In Defense of Fairness
Opinions: An Empirical Review of Ten Years of Data
Posted by Robert Bartell and Christopher
Janssen, Duff & Phelps, on Wednesday, April 19, 2017
Robert Bartell is Global Head of Corporate Finance and
Christopher Janssen is Global Head of Transaction Opinions at
Duff & Phelps. This post is based on a Duff & Phelps publication.
the utility of fairness opinions have periodically seized headlines for many
years. As the leading fairness opinion advisor, we can readily speak to the
value of the opinions we provide and the best practices we observe in rendering
them. But when addressing broad industry criticisms—in particular that fairness
analyses generally provide valuation ranges too wide to be useful and that they
are too reliant on “mechanical” discounted cash flow (DCF) analyses—our
arguments have lacked the force of empirical data beyond our own client work.
now. This post—the compilation, review and analysis of more than 3,000
fairness opinions—is the culmination of our efforts to address those
criticisms with research. We believe it does that.
We also believe
that the post itself can serve as a valuable tool for boards evaluating purchase
fairness opinions have long been left to rely on their own intuition and
experience in scrutinizing valuation estimates. Our post provides them with a
set of benchmarks, drawn from federal filings, for comparison. They’ll now know
when a fairness opinion’s estimate falls outside the average valuation range
against the offer price for similar-sized deals. Our post should empower
directors to ask more informed questions, which can only improve the process of
deliberating a purchase offer.
We don’t expect
our study to put an end to the debate around fairness opinions. We do believe it
can help elevate that debate by injecting data where there has only been
conjecture, by replacing the anecdotal with the empirical and by better
equipping boards to make informed decisions.
Fairness Opinions 2006-2016
opinions use a robust set of methodologies to produce a useful range of
valuations, according to Duff & Phelps’ study of more than 3,000 publicly
disclosed fairness opinions.
disprove periodic criticisms that fairness opinions generally provide little
utility for boards analyzing potential transactions. Specifically, some critics
have asserted that fairness analyses produce valuation ranges too wide to
provide meaningful information and that, because most fairness opinions are
based in part on DCF analysis, the opinions are too reliant on financial
projections that have been produced by management and left unscrutinized by the
We agree that
narrower valuation ranges are, intuitively, more useful to boards than wider
ranges. However, some deals are likely to produce wide ranges because the
companies themselves are difficult to value. The real question is whether wide
ranges are pervasive. And while we would also agree that relying solely on DCF
analysis (that uses projections company management has fed to the fairness
advisor) can be problematic, the follow-up should be to ask: is that really
In an effort to
answer those questions, assess the validity of periodic criticisms and determine
the overall usefulness of fairness opinions, Duff & Phelps conducted a thorough
analysis of more than 3,000 fairness opinions filed with the SEC during the
ten-year period ending in 2016. Specifically we looked at forms 14D and DEFM14A,
which companies are required to file when they are the target of a purchase
offer or require a shareholder vote.
A Valuable Tool for Boards
To test whether
wide ranges are pervasive, we analyzed publicly disclosed fairness analyses over
the last ten years. Our analysis confirms that on average, fairness opinions
deliver a range of valuations that is sufficiently narrow to serve as a valuable
tool in evaluating purchase offers. And the average range grows narrower as deal
size grows larger. Among deals we analyzed that carried a value of $10 billion
or more, DCF analyses produced average price ranges between 78 percent and 106
percent of the offer price. Large-cap companies typically are more diversified
and established, with more stable and predictable cash flows and broader
equity-analyst coverage. Armed with multiple, reliable sets of financial
projections and a variety of perspectives on the company’s future performance,
fairness opinion advisors can be expected to produce more precise valuation
ranges than when this information is absent.
In the charts
above and below, valuation ranges are expressed as average percentages of the
implied share prices as compared to the offer price. The average range widened
only slightly for deals valued at less than $10 billion but more than $100
million. For deals valued at less than $100 million, DCF analyses produced
average price ranges between 65 percent and 105 percent of the offer prices. The
difference in average valuation ranges for micro-cap companies versus large-cap
companies is even more pronounced when we analyze the dispersion of fairness
opinion ranges. As the chart below illustrates, as company size decreases, the
widest 25% of valuation ranges increases.
observation—wider and more disperse valuation ranges for smaller companies—is
not all that surprising. This reflects the heightened complexity involved in
valuing enterprises that are less mature, have less historical data to analyze
and compare, or are growing at a rate that causes dramatic variances in expected
voluminous published analyses, including our own
Valuation Handbook—Guide to Cost of Capital,
 have shown that
discount rates decrease as company size increases due to the diminishing effects
of small-stock premiums. That research helps explain our finding that micro-cap
companies receive the broadest valuation ranges.
Methodologies: Rigor and
present clear signs of an industry standard at work among fairness opinion
advisors. Counter to the criticism that fairness opinions rely too heavily on
DCF analysis, we find that fairness advisors have been using multiple
methodologies for some time. For instance, 91 percent of the fairness opinions
we reviewed used more than one methodology to arrive at valuations. In 75
percent of the deals, advisors used three or more methodologies.
Moreover, we also
observed a slight increase in the average number of methodologies since 2008,
from an average of 3.3 methodologies to nearly 3.5 in 2016.
