Comps valuation
Value a company by comparable companies / trading multiples (and precedent transactions) - select peers, compute multiples, and apply to the target. Use for relative valuation alongside a DCF.From its SKILL.md
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SKILL.md
1.4 KB, 280 tokens by cl100k_base, as published. Nobody here has run it
comps-valuation
Relative value from how the market prices similar businesses. The peer set is everything.
Process
- Select peers: genuinely comparable by business model, size, growth, margins, geography - justify each; note where the target differs.
- Compute multiples for each peer (sourced): EV/Revenue, EV/EBITDA, P/E, P/FCF; use the right metric for the sector. Use a consistent basis (TTM or forward; EV reconciled with net debt).
- Benchmark: the peer median/mean and range; adjust for the target's growth/margin/quality differences.
- Apply the chosen multiple(s) to the target's metric -> implied EV/equity/per-share value RANGE.
- Precedent transactions (optional): control-premium multiples from comparable M&A.
Output
- The peer table (multiples, sourced), the chosen multiple + rationale, and the implied value RANGE - plus how it triangulates with the DCF (a "football field").
Guardrails
- Multiples sourced; consistent TTM/forward and EV basis (
accuracy-precision); peers justified, not cherry-picked. - A range, not a point; combine with DCF rather than relying on one method (
methodology).
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most finance skills give in 280 tokens
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Said here and by no other author read
- select genuinely comparable peers
- justify each selected peer
- note target differences from peers
- compute multiples for each peer
- use a consistent reporting basis
- benchmark peer median mean and range
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.