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workflow-er-idea-screening

WHAT: Quantitative and thematic investment idea generation — applying Piotroski F-Score, Beneish M-Score, FCF yield, ROIC vs WACC, and revenue growth filters to a broad universe, then overlaying thematic qualitative criteria to produce a ranked list of deep-dive candidates with one-paragraph thesis summaries. WHEN: Invoke when generating new investment ideas for a coverage universe or sector, performing quantitative stock screening, or responding to a mandate such as "find quality growth names in [sector]" or "screen for value with fundamental momentum".

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fall-development-rob/corp_finance
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11. Mai 2026 um 14:10
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
workflow-er-idea-screening
description
WHAT: Quantitative and thematic investment idea generation — applying Piotroski F-Score, Beneish M-Score, FCF yield, ROIC vs WACC, and revenue growth filters to a broad universe, then overlaying thematic qualitative criteria to produce a ranked list of deep-dive candidates with one-paragraph thesis summaries. WHEN: Invoke when generating new investment ideas for a coverage universe or sector, performing quantitative stock screening, or responding to a mandate such as "find quality growth names in [sector]" or "screen for value with fundamental momentum".
# Equity Research: Investment Idea Screening ## What this skill covers A two-stage funnel — quantitative filters followed by thematic overlay — that narrows a broad universe to a ranked shortlist of deep-dive candidates. Each surviving candidate receives a one-paragraph thesis summary and a composite score. ## Inputs - Universe definition: broad index, sector, or custom ticker list - Thematic mandate (optional): sector focus, factor tilt (quality, value, growth, momentum), or ESG constraint - Screening stringency: standard (Piotroski >= 7, Beneish < -1.78) or custom thresholds ## Workflow ### Step 1 — Define the universe Start with the broadest feasible universe. Options: - A sector via `fmp_stock_screener` (filter by sector, market cap floor) - An index via `fmp_index_constituents` - A custom ticker list provided by the user Record the starting universe count. ### Stage 1 — Quantitative screens Apply hard filters sequentially. Record pass/fail count at each gate. **Gate 1: Fundamental quality — Piotroski F-Score** Call `piotroski_fscore` for each company. Pass criterion: score >= 7 (strong fundamentals on profitability, leverage, and operating efficiency dimensions). Fail: score < 7. **Gate 2: Earnings integrity — Beneish M-Score** Call `beneish_mscore` for each passing company. Pass criterion: M-Score < -1.78 (no manipulation signal). Fail: M-Score >= -1.78 (potential manipulation — exclude or flag for extra scrutiny). **Gate 3: Value creation — ROIC vs WACC** Call `fmp_key_metrics` for ROIC. Call `wacc_calculator` for WACC estimate. Pass criterion: ROIC > WACC (company destroys or creates value). Fail: ROIC <= WACC. **Gate 4: Cash generation — FCF yield and revenue growth** Call `fmp_key_metrics` for FCF yield. Call `fmp_financial_ratios` for revenue growth vs sector median. Pass criteria: FCF yield > 5% AND revenue growth > sector median. Fail: either criterion misses. Record the universe count after Stage 1: [N] companies passed all four gates. ### Stage 2 — Thematic overlay (qualitative filters) For each Stage 1 survivor, apply the thematic mandate: 1. **Sector trends:** is the company operating in an industry with secular tailwinds (not just cyclical recovery)? 2. **TAM growth:** is the addressable market expanding >5% annually? (use industry sources or World Bank data) 3. **Regulatory tailwinds:** are pending policy changes a net positive for this company's model? 4. **Management alignment:** recent insider buying or low turnover at senior level (check `fmp_insider_latest`) Each criterion scores 0 or 1. Minimum thematic score: 2 of 4 to advance to the shortlist. ### Stage 3 — Composite ranking Compute a composite score for each shortlisted company: ``` composite = (piotroski_fscore / 9 × 0.35) + (fcf_yield_normalised × 0.30) + (roic_spread_normalised × 0.20) + (thematic_score / 4 × 0.15) ``` Rank all shortlisted companies by composite score. Top 5-10 become deep-dive candidates. ### Step 4 — One-paragraph thesis per idea For each deep-dive candidate, write a one-paragraph thesis: - Ticker, market cap (from `fmp_market_cap`), sector - Key fundamental strengths (from Piotroski sub-scores) - Valuation hook (FCF yield, ROIC spread) - Thematic alignment - Single-sentence investment thesis ## Output format 1. **Funnel table** — universe start count and pass count at each gate 2. **Shortlist table** — ranked by composite score with sub-scores per dimension 3. **Thesis summaries** — one paragraph per deep-dive candidate 4. **Next steps** — which candidates are recommended for full `workflow-er-initiating-coverage` ## Quality gates - [ ] All Piotroski scores from `piotroski_fscore` — not manual calculation - [ ] All Beneish scores from `beneish_mscore` - [ ] WACC from `wacc_calculator`; ROIC from `fmp_key_metrics` - [ ] Composite score formula applied consistently to all shortlisted candidates - [ ] Shortlist limited to 5-10 candidates — not a padded list ## Related skills - `workflow-er-initiating-coverage` — full coverage initiation for shortlisted candidates - `workflow-er-sector-overview` — sector context that informs thematic criteria in Stage 2 - `workflow-er-thesis-tracker` — thesis framework applied once a candidate advances to coverage
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