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Get Started Free →Build M&A accretion/dilution workbooks in Excel.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | 16% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 53% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 4% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 8% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 40% | 0% |
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
Other measured skills in the registry, with their headline benchmark lift.