We argue that the
use of multiple valuation methodologies also significantly mitigates the
criticism that DCF analysis and therefore the opinion could be too heavily
influenced by unrealistic company projections. The common pairing of
public-company comparables and/or precedent transactions with DCF analyses,
often supplemented by one or more additional methodologies, demonstrates that,
in the vast majority of cases, fairness opinion advisors diligently consider
multiple perspectives and relevant analyses, when available, in assessing the
fairness of transaction prices. It also dispels the notion that fairness
advisors do not scrutinize management projections. Simply put, if the DCF
analysis produced a valuation range that bore little resemblance to a range of
values derived from other methodologies, that would be the first clue that
something might be amiss and thus warrants a closer look. After all, if the
public peer group or the set of precedent transactions is sufficiently
comparable, valuation multiples derived from these techniques can, in many
cases, provide an inherently more objective view of valuation.
To test our
assertion that a confirmatory valuation technique can serve as an effective
check on the DCF analysis, we also analyzed those fairness analyses that used
both DCF and public-company comparables. In the fairness opinions we reviewed,
DCF analysis usually provided the narrowest range of values. For deals valued at
below $10 billion, DCF analysis provided slightly narrower ranges of values than
public-company comparables analyses; for the largest of deals the ranges were
circumstances, a significantly wider public-company comparables range may
indicate that a fairness opinion advisor overlooked a key step in that analysis.
In order to achieve a useful valuation based on public multiples, it’s crucial
that the advisor calibrate the selection of valuation multiples to those peers
with risk profiles and growth prospects similar to the subject company—to the
extent that such comparisons are sufficiently meaningful. Absent that
refinement, valuation ranges may be wider than necessary and in some cases
misleading. The data we collected showed that overall the public-company
comparables and DCF analyses produced relatively consistent ranges that were
reasonably narrow, particularly for larger companies where more information was
available. The consistency of the average valuation ranges across DCF and
public-company comparables analyses confirms the rigor and validity of both
methodologies. When done correctly, neither examination is mechanical and both
illuminate appropriate valuation ranges to boards and special committees.
Multiple DCF Scenarios
Indicate Additional Scrutiny
In 43 percent of
the filings we analyzed, fairness opinion advisors used multiple cases of DCF
analyses. This most likely indicates an attempt to account for multiple sets of
projections used for different purposes by management. One might reflect stretch
goals, for example, while another may have been produced to make the company
more attractive to buyers. Yet another forecast may use an amalgamation of
consensus projections from equity analysts to represent the market’s assessment
of the company’s prospects.
practitioners subscribe to the theory that DCF analysis should reflect the best
estimates available to management, without bias in either direction. The
frequent use of multiple DCF scenarios indicates that advisors are considering
every potentially pertinent projection, rather than simply accepting a single
set of forecasts. In addition, the presentation of two (or more) DCF scenarios
is likely the result of a growing judicial emphasis—via suggestion and
mandate—on disclosure. Companies today are less likely to pick and choose which
projections to disclose than they were a decade ago. Those who counsel boards of
directors may conclude that erroring on the side of complete disclosure—even if
a certain forecast included in regulatory filings was prepared for a much
different purpose than assessing fairness—is generally prudent for the filer.
Choice of Advisor Matters
study reveals that valuation ranges vary by provider. Among the most active
advisors, the tightest average range, at 23 percentage points, is nearly twice
as narrow as the broadest range of 41 percentage points. This demonstrates that
the choice of an advisor does impact the precision and usefulness of a given
fairness opinion and illustrates the importance of following the best practices
described above—calibrating public-company comparables and scrutinizing
Even as fairness
opinions have become standard practice, critics have questioned their efficacy
and usefulness. The criticism often surfaces in the wake of particular
transactions where there is public disagreement on the deal price or controversy
surrounding the fairness analysis, which generates widespread headlines. But our
analysis shows that those instances are outliers, typically owing to
peculiarities in circumstances more than to faults in the process.
The vast majority
of fairness opinions offer valuation indications that fall within 15 percentage
points on either side of a midpoint—a clear indication of a widespread industry
standard with robust methodologies and highly calibrated valuation analyses. For
the minority of fairness analyses that fall outside of this precise range, it’s
important to note that many of those outliers also may represent useful
valuation assessments. Not all companies fit neatly into valuation models and
not all deals are structured the same. When fairness opinions account for such
unique factors, we would expect them to produce price ranges that stray from the
indicates that fairness opinion advisors use robust, sophisticated methods to
reach those valuations. From this we can only conclude that, broadly speaking,
fairness opinions represent a reliable way for corporate boards and executives
to evaluate purchase offers.
This post relies
on data we collected from public filings available in the U.S. Securities and
Exchange Commission EDGAR database covering the timeframe January 1, 2006,
through September 30, 2016.
are expressed as average percentages of the implied share prices as compared to
the offer price.
Electronic Data Gathering, Analysis, and Retrieval system, allows collection,
validation, indexing, acceptance, and forwarding of submissions by companies and
others who are required by law to file forms with the SEC.
collected from the following forms:
documents filed by the “being acquired” company regarding the offer it received.
documents filed after the date of filing original document (SC 14D9) that may
have amendments to the original content or new exhibits.
statement relating to merger or acquisition” as required under Section 14(a) of
the Securities Exchange Act of 1934.
Harvard Law School Forum
on Corporate Governance and Financial Regulation
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