workflow-er-thesis-tracker

# Equity Research: Investment Thesis Tracker ## What this skill covers Structures the bull/base/bear thesis framework with explicit scenario definitions, price targets, probability weights, and milestone catalysts. Defines the update protocol for quarterly thesis drift detection — flagging when actual results diverge from the base case and triggering a re-rating review when two or more catalysts resolve in the same direction. ## Inputs - Company ticker and current coverage rating - Existing price target and valuation model output (from `workflow-er-initiating-coverage` or `workflow-er-model-update`) - List of known upcoming catalysts with dates ## Workflow ### Step 1 — Bull case definition Define the upside scenario with: - 3-5 specific catalysts that drive the bull case (e.g., margin expansion, market share gain, product launch success) - Bull case revenue, EBITDA, EPS assumptions (explicit; not narrative) - Call `dcf_model` with bull case inputs to derive the bull price target - Quantify upside: bull PT vs current price, implied return % - Assign probability weight (typically 20-30%) ### Step 2 — Base case definition Define the central estimate: - Core assumptions for revenue growth, margin, multiple — most likely outcome - Call `dcf_model` with base case inputs to confirm the published price target - Call `comps_analysis` for trading multiple cross-check - This is the published price target and the current rating's basis - Assign probability weight (typically 50-60%) ### Step 3 — Bear case definition Define the downside scenario with: - 3-5 specific risks that drive the bear case (e.g., competitive entry, margin compression, end-market demand weakness) - Bear case revenue, EBITDA, EPS assumptions (explicit) - Call `dcf_model` with bear case inputs to derive the bear price target - Quantify downside: bear PT vs current price, implied loss % - Assign probability weight (typically 15-25%) **Validation:** bull + base + bear probability weights must sum to 100%. ### Step 4 — Probability-weighted price target Compute: `PT_weighted = (bull_PT × bull_weight) + (base_PT × base_weight) + (bear_PT × bear_weight)` The published price target is the base case PT; the probability-weighted PT is reported alongside for reference. ### Step 5 — Catalyst milestone register For each catalyst (from all three cases), create a register entry: | Catalyst | Expected date | Scenario relevance | Expected impact | Resolved? | |----------|--------------|-------------------|-----------------|-----------| | Q2 margin guidance | Q2 2026 earnings | Base / Bull | ±150bps on EBITDA | No | | FDA approval, drug X | H1 2026 | Bull only | +20% revenue in FY2027 | No | Track resolution quarterly. A catalyst resolves as: **confirming** (aligns with base or bull), **neutral**, or **challenging** (aligns with bear). ### Step 6 — Quarterly drift detection At each quarterly update: 1. Mark resolved catalysts in the register 2. Tally: how many resolved as confirming vs challenging? 3. Trigger rule: if 2+ catalysts resolve in the same direction (both confirming or both challenging), initiate a scenario re-rating review 4. Call `sensitivity_matrix` to quantify the scenario weight shift 5. Document thesis status: **on-track** / **drifting** / **broken** When thesis is **broken** (core assumption definitively refuted), initiate a rating change review and call `target_price` with updated case weights. ## Output format 1. **Thesis memo (3-5 pages)** — structured as: bull case, base case, bear case, probability weights, probability-weighted PT 2. **Catalyst milestone register** — table as in Step 5, updated each quarter 3. **Quarterly update log** — per quarter: catalysts resolved, thesis status, weight changes ## Quality gates - [ ] All three scenario price targets derived from `dcf_model` — not narrative estimates - [ ] Probability weights sum to 100% - [ ] At least 3 catalysts per scenario defined with specific dates - [ ] Drift detection rule documented and applied each quarter - [ ] Rating change review triggered when 2+ catalysts break in the same direction ## Related skills - `workflow-er-initiating-coverage` — produces the initial model and valuation that seed the thesis cases - `workflow-er-earnings-update` — quarterly earnings notes trigger catalyst resolution updates - `workflow-er-model-update` — model revision invoked when thesis drifts materially - `workflow-er-idea-screening` — provides quantitative backing for new thesis ideas