Precedent transaction Analysis

The Precedent transaction analysis is a valuation method in which the price paid for same companies in the past is considered an indicator of a company’s value. Precedent transaction analysis creates an estimate of what a share of stock would be worth in the case of an acquisition.

Steps to Perform Precedent Transaction Analysis:

Search for relevant transactions

The process begins by looking for other transactions that have happened in (ideally) recent history and are in the same industry.

The screening process requires setting criteria such as:

  • Industry classification
  • Type of company (public, private, etc.)
  • Financial metrics (revenue, EBITDA, net income)
  • Geography (headquarters, revenue mix, customer mix, employees)
  • Company size (revenue, employees, locations)
  • Product mix (the more similar to the company in question, the better)
  • Type of buyer (private equity, strategic/competitor, public/private)
  • Deal size (value)
  • Valuation (multiple paid, i.e., EV/Revenue, EV/EBITDA, etc.)

The above criteria can be set in a financial database, such as Bloomberg or CapIQ, and exported to Excel for further analysis.

Analyze and refine the available transactions

Once the initial screen has been performed and the data is transferred into Excel, then it’s time to start filtering out the transactions that don’t fit the current situation.

In order to sort and filter the transactions, an analyst has to “scrub” the transactions by carefully reading the business descriptions of the companies on the list and removing any that aren’t a close enough fit.

Many of the transactions would have missing and limited information if the deal terms were not publicly disclosed. The analyst will search high and low for a press release, equity research report, or another source that contains deal metrics.  If nothing can be found, those companies will be removed from the list.

Determine a range of valuation multiples

When a shortlist is prepared (following steps 1 and 2), the average, or selected range, of valuation multiples can be calculated.

The most common multiples for precedent transaction analysis are EV/EBITDA and EV/Revenue.

An analyst may exclude any extreme outliers, such as transactions that had EV/EBITDA multiples much lower or much higher than the average (assuming there is a good justification for doing so).

Apply the valuation multiples to the company in question

After a range of valuation multiples from past transactions has been determined, those ratios can be applied to the financial metrics of the company in question.

For example, if the valuation range was:

  • 4.5x EV/EBITDA (low)
  • 6.0x EV/EBITDA (high)

And the company in question has an EBITDA of $150 million,

The valuation ranges for the business would be:

  • $675 million (low)
  • $900 million (high)

Graph the results (with other methods) in a football field

Once a valuation range has been determined for the business that’s being valued, it’s important to graph the results so they can be easily understood and compared to other methods.

The Football field chart is the best way to illustrate the various methods on one page in a simple way.

The main valuation methods included in the chart are:

  • Comparable company analysis
  • Precedent transactions analysis
  • DCF analysis
  • Ability-to-pay analysis
  • 52-week hi/lo (if a public company)
Advantages Disadvantages
Typically based on publicly available information. Public data is based on past transactions that may not be indicative of current market conditions.
Multiples reflect actual payments for real-life deals, rather than traded multiples that are subject to supply and demand pressure. Information available from industry and news sources can be misleading.
Useful in M&A negotiations and discussions. Precedent transaction dynamics are rarely perfectly comparable.


Provide guidance to assess what a buyer may be willing to pay for a business. Values and multiples obtained may vary over a wide range and the summary metrics may be of limited usefulness.
Can reveal valuable information such as industry consolidation trends, and potential buyers and sellers. Other factors may affect the multiples such as governance issues, specific agreements, synergies, and intangible values (such as patents and other intellectual property).

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