traces, code, ablations), tunes voice against publisher house styles (Datadog, Vercel, GitHub, AWS, Meta, Cloudflare, Jane Street), and runs a pre-publish gate for narrative momentum and disclosure ethics. Use when drafting a new engineering post, restructuring a draft that feels flat, deciding which evidence form belongs where, validating that depth and product context are balanced, or preparing a postmortem, migration, or performance narrative for external publication. Do not use for API reference documentation, README authoring, marketing copy, release notes, generic SEO content, ghost-written executive thought leadership, or non-engineering long-form essays.
blog-google
IncludedGoogle API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".