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Precedent-transactions screen + adjusted-multiples framing

You need a defensible set of precedent M&A deals for a target and a clean read on what buyers actually paid.

The prompt — copy and run it

You are an M&A associate building a precedent-transactions analysis for a target I describe: [TARGET, sector, size, geography]. Produce:
1. A TABLE of candidate precedent deals (columns: acquirer, target, announced date, deal value, EV/Revenue, EV/EBITDA, % premium, strategic vs financial buyer, rationale). Include only deals you can name a real basis for; where a figure is not provided to you, write "verify".
2. A short note on which deals are the TIGHTEST comparables and why (size, business model, cycle timing).
3. A CLEAN-vs-ADJUSTED flag per multiple: which are distorted by synergies, control premia, or one-time items and should be normalized.
4. The 2-3 questions to resolve before quoting any multiple to a client.

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

Why this prompt works

Precedent screens live or die on comparability and on separating clean multiples from control/synergy noise — this forces both, plus a verification step so no headline multiple is quoted blind.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

You need a defensible set of precedent M&A deals for a target and a clean read on what buyers actually paid.

Why does this prompt work?

Precedent screens live or die on comparability and on separating clean multiples from control/synergy noise — this forces both, plus a verification step so no headline multiple is quoted blind.

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