NeuraCap

M&A intelligence

M&A precedent transactions, normalised into evidence

Precedent transaction analysis is only as good as the comparability of the deals in the set. NeuraCap holds a structured M&A transaction record, rebuilds each deal onto a consistent enterprise-value definition, aligns the target financials behind the multiple, and lets you cut the set by sector, size, date, deal type and buyer type until it resembles the transaction you are actually working on.

  • Transaction comparables
  • Deal multiples
  • Buyer universe
  • Sector deal flow
208,000M&A transactions in the record
97.5%of figures confirmed against two independent sources

The story

Announced numbers are not comparable numbers.

Precedent transactions

From a press release to a usable multiple

The problem
Deal announcements describe consideration in whatever way suits the announcement. Debt is sometimes included and sometimes not, target financials are quoted on inconsistent periods, and a large share of transactions disclose no price at all.
Why it matters
Precedent transactions carry more weight than any other method in a sale process, because they show what a buyer actually paid rather than what a market is quoting. A set assembled from unadjusted announcements will be attacked on comparability, and it will lose.
In NeuraCap
NeuraCap resolves the parties, rebuilds the consideration onto one enterprise-value definition, aligns the target's financials to a comparable basis and period, applies plausibility gates, and classifies the deal by sector, size, type, buyer and geography.
What you get
A filterable deal set with normalised multiples, the classification behind each transaction, the median and percentile spread of the set, and a clear count of how many deals in the period disclosed terms at all.
The decision it enables
What a buyer would plausibly pay for this asset, which acquirers are active in the space right now, and whether the public market or the deal market is telling the better story.

Normalisation, step by step

  1. Resolve the partiesTarget, acquirer and any consortium members are matched to the same entities used elsewhere in the platform, so a deal can be read against the acquirer's own financial profile.
  2. Rebuild the considerationAnnounced consideration, assumed debt and cash acquired are reconciled into an enterprise value on a consistent definition, rather than taken from whichever number the press release led with.
  3. Align the denominatorTarget financials are put on a comparable basis and period before any multiple is calculated, because an EV/EBITDA against a different EBITDA is not a comparable at all.
  4. Gate the resultMultiples that fail a plausibility test are excluded. They are not winsorised into the median or quietly plotted at the edge of the chart.
  5. Classify the dealSector, industry group, deal type, buyer type and geography are attached so the set can be filtered down to the transactions that actually resemble the one in front of you.

Filtering

Six ways to cut the set until it is genuinely comparable.

A precedent set is an argument about similarity. These are the dimensions that decide whether that argument holds.
Filter dimensions available on the M&A transaction record and why each matters
DimensionHow it is usedWhy it changes the answer
Sector and industry groupNarrow from a broad sector to the specific sub-segment.Multiples inside one sector diverge sharply by sub-segment. The average of the whole sector is rarely the relevant number.
Date rangeAny window, from the last two weeks to several years.Deal multiples are a function of the rate and credit environment they were struck in. A five-year average blends two different markets.
Deal sizeBand the set by enterprise value.Large-cap transactions and lower-mid-market transactions clear at different multiples for the same business model.
Deal typeControl, minority, carve-out, take-private.What was bought changes what was paid. A carve-out multiple is not a whole-company multiple.
Buyer typeStrategic acquirer or financial sponsor.Strategics pay for synergies; sponsors pay for returns. Separating them explains much of the spread in a deal set.
GeographyBy target and acquirer domicile.Cross-border deals carry a different premium pattern, and local market comparables often make the better argument.

Honesty about the data

What the deal record can and cannot tell you.

M&A data is the messiest input in corporate finance. Being straight about its limits is what makes the rest of the analysis usable.

Not every deal has a multiple

Many transactions are announced without consideration, and private targets often disclose no financials. Those deals still count as activity, but they cannot produce a multiple, and the platform says so rather than estimating one.

Gated, not smoothed

Implausible multiples are excluded so they are never plotted. A distressed sale at a broken denominator should not set the top of anybody’s range.

Read, not asserted

The commentary is calibrated: NeuraCap reads a pattern in the deal set rather than claiming it caused anything. The methodology page sets out the rule.

Where it feeds

The deal set is one bar on the field, and one half of the story.

Precedent transactions rarely agree with trading comparables. That gap is the most useful thing on the page, and it is why both are kept in view.

Nothing in the deal record is a recommendation to buy or sell a security, an offer or solicitation, an appraisal, or a fairness opinion.

Proof

See it in the published research.

The Bi-Weekly Industry Events & M&A Update is the deal record in published form: what was announced in the last two weeks, at what multiples where terms were disclosed, and what it says about the sector. Free, ungated, every two weeks.

Pick the industry group you care about on the sector coverage index, or see how deal evidence is used in a live mandate by private equity deal teams and investment banking coverage teams.

Get your custom-built strategic insights report today.

Public or private, any sector. Tell us the company and what you need to understand.