Valuation Methods – Precedent Transaction Comparables

In addition to the public trading multiples comparables, the other common multiples valuation methodology is the M&A multiples compset. M&A multiples uses mergers and acquisition transactions to value the target. One can use the value that others that have put on a company to help determine the valuation of the target.

The example below, taken from the Oracle/Autonomy deck shows recent precedent transactions in the enterprise software space.

M&A comp set

The list would be shorter and more varied than the trading multiples compset.


With most acquisitions, there is a premium paid for the target. There is value to controlling the company rather than just investing in the target. There is potential for operational synergies (top-line growth, decreased overhead, decreased financial risk, funding cost etc.)
That premium is included in the price of the acquisition and hence baked into the M&A multiple, so you would need to discount the M&A multiple to get to a fair trading multiple. I’ve seen discounts ranging from 15% to 50%.

After coming up with the the multiples, you apply them to your target.

Valuation Methods – Public Comparables

There are numerous ways to value a company. Each method has its pros and cons and are usually used in combination to triangulate a value. Of course, the value is ultimately set by the buyer.

This post will give an example of public comparables methodology. A public compset is a select set of publicly traded companies where price metrics and operating metrics are laid out in a table for comparison with the target company. The example below is a quick compset I threw together of internet companies with Apple and RIMM thrown in for comparison.

What companies to include

Ideally, there are direct competitors and pure plays, meaning they only focus on that one product/service. You can also include companies that offer similar services. In our example compset below, most are internet/tech companies. But there is a sub-segment of pure internet companies if you remove Apple and RIMM.
You can also segment the list based on size or other outliers.
In my experience, the ideal list size is 7-10 companies.
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