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merger-model
// Build accretion/dilution (merger) models in Excel — pro-forma P&L, synergies, financing mix, EPS impact. Pairs with excel-author. Use for M&A pitches, board materials, or deal evaluation.
// Build accretion/dilution (merger) models in Excel — pro-forma P&L, synergies, financing mix, EPS impact. Pairs with excel-author. Use for M&A pitches, board materials, or deal evaluation.
| name | merger-model |
| description | Build accretion/dilution (merger) models in Excel — pro-forma P&L, synergies, financing mix, EPS impact. Pairs with excel-author. Use for M&A pitches, board materials, or deal evaluation. |
| version | 1.0.0 |
| author | Anthropic (adapted by Nous Research) |
| license | Apache-2.0 |
| platforms | ["linux","macos","windows"] |
| metadata | {"hermes":{"tags":["finance","m-and-a","merger","accretion-dilution","excel","openpyxl","modeling","investment-banking"],"related_skills":["excel-author","pptx-author","dcf-model","3-statement-model"]}} |
This skill assumes headless openpyxl — you are producing an .xlsx file on disk.
Follow the excel-author skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
Recalculate before delivery: python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx.
Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms.
Acquirer:
Target:
Deal Terms:
| Item | Value |
|---|---|
| Offer price per share | |
| Premium to current | |
| Equity value | |
| Plus: net debt assumed | |
| Enterprise value | |
| EV / EBITDA implied | |
| P/E implied |
| Sources | $ | Uses | $ |
|---|---|---|---|
| New debt | Equity purchase price | ||
| Cash on hand | Refinance target debt | ||
| New equity issued | Transaction fees | ||
| Financing fees | |||
| Total | Total |
Calculate year-by-year (Year 1-3):
| Standalone | Pro Forma | Accretion/(Dilution) | |
|---|---|---|---|
| Acquirer net income | |||
| Target net income | |||
| Synergies (after tax) | |||
| Foregone interest on cash (after tax) | |||
| New debt interest (after tax) | |||
| Intangible amortization (after tax) | |||
| Pro forma net income | |||
| Pro forma shares | |||
| Pro forma EPS | |||
| Accretion / (Dilution) % |
Accretion/Dilution vs. Synergies and Offer Premium:
| $0M syn | $25M syn | $50M syn | $75M syn | $100M syn | |
|---|---|---|---|---|---|
| 15% premium | |||||
| 20% premium | |||||
| 25% premium | |||||
| 30% premium |
Accretion/Dilution vs. Cash/Stock Mix:
| 100% cash | 75/25 | 50/50 | 25/75 | 100% stock | |
|---|---|---|---|---|---|
| Year 1 | |||||
| Year 2 |
Calculate the minimum synergies needed for the deal to be EPS-neutral in Year 1.
Many passages below say "use the S&P Kensho MCP / Daloopa MCP / FactSet MCP". Those are commercial financial-data MCPs from the original Cowork plugin context. In Hermes:
native-mcp skill), prefer it for point-in-time comps, precedent transactions, and filings.web_search / web_extract against SEC EDGAR (https://www.sec.gov/cgi-bin/browse-edgar) for US filingsbrowser_navigate for interactive data portals[UNSOURCED] and surface it to the user.This skill is adapted from Anthropic's Claude for Financial Services plugin suite (Apache-2.0). The Office-JS / Cowork live-Excel paths have been removed; this version targets headless openpyxl via the excel-author skill's conventions. Original: https://github.com/anthropics/financial-services