Comps valuation
Claude Code pack for financial analysts: data-integrity (citation), SEC/FINRA disclaimer, projection-labeling & MNPI/PII guardrails + skills for statement analysis, ratios, DCF/comps valuation, modeling, earnings, forecasting & FP&A, loops & review agents. Not investment advice.
npx -y skills add m-binimran/finance-pack --skill comps-valuationAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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What its author says it does
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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.
SKILL.md
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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).