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Financial analysts and the evaluation of corporate acquisitions: Survey
evidence on IFRS knowledge, analyst experience, and the use of accounting
information for company valuation purposes
Abstract
The conceptual framework that IFRS is based on emphasises the need for understandability, i.e. that
users have a reasonable degree of relevant knowledge and study the financial information diligently.
This paper reports results from a survey examining financial analysts’ knowledge of accounting
standards related to acquisitions [IFRS 3 (Business combinations) and IAS 36 (Impairment of assets)]
and their use of such accounting information for company valuation purposes. The analysts’
communication with clients is emphasised and the sample is limited to analysts with experience of
evaluating acquisitions. The results suggest that the financial analysts, on average, have relatively low
knowledge of the relevant standards, but still place much importance on information reported in
accordance with these standards when evaluating the impact of acquisitions on company valuation.
Separating the sample based on analyst experience revealed differences regarding client communication
behaviour and the use of valuation measures. Separating the sample into more knowledgeable and less
knowledgeable analysts showed that the latter group was more inclined to let their valuations be
influenced by goodwill impairment. Moreover, as the less knowledgeable analysts stated to have a high
use of the discounted cash flow (DCF) model, this raises questions regarding how they deal with
complex accounting issues when applying the DCF model. The observed pattern of analysts relying on
complex accounting information despite having relatively low knowledge of the corresponding
standards, is discussed in the paper in relation to the literature on analyst incentives and their use of use
non-sophisticated valuation methods.
Key words: acquisition, financial analyst, goodwill, IFRS, impairment, company valuation,
accounting information, analyst forecasts, acquisition analysis
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1. Introduction
The international accounting standards on business combinations and post-acquisition goodwill
treatment that came into force in 2005 (IFRS 3/IAS 36)1 have been described as ‘…complex standards
that brought far-reaching changes for European companies…’ (Glaum, Schmidt, Street, & Vogel, 2013,
p. 167). The post-implementation review of IFRS 3 initiated by the International Accounting Standards
Board (IASB) in 2013 has made the Board concerned about key aspects of the standard (IASB, 2015).
Both archival (e.g. Shalev, 2009; Chen, Krishnan, & Sami, 2015; Knauer & Wöhrmann, 2015) and
experimental research (e.g. Hopkins, Houston, & Peters, 2000; Hellman, Andersson, & Fröberg, 2016)
suggest that investors and analysts are influenced by the way accounting standards portray acquisitions
made, both at the date of purchase and during the subsequent period. The IASB requires standards to be
useful to capital market participants but the Board also states that users should have a reasonable degree
of financial knowledge and are responsible for studying the information with reasonable diligence
(IASB, 2010). Against this background, the current paper investigates financial analysts’ knowledge of
IFRS 3 and IAS 36 and their use of such accounting information for company valuation purposes.
Financial analysts act as information intermediaries between companies and investors when it comes to
evaluating the effects of corporate acquisitions. In general, investors on the stock market tend to place
considerable reliance on financial analysts’ research, forecasts and recommendations (Barber, Lehavy,
McNichols, & Trueman, 2001; Krishnan & Booker, 2002; Mikhail, Walther, & Willis, 2007). Prior field
research suggests that accounting information plays a primary role in anchoring professional investors’
and financial analysts’ valuation-related opinions about companies (Barker, 1999; Barker & Imam,
2008). As learned by many during the Enron, WorldCom and Lehman Brothers debacles, this implies a
need for accounting knowledge relevant to the specific context of the company analysed. Still, it has
been questioned how sophisticated analysts really are in terms of accounting knowledge and diligent
1 International Financial Reporting Standard (IFRS) 3 Business Combinations and International Accounting
Standard (IAS) 36 Impairment of Assets. Similar standards had been adopted in the USA a few years earlier.
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use of accounting information (Bréton & Taffler, 1995). One reason may be that sell-side analysts have
economic incentives to increase trade and investment banking business (e.g. Baik, Farber, & Petroni,
2009) and may not find investments in knowledge and diligent use of accounting information to be
worthwhile. A recent study by Bischof, Daske, & Sextroh (2014) investigates financial analysts’
treatment of fair value-related topics in connection with investment evaluations of banks – a task
requiring analyst knowledge of accounting in a complex area. The study is based on content analysis of
824 conference calls held by 95 banks applying IFRS and 552 analyst reports related to these conference
calls. The results show that analysts varied with regard to how they treated fair value-related information
in their forecasts and communicated reports, but it was difficult to identify the causes of this variation.
The current study relates to Bischof et al. (2014) in that it investigates analysts’ use of accounting
information for company valuation purposes in an area where the accounting standards are complex.
