Purpose
Translate a target company profile into a defensible trading comparables analysis — a screened peer set, the right multiple set, benchmarked statistics, and an implied valuation range — so an analyst can move from "who are the comps?" to a board-ready valuation range without rebuilding methodology each time.
When to Use
Invoke this skill when the user asks to:
- Build a trading comps or comparable company analysis for a target
- Identify the right peer set to value a private or public company
- Determine which valuation multiples apply to a given business model
- Derive an implied valuation range from public market comparables
- Pressure-test or sanity-check an existing valuation against peers
- Prepare the comps tab narrative for a pitch deck or fairness opinion
Inputs Required
Before starting, collect:
- Target description: 2–4 sentences on what the company does, business model, and primary revenue streams
- Sector / sub-sector: The industry vertical and any niche positioning
- Financial profile: Revenue, EBITDA, EBITDA margin, growth rate, and net income (or as many as available)
- Size band: Approximate revenue or enterprise value scale (informs peer comparability)
- Geography: Primary markets and where it's domiciled
- Candidate comps (optional): Any peers the user already has in mind
- Purpose of the analysis: Acquisition, fundraising, IPO readiness, fairness opinion, or internal valuation
If EBITDA or net income is missing, default to the multiples the available metrics support (e.g., EV/Revenue for early-stage or pre-profit companies) and flag the limitation.
Instructions
Step 1: Define Peer-Set Selection Criteria
Establish the screening rules before naming any companies. Filter on:
- Industry / business model: Same revenue model and value chain position — not just same broad sector
- Size: Comparable revenue or EV scale, typically within roughly 0.3x–3x of the target; flag when the target is materially smaller or larger than its universe
- Growth profile: Similar revenue growth trajectory — high-growth and mature peers trade on different multiples
- Margin profile: Comparable EBITDA / gross margins, which drive multiple dispersion within a sector
- Geography / end markets: Same primary markets and regulatory regime
- Capital structure considerations: Note where leverage or one-time items will distort equity-value multiples
State each criterion explicitly so the peer set is auditable.
Step 2: Build the Comparable Universe
Identify 8–12 candidate comparables that satisfy the criteria. For each, capture:
- Company name and ticker (where public)
- One-line rationale: why it belongs in the set
- A fit rating: Core / Adjacent / Peripheral
Mark "Core" peers (closest business model, size, and growth) separately — these drive the central valuation conclusion; Adjacent and Peripheral peers provide context and range boundaries.
Step 3: Select the Relevant Multiple Set
Map multiples to the business model, with reasoning:
- EV/EBITDA: Primary multiple for profitable, capital-normalized businesses; capital-structure neutral
- EV/Revenue: Use for pre-profit, high-growth, or margin-volatile companies; always pair with a margin/growth note
- P/E: Use when comparing equity value and capital structures are similar; sensitive to leverage and tax differences
- Sector-specific multiples: Note any standard the sector demands (e.g., EV/EBITDAR, ARR multiples, EV/Subscriber) and recommend including them when applicable
Recommend a primary multiple and 1–2 secondary multiples, with a one-sentence justification each.
Step 4: Benchmark the Multiples
Construct the benchmarking table across the peer set, computing for each chosen multiple:
- Minimum, 25th percentile, Median, Mean, 75th percentile, Maximum
- Position the target's own current metrics (growth, margin) relative to the set to justify where in the range it should land
Lead with the median and interquartile range rather than the mean — the median is the standard anchor and resists outlier distortion.
Step 5: Identify and Comment on Outliers
For any peer whose multiple sits well outside the interquartile range:
- Name the company and the multiple
- Explain the likely driver (acquisition premium baked in, distressed valuation, hyper-growth, one-time earnings distortion, thin float)
- Recommend: keep, footnote, or exclude — with reasoning
A clean comps analysis explains its outliers rather than silently discarding them.
Step 6: Derive the Implied Valuation Range
Apply the benchmarked multiples to the target's financials:
- Apply the 25th percentile, median, and 75th percentile multiples to the relevant target metric
- Produce a low / central / high implied enterprise value (and equity value where applicable)
- Reconcile across multiples — if EV/EBITDA and EV/Revenue imply divergent ranges, explain why and which to weight
- State the recommended valuation range in a single sentence with the central anchor
Output Format
- Structure: Six sections following the Instructions sequence, with a benchmarking table and an implied-valuation table
- Length: 900–1,300 words
- Format: Structured document — prose for criteria and commentary; tables for the comparable universe, the multiple benchmarking statistics, and the implied valuation range
- Sections: Selection Criteria → Comparable Universe → Multiple Set & Rationale → Benchmarking Table → Outlier Commentary → Implied Valuation Range
- Tone: M&A analyst — precise, methodologically transparent, conclusion-oriented; defensible to a deal team or committee
Quality Checklist
Before delivering output, verify:
- [ ] Selection criteria are stated explicitly before any company is named
- [ ] The comparable universe has 8–12 peers, each with a rationale and Core/Adjacent/Peripheral fit rating
- [ ] The chosen multiple set is justified against the target's business model — not applied by default
- [ ] The benchmarking table reports min, 25th, median, mean, 75th, and max for each multiple
- [ ] Every outlier outside the interquartile range is named and explained, with a keep/footnote/exclude call
- [ ] The implied valuation range gives a low/central/high figure and a single-sentence recommended range
Notes
- Anchor conclusions on the median and interquartile range; the mean is reported for context but is vulnerable to outliers.
- A peer set of fewer than 6 names is usually too thin to be defensible — broaden the criteria or add adjacent peers and footnote the stretch.
- Comps establish a market-implied range; pair them with a DCF when the target's cash-flow profile diverges meaningfully from its peers.
- Always note the data-as-of date — trading multiples move, and a comps range is only valid as of the pricing date.
How to use this skill
This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.
Installing in Claude Code:
~/.claude/skills/<folder-name>/SKILL.md— auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)<your-project>/.claude/skills/<folder-name>/SKILL.md— auto-loads only when working in that project (recommended for project-specific skills)
Restart Claude Code or open a new session to register.
Using in Claude.ai, ChatGPT, Gemini, or other AI tools:
- Drag this file into a new chat, or copy and paste its contents
- Send your task or request as your next message — the AI will apply the skill where it fits
For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills