Precedent Transaction Analysis

Guide to Understanding Precedent Transaction Analysis

Precedent Transaction Analysis: Training Tutorial

The premise of precedent transaction analysis – often used interchangeably with the term “transaction comps” – is that similar transactions of comparable companies can serve as a useful point of reference when valuing companies.

In short, precedent transaction analysis utilizes multiples to calculate the value of a target.

Thus, precedent transaction analysis is a method of valuing a company based on the purchase multiples recently paid to acquire comparable companies.

Once the peer group of comparable transactions and the appropriate valuation multiples are selected, either the median or mean multiple of the peer group is applied to the target’s corresponding metric to arrive at a transaction comps-derived value.

The estimated valuation from transaction comps is not meant to be a precise calculation, but rather establishes valuation parameters for the target company based on what other buyers paid for similar companies.

From the perspective of a buyer and seller, as well as their advisors, the goal is to gain insight on:

1. Buy Side → “How much should we offer to purchase the company?”
2. Sell Side → “How much can we sell our company for?”

Based on the circumstances surrounding each transaction, a higher premium (or discount) could be warranted, but the acquirer can benchmark against comparable transactions to ensure their offer price is “reasonable” and most importantly, as a sanity check.

Valuation Multiples Review: Enterprise Value vs. Equity Value

Just to briefly review, a valuation multiple is comprised of a value measure in the numerator – i.e. enterprise value or equity value – whereas the denominator will be an operating metric like EBITDA or EBIT.

It is important to ensure that the represented investor groups (i.e. the capital providers) must match both the numerator and denominator.

• Enterprise Value Multiple: TEV multiples are more practical due to being capital structure neutral, i.e. the enterprise value represents all the providers of capital, such as debt and equity holders.
• Equity Value Multiple: On the other hand, equity value multiples represent the residual value remaining just for common shareholders – for example, the P/E ratio.

Comparable Transactions Screening Criteria

The “peer group” in transaction comps analysis describes the collection of recent M&A transactions involving companies with characteristics that are similar to that of the target.

When selecting which types of companies sufficiently meet the criteria to be placed in the peer group, considerations include:

• Business Characteristics: Product/Service Mix, Key End Markets Served, Customer Type (B2B, B2C)
• Financial Profile: Revenue Growth, Profit Margins (Operating and EBITDA Margins)
• Risks: Regulatory Landscape, Competitive Landscape, Industry Headwinds or Tailwinds, External Threats

However, “pure-play” transactions are virtually non-existent, so flexibility must be retained in the screening process, especially for niche industries.

Particularly for precedent transaction analysis, it is important that the transactions occurred relatively recently because dissimilar macroeconomic conditions can create significant differences in valuations.

The necessary data to perform transaction comps can be acquired from the following sources:

• Deal Announcement Press Releases
• Merger Proxy and 8-Ks
• Tender Office Documents (Schedule 14D-9, Schedule TO)
• Financial Reports (10-K / 10-Q Filings)
• Management Presentations
• Equity Research Reports (M&A Commentary)

Precedent Transaction Analysis Guide (Steps-by-Step)

Step Description
Step 1. Compile Comparable Transactions
• The first step is to compile data on recent transactions that closed within the same (or an adjacent) industry as the target, i.e. ideally close competitors of the target.
Step 2. Market Research
• The next step is to gather as much relevant information as possible from publicly available sources, as well as the ongoing industry and market trends to understand which specific factors impact the purchase multiples in a specific industry.
Step 3. Input Financial Data
• Once an understanding of the industry is formed, the next step is to organize the financial data of each comparable transaction, making sure to “scrub” (adjust) the financials for non-recurring items, accounting differences, leverage differences, and any cyclicality or seasonality.
• If needed, the company’s financials might need to be calendarized to standardize the dates (i.e. different ending fiscal year dates converted to match).
Step 4. Calculate Peer Group Multiples
• After the financials are entered, the relevant valuation multiples can be calculated to be compared against one another in the output sheet.
• The general convention is to express the multiples on a last twelve months (LTM) and next twelve months (NTM) basis, with the summarized data on the minimum, 25th percentile, median, mean, 75th percentile, and maximum of each metric.
Step 5. Apply Multiples to Target
• In the final step, either the median or mean multiple is applied to the target’s corresponding metric to get the transaction comps-derived value.
• It is imperative to not neglect the fundamental drivers affecting purchase prices, as well as any transactional considerations to understand why one deal was priced higher (or lower) than the peer average.

Transaction Comps Peer Group: Deal Considerations

When putting together a peer group for transaction comps, the following are examples of diligence questions to keep in mind:

1. Transaction Rationale: What was the transaction rationale from both the buyer’s and seller’s perspectives?
• Overpaying is a common occurrence in M&A, so the outcome of the deal should be assessed.
2. Buyer Profile: Was the acquirer a strategic or a financial buyer?
• Strategic acquirers can afford to pay a greater control premium than financial buyers because strategics can benefit can synergies.
3. Sale Process Dynamics: How competitive was the sale process?
• The more competitive the sale process, i.e. the more buyers that are serious about acquiring the target, the greater the likelihood of a higher premium.
4. Auction vs. Negotiated Sale: Was the transaction an auction process or negotiated sale?
• In most cases, a sale structured as an auction will result in a higher purchase price.
5. M&A Market Conditions: What were the market conditions at the time when the deal closed?
• If the credit markets are healthy (i.e. if access to debt to partially fund the deal or share price is relatively easy), then the buyer is more likely to pay a higher price.
6. Transaction Nature: Was the transaction hostile or friendly?
• A hostile takeover tends to increase the purchase price, as either side does not want to be on the losing end.
7. Purchase Consideration: What was the purchase consideration (e.g. all-cash, all-stock, mixture)?
• A transaction in which the purchase consideration was stock rather than cash is more likely to be valued less than an all-cash transaction since the shareholder can benefit from the potential upside post-deal.
8. Industry Trends: If the industry is cyclical (or seasonal), did the transaction close at a high or low point in the cycle?
• If the transaction occurred at an unusual time (e.g. cyclical peak or bottom, seasonal swings), there can be a material impact on pricing.

Transaction Comps: Pros and Cons

• Implied value is determined by the prices paid in real-life to purchase similar companies
• The implicit assumption is that buyers are rationale, yet poor decisions are often made in M&A, namely overpaying
• Multiples-based approach with an estimated “control premium” – which can be very practical in terms of providing pricing guidance
• Limited public information about M&A makes the process more challenging and time-consuming
• Comparable acquisitions can function as a frame of reference for participating parties, i.e. insights from similar deals
• The necessity for transaction recency and  occurrence in relatively similar market conditions further reduces the pool of comps

Transaction comps analysis typically yields the highest valuation because it looks at valuations for companies that were acquired – meaning that a control premium is included in the offer price.

A control premium is defined as the amount that an acquirer paid over the unaffected market trading share price of the company being acquired, typically expressed as a percentage.

As a practical matter, a control premium is necessary to incentivize existing shareholders to sell their shares and forego their ownership.

Control premiums, or “purchase premiums,” are paid in the vast majority of M&A deals and can be quite significant, i.e. can be as high as 25% to 50%+ above unaffected market prices.

In the absence of a reasonable control premium, it is unlikely that an acquirer will be able to obtain a controlling stake in the acquisition target, i.e. the existing shareholders typically need an extra incentive that compels them to give up their ownership.

Hence, the multiples derived from transaction comps (and the implied valuations) tend to be the highest when compared to the valuations derived from trading comps or standalone DCF valuations.

A key benefit to transaction comps is that the analysis can provide insights into historical control premiums, which can be valuable points of reference when negotiating the purchase price.

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Precedent Transactions vs. Comparable Company Analysis

The credibility of a precedent transaction analysis is contingent on the selection of comparable transactions that involve similar companies and occurred in similar market conditions.

However, finding comparable companies and their transaction comps tends to be much more challenging than finding pure trading comps.

Unlike trading comps, where public companies are obligated to file their financial reports (10-Q, 10-K) periodically, companies and M&A participants are under no obligation to publicly announce the details of an M&A transaction.

The discretionary nature of information disclosure in M&A results in frequently “spotty” data.

But while the valuation range from a transaction comps analysis is often seen as a more realistic assessment of the actual purchase prices paid, transaction comps are vulnerable to how buyers can (and frequently do) make mistakes.

The phrase “less is more” and “quality of quantity” applies to transaction comps, since a handful of truly comparable transactions will be more informative than a long list of random transactions included purely for the sake of building a large peer group.

Precedent Transaction Analysis Calculator – Excel Template

We’ll now move to a modeling exercise, which you can access by filling out the form below.

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Transaction Comps Analysis Model Example

Suppose we are attempting to determine the valuation of a potential acquisition (”TargetCo”).

The financial data of TargetCo can be found below:

• Current Share Price = \$50.00
• Total Shares Outstanding = 1 million
• LTM Revenue = \$50 million
• LTM EBITDA = \$10 million
• LTM Net Income = \$4 million
• Net Debt = \$2 million

Since earnings per share (EPS) is equal to net income divided by the number of shares outstanding, TargetCo’s LTM EPS is \$4.00.

• LTM Earnings Per Share (EPS) = \$4 million Net Income / 1 million Total Shares Oustanding
• LTM EPS = \$4.00

In the next step, we are provided with a table of the peer group’s valuation multiples.

TV / LTM Revenue TV / LTM EBITDA Offer Price / EPS
Comp 1 2.0x 10.0x 20.0x
Comp 2

1.6x

9.5x 18.5x
Comp 3 2.2x 12.0x 22.5x
Comp 4 2.4x 10.6x 21.0x
Comp 5 1.5x 8.8x 18.0x

In practice, the valuation multiples will be linked to other tabs where the metrics were calculated separately, but for illustrative purposes, the numbers are just hard coded in our exercise.

Given those assumptions, we can now summarize the data of the comparable transactions using the following Excel functions.

Comps Summary Table – Excel Functions
• Minimum → “=MIN(Range of Multiples)”
• 25th Percentile → “=QUARTILE(Range of Multiples,1)”
• Median: “=MEDIAN(Range of Multiples)”
• Mean → “=AVERAGE(Range of Multiples)”
• 75th Percentile → “=QUARTILE(Range of Multiples,3)”
• Maximum → “=MAX(Range of Multiples)”

Since there are no clear outliers, we’ll use the mean here – but whether we use the median or mean does not make a meaningful difference.

We now have the necessary inputs to calculate the transaction value and implied offer value (i.e. equity value) of TargetCo.

In order to get from the transaction value (TV) to the offer value (i.e. equity value), we must subtract net debt.

• Implied Offer Value = Transaction Value (TV) – Net Debt

Under the multiples derived from our comparable transactions analysis, we arrive at the following approximate valuations.

1. TV / Revenue = \$97 million – \$2 million Net Debt = \$95 million
2. TV / EBITDA = \$102 million – \$2 million Net Debt = \$100 million
3. Offer Price / EPS = \$80 million

According to our completed exercise, the implied offer value is an offer value in the range of \$80 million to \$100 million.

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