Our approach is however different in three ways: (i) we explicitly relate the analyst’s level of accounting
knowledge to her/his use of accounting information in the company valuation context; (ii) we study a
different area of accounting (corporate acquisitions), and (iii) we adopt a different methodological
approach. With regard to the third point, a questionnaire was designed for the purpose of studying
analysts’ knowledge of relevant IFRSs in the area of acquisitions (IFRS 3 and IAS 36), their use of such
accounting information for the evaluation of acquisitions, their use of valuation-related measures, and
their communication of such information to clients. The sample consists of Swedish financial analysts
with experience of evaluating acquisitions.
In sum, the results point at some paradoxes. First, the IFRS knowledge level was surprisingly low given
the fact that the study focused exclusively on analysts who had experience of evaluating acquisitions.
Only about one third of the analysts perceived they knew the standards on business combinations and
impairment tests fairly well or very well. About 40 per cent stated that they knew the standards not well
at all or to a slight, or very slight, extent. On average, the analysts’ levels of knowledge of IFRS 3 and
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IAS 36 corresponded to the response alternative ‘to some extent’. In terms of understandability, low
knowledge is a problem in itself but also in terms of being an obstacle for diligent use of accounting
information. Second, the less knowledgeable analysts tended to use the reported acquisition analysis
information at least as much as the more knowledgeable analysts. This raises concerns in the sense that
analysts may lack sufficient accounting knowledge but will still act as financial advisers in the area in
question (acquisitions in this case). Third, with regard to goodwill impairment tests, the less
knowledgeable analysts were more inclined to let their valuations be influenced by reported goodwill
impairment losses. Thus, analysts who knew more about how the goodwill impairment tests are
performed considered reported impairment loss information to be of relatively less importance from an
company valuation point of view. As more IFRS knowledge corresponded with less use, this raises
questions regarding the usefulness of the reported impairment information.
In the paper, we discuss what may cause the counter-intuitive result that professional analysts rely
extensively on complex accounting information despite low knowledge. We believe some insight can
be gained by comparing with the results of prior research on analysts’ use of valuation methods, where
unsophisticated methods (i.e. valuation multiples based on, for example, short-term earnings forecasts)
are reported to be used extensively (Demirakos, Strong, & Walker, 2004; Imam, Chan, & Shah, 2008),
despite the fact that the superiority of sophisticated models is well established and presumably well
known by analysts. We argue that the reasons suggested in the literature, regarding why analysts prefer
simple valuation techniques, i.e. ability to communicate with clients, economic incentives, distrust in
numbers relying heavily on long-term assumptions, may to some extent be the same as the reasons why
analysts rely on accounting information where they know little about the underlying principles. For
example, analysts’ investments in accounting knowledge and diligent use of accounting information
may not be perceived as paying off as well as time spent on developing news stories to the market (cf.
Barker & Imam, 2008).
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The remainder of the paper is organised as follows. The second section provides a review of the relevant
literature. The third section presents research propositions whereas the fourth section includes a
description of the applied methodology and documents the responses to the questionnaire. The results
are presented in the fifth section. The sixth section discusses the limitations of the study and concludes.
2. Literature review
2.1 Users’ understanding of complex accounting information
In the past, user characteristics have been much emphasised in conceptual frameworks of accounting.
In the International Accounting Standards Committee Framework (IASC, 1989),2 understandability was
stated to be one of the four principal qualitative characteristics that makes financial statements
information useful to users (together with relevance, reliability and comparability). Preparers should
strive for understandability, but, in addition, users were expected to have reasonable knowledge of
business and economic activities and accounting and to be willing to study the information with
reasonable diligence (ibid., p. 25).3 Relevant information about complex matters should not be excluded
merely on the grounds that it might be too difficult for certain users to understand (ibid.),4 which might
be interpreted as a de facto higher knowledge requirement than ‘reasonable knowledge’. In the
prevailing version of the conceptual framework, prepared jointly by the IASB and FASB (IASB, 2010),
understandability is included as a so called enhancing qualitative characteristic of financial reporting
(together with comparability, verifiability and timeliness) instead of being a fundamental characteristic
(i.e. relevance and faithful representation). The idea of enhancing qualitative characteristics is to
distinguish more useful information from less useful information, but the information must always be
useful (relevant and faithfully represented) in the first place. According to the basis for conclusions
2 The IASC Framework was subsequently adopted by the International Accounting Standards Board (IASB) in
2001. 3 A similar approach was applied in Concepts Statement 1 in the U.S. (FASB, 1978, p. 34). It follows from the
Basis of Conclusions of the IASB 2010 Conceptual Framework that this formulation regarding user knowledge
comprises a demand for reasonable degree of financial (accounting) knowledge (IASB 2010, BC 3.40-3.41). 4 This is in line with the arguments put forward in Concepts Statement 2 (FASB, 1980), where understandability
is high up in the hierarchy of desirable accounting qualities.
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(ibid., BC 3.40–3.43), one of the reasons for downgrading understandability in comparison with
fundamental characteristics is to clarify the extensive responsibilities of users with regard to complex
accounting information, e.g. it is not enough for users to be willing to study reported financial
information with reasonable diligence but they must actually do so. The boards also suggest that users
may need to seek the aid of advisers to understand economic phenomena that are particularly complex.
One may argue that economic phenomena and corresponding accounting standards have grown more
complex over time (financial instruments, business combinations, share-based payment etc.) and it is
therefore necessary for users to advance their knowledge and/or seek advice. It has not been considered
a viable option to strive for less complexity just in order to make more users comprehend the meaning
of the information. However, the position taken by the boards implies that the prevailing framework has
increased the demands on users’ knowledge and ability to comprehend information in financial reports
with a high degree of complexity. The boards primarily refer to users as capital providers whereas
financial analysts act as advisers to capital providers. One may assume that capital providers are
expected to turn to financial analysts in situations when the underlying economic phenomena are
particularly complex and fewer users understand the financial information depicting those phenomena.
According to prior research, the effectiveness of communication based on financial reports depends on
the complexity of the content as such (its readability) and users’ capacity to extract the relevant message
based on the interaction between content and user (its understandability) (Patel & Day, 1996, p. 140).
Measures of readability (e.g. sentence length, word length) and understandability (e.g. the ability of
subjects to fill in missing words correctly) have been applied in accounting research since the 1970s
(e.g. Adelberg, 1979; Patel & Day, 1996; Jones & Smith, 2014). Research in this area suggests that
preparers will vary with regard to the readability and the understandability of the information they
present, with some tendency of more obfuscation in connection with the reporting of ‘bad’ news (e.g.
Courtis, 2004). Users, on the other hand, will differ with regard to their cognitive abilities to comprehend
information. For example, Patel and Day (1996) show that individuals with the same accounting
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education, but different cognitive styles, may differ significantly in their abilities to understand complex
accounting information. The boards (IASB and FASB) associate the concept of understandability with
users who have a reasonable knowledge of business and economic activities and who review and analyse
the information diligently (IASB, 2010, QC32, emphasis added). There is thus a gap between what are
the key aspects of understandability according to the boards (knowledge and diligent use) and the
operationalised variables for readability and understandability that are used in research, where the
preparer-related aspects are emphasised (word length, sentence length etc.) and knowledge is
presumably a component of an individual’s ability to comprehend when applying the, so called, Cloze
test and similar methodologies (successful reproduction of the missing words from a selected passage)
(Jones & Smith, 2014). Diligent use of information is not in focus in this line of research, but more of a
hygiene variable in the experimental designs. The boards’ approach shows some similarity with the
reasoning used in audit theory, where the quality of audit services is viewed to depend in part on the
auditor’s ability to discover breaches in the client’s accounting system (DeAngelo, 1981).5 In turn, this
ability depends on the auditor’s competence and the quantity of inputs devoted to the audit (Watts &
Zimmerman, 1986, p. 314). Competence and knowledge are closely related concepts whereas the
‘quantity of inputs’ (e.g. the audit time budget) corresponds well with diligent use of information. The
concept of knowledge is not defined by the boards but the reference to financial advisers in QC32 (IASB,
2010) as individuals who have the ability to understand complex economic phenomena would suggest
that the expertise knowledge held by such advisers also incorporates practical experience of using such
complex information.
What do we know about financial analysts’ knowledge and comprehension of complex accounting
information? Prior research suggests that technical knowledge (e.g., knowledge about accounting
standards) is necessary for expert users to become successful, but only up to a certain level; for example,
5 DeAngelo (1981) writes (p. 186): “The quality of audit services is defined to be the market-assessed joint
probability that a given auditor will both (a) discover a breach in the client’s accounting system, and (b) report the
breach.” The reporting of the breach is related to the auditor’s independence.
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research in the audit area has shown that technical knowledge is associated with better performance at
lower organizational levels, whereas superior performance higher up in the hierarchy was distinguished
by tacit managerial knowledge (Tan & Libby, 1997). There is no corresponding study of financial
analysts, but the above results might suggest that technical knowledge in the accounting and finance
area will be important for junior analysts whereas other forms of knowledge will also be required to
become a top-ranked senior analyst. When people have better knowledge they tend to search for
information in a ‘directed’ rather than ‘sequential’ manner and this leads to improved performance
(Barrick & Spilker, 2003). This is likely to be of particular importance in decision contexts where issues
are complex and task-relevant technical knowledge must be applied during the information search
(ibid.). Financial analysts have been found to develop such task-specific knowledge which enable them
to search more quickly for relevant information in a direct, non-sequential, way (Bouwman, Frishkoff,
& Frishkoff, 1987; Frederickson & Miller, 2004). They could be expected to be guided by experience
in terms of being able to mentally access knowledge of similar or related situations when solving a
judgment or decision task (cf. Hopkins, 1996, p. 35). For example, when being exposed to an acquisition
announcement it would seem important for an analyst to have, and to be able to mentally access, the
accounting knowledge needed in order to be able to quickly evaluate the financial consequences for the
acquirer, such as the pieces of information influencing earnings per share, goodwill and indebtedness of
the acquirer.
2.2 Financial analysts’ processing of information
In addition to the factors related to understandability described so far, the decision context must also be
taken into account, i.e., for what purpose the analyst will use the information (e.g. to develop forecasts,
to make investment recommendations), and what the incentives are in connection with this task.
Abhyaywansa, Aleksanyan, & Bahtsevanoglou (2015) investigate sell-side analysts’ use of intellectual
capital information in company valuation. The authors adopt a broad perspective and use a framework
where information is sought to influence analysts’ decisions or opinions at six different stages: (1)
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Overall opinion about the company, (2) Forecasting of value drivers and valuation inputs, (3) Valuation
model application, (4) Price target justification or moderation, (5) Justification of investment
recommendation, and (6) One-to-one client discussions. The first three stages point at a use of
information that follow logically from a traditional model of fundamental analysis, i.e. to develop a
thorough understanding of the company and then provide a realistic business scenario that can be
converted into the financial numbers required by the applied valuation model. However, the three latter
stages have also been observed to have strong influence on analysts’ use of information. In particular,
Brown, Call, Clement, & Sharp (2015) reports that analysts face strong incentives to satisfy their
investing clients through communication where analyst credibility plays a major role.
Accounting information plays an important role both during the late and the early stages of the
Abhyaywansa et al. (2015) framework. Bouwman, Frishkoff, & Frishkoff (1995) studed the role of
GAAP-based information and found that such information primarily serves a screening function in order
to quickly eliminate unattractive investment alternatives whereas the GAAP-based information
appeared less important for developing positive investment cases. Accordingly, many subsequent
studies have examined financial analysts’ use of non-financial information for company valuation
purposes and identified contexts where such information is particularly important (e.g. Orens & Lybaert,
2010). A combined view is offered by Barker & Imam (2008) who conclude that although non-
accounting information may be widely used by analysts, accounting information is still highly relevant
(p. 314):
...accounting-based information nevertheless plays an important role in anchoring and constraining analysts’
views. Specifically, we find that in cases where analysts are positive on accounting aspects of earnings quality,
they are ‘free’ to be either positive or negative on non-accounting aspects, but that if they are negative on
accounting aspects, then they are, in effect, constrained to be negative overall.
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Thus, financial analysts will always use accounting numbers when framing their analyses but will go
beyond these numbers when developing their cases. This would seem to require ongoing ‘investments’
in technical accounting knowledge and devoting time to use the accounting information with diligence.
During the first three stages of the Abhyaywansa et al. (2015) framework, financial analysts will use
information for the purpose of making an equity valuation. On the basis of a literature review, Ramnath,
Rock, & Shane (2008) concluded that research has not been able to adequately explain analysts’ stock
market valuations by using theoretically feasible valuation models, such as the discounted cash flow
(DCF) model. In line with this conclusion, studies based on interviews, questionnaires, and analyst
reports have found that analysts also frequently use less sophisticated comparable-based valuation
techniques to a great extent, such as the price-to-earnings (PE) ratio comparisons (Barker, 1998; 1999;
2000; Demirakos et al., 2004; Imam et al., 2008; 2013; Brown et al., 2015). The reasons why analysts
use less sophisticated methods are related to aspects of the decision context not fully captured by the
traditional model of fundamental analysis. First, the analyst needs to communicate the analysis and
convince the client about the result. In the framework by Abhyaywansa et al. (2015), this takes place in
connection with providing price target justification or moderation (stage 4), justification of investment
recommendation (stage 5) and during one-to-one client discussions (stage 6). For example, the analyst
may choose a valuation model that their clients expect them to use or is currently ‘in fashion’ (Imam et
al., 2008). In addition, analysts are observed to frequently rely on intellectual capital information, for
example, information about management quality when providing justification of valuations and
recommendations to clients (Abhyaywansa et al., 2015). Such information is often difficult to reliably
transform into quantified inputs in the sophisticated model, but may still be perceived by clients as viable
arguments why, for example, higher valuation multiples may be justified for certain companies. In
particular, the results reported by Barker (1999) point at analysts’ unwillingness to accept that the
terminal value component, which typically accounts for a very large part of the total value in
sophisticated valuation models, is determined without any evident connection to the current company
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situation. Current earnings multiples may be perceived as less uncertain long-term projections of
terminal value compