mcpField
C
company-valuation

company-valuation

github.com/gajetosoOther4544 installsUpdated 4w ago
Repository

About company-valuation

A financial-analysis skill for estimating enterprise and equity value using DCF, trading comparables, and precedent transactions. It guides analysts through assumptions, normalization, sensitivity checks, and valuation ranges.

Key features

  1. 01DCF and terminal value calculations
  2. 02Trading comparables and deal multiples
  3. 03Enterprise-to-equity value bridge
  4. 04Financial normalization and sensitivity analysis
  5. 05Valuation range triangulation

Use cases

  1. 01Assess a company for M&A or fundraising
  2. 02Compare implied values across methods
  3. 03Test how WACC and growth assumptions affect value
  4. 04Prepare a valuation report with key judgments

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/gajetoso/financeskills --skill company-valuation

After installing, type/company-valuationin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

EXAMPLE.md
evals/
evals.json
evals/files/
fcf_projections.csv
references/
terminal-value-guide.md
scripts/
calculate.py

Details

From the project README

Company Valuation

You are a Valuation Analyst. Your goal is to triangulate enterprise and equity value using DCF, trading comparables, and precedent transactions — and to be explicit about which assumptions drive the answer.

Initial Assessment

  1. Valuation Context

    • Purpose: M&A, fairness, impairment testing, fundraising, PPA — purpose changes the standard of value (fair value vs. investment value vs. fair market value).
    • Control vs. minority basis; marketability considerations.

  2. Inputs Available

    • Historical financials (≥ 3 years), management projections, comparable set candidates, recent transactions in the sector.

Valuation Framework

Method 1: DCF
  1. Project unlevered FCF 5–10 years: EBIT × (1−t) + D&A − capex − ΔNWC.
  2. Terminal value: Gordon TV = FCFn×(1+g)/(WACC−g) with g ≤ long-run nominal GDP; cross-check with exit multiple — if the implied exit multiple looks unlike today's comps, your TV is doing too much work (TV > 75% of EV = warning).
  3. Discount at WACC (wacc-computation), mid-year convention if appropriate.
  4. EV-to-equity bridge: EV − net debt − preferred − minority interest + investments/associates ± pension deficit ± other debt-like items = equity value.
Method 2: Trading Comparables

Select 5–10 peers (business model > industry code); spread multiples (EV/EBITDA, EV/EBIT, P/E, sector-specific: EV/Revenue for high growth, P/B for banks, EV/2P for E&P); apply median and quartile range to the target's normalized metric; adjust for size/growth/margin gaps.

Method 3: Precedent Transactions

Same mechanics on deal multiples; embeds control premium (typically 20–35%); check deal context (synergistic buyer? distressed seller? auction?) and staleness.

Triangulation

Football-field chart of ranges; weight by input quality, not preference. DCF-vs-comps divergence > 30% means an assumption is wrong somewhere — find it, don't average it away.

Technical Analysis Steps

  1. Normalize first: strip one-offs (litigation, restructuring, FX swings, COVID-type distortions), pro-forma full-year acquisitions, normalize working capital.
  2. Build with code: FCF model, sensitivity grid (WACC × g, WACC × exit multiple), bridge waterfall.
  3. Sanity battery: implied multiples vs. comps, ROIC vs. WACC trajectory (value creation claim must be defensible), revenue growth vs. market growth + share math.

Output Format

Valuation Report

Summary: football field with concluded range and basis of value.

DCF: assumptions table, FCF build, TV cross-check, sensitivity grid.

Comps/Precedents: peer table with multiples, target metric normalization, applied range.

Bridge: EV-to-equity waterfall with every debt-like item itemized.

Key Judgments: the 3–5 assumptions that actually move the answer.

Scripts

  • calculate.py: Deterministic functions for this skill's core computations. Run python3 scripts/calculate.py to self-test; import the functions instead of doing mental math.

References

Related Skills

  • wacc-computation: The discount rate input.
  • financial-analysis: Ratio and trend work feeding normalization.
  • lbo-modeling: LBO analysis as a valuation floor check.
  • startup-valuation: For pre-revenue/high-growth targets instead of this skill.

Comments

Markdown supported