Selected Precedent Transactions
Show what buyers have actually paid for businesses like this one.
Seat
IB · PE
Level
Analyst / Associate
Runtime
~30 min
Output
Precedent transactions page: Excel + slide
What this helps you accomplish
Announced deals with their multiples and premiums, the statistics across the set, and the value per share they imply for the target. A deal price carries control and, for a strategic buyer, synergies, so precedents sit above trading multiples by construction. Check the dates before anything else: a set leaning on 2021 is describing a different market.
What you get
Not a description of an output. The file itself, in the conventions a banker, a PE associate or a hedge fund analyst already reads without being told.
{TICKER}_transaction-comps.xlsx
Excel workbook
- 1
Target inputs
The target’s own shares, net debt, current price and trailing metrics, which the precedent multiples are applied to
- 2
Selected precedent transactions ($mm)
Date, acquirer, target, consideration, enterprise value, the multiples paid and the premium to unaffected, with maximum, quartile, mean, median and minimum rows
- 3
Implied valuation of the target
The quartile and median multiples and the median premium applied to the target, to a value per share and a premium to the current price
- 4
PowerPoint
One slide: the precedent table, the implied-value table and a KPI rail of the range against the offer
Where the numbers come from
From the filings: the header only, which is the target’s own shares, net debt and trailing metrics. Every filed figure resolves to its form, period, page, the printed value and a link into the filing on EDGAR. Not from filings: every precedent, which arrives as an illustrative placeholder the build warns about. Replace the rows from the deal proxies or from your own list. Assumptions are listed on the slide’s source line under "Not from filings", so an assumed input is never read as a filed one.
Run it yourself
python3 skills/deal-slides/build.py transaction-comps --ticker BSX --offer 60Delegate · Verify · Decide
The core L3VLUP principle: AI output is never automatically correct. Know what to hand off, what to check, and what only you can own.
Delegate
AI is good enough to do this.
- • Filling the header from the filings with a citation on each figure
- • Computing each precedent’s multiples, the percentile statistics and the implied valuation
- • Applying the median premium to the target’s unaffected price
- • Building the branded slide with both tables and the KPI rail
Verify
AI accelerates you here, but a professional checks the work.
- • Each precedent’s enterprise value and metric against the deal’s own proxy or announcement
- • That every multiple is struck on trailing figures as at the announcement date
- • That every premium uses the same reference, and the header names which
- • That a deal with a leaked approach is either excluded or flagged, because its premium is understated
Decide
Judgment the human owns. This is the skill.
- • The screen, and the period the set covers
- • Whether competed, hostile or distressed deals belong in it
- • How much of the precedent premium is control and how much was synergy specific to that buyer
- • Whether the implied range supports the recommendation being made from it
Inputs required
- Company name or ticker
- The offer per share
- The precedent list: date, acquirer, target, enterprise value, metrics and premium
- Your own numbers where you would rather not use the default
The workflow
- 1
Resolve the company
A ticker or a name fills the header the precedent multiples are applied to.
- 2
Set the screen
Sector, size, geography and a period you can defend. A five-year window through a rate cycle is a different set from a three-year one.
- 3
Replace the rows
Each precedent comes from its own proxy or announcement: enterprise value, the metric it is struck on, and the premium with its reference date.
- 4
Normalise the basis
Multiples on trailing figures as at announcement, and premiums on the same reference for every deal. A mixed basis makes the median meaningless.
- 5
Build and compare
The offer row at the bottom against the median on both bases, with competed, hostile or distressed deals flagged if they stay in the set.
Run this skill
Any listed company, anywhere. Ticker or name.
Quality checklist
The output isn’t done until every box ticks.
- verify reports zero errors and every derived cell is a formula on blue inputs
- Units are on every table header and the subtitle names the pricing date
- Every precedent states its announcement date and its multiples are on trailing figures at that date
- Premiums use the same reference for every deal and the header says which
- The offer row is compared with the median on both bases in the notes
- Competed, hostile or distressed deals are flagged in the source line if they stay in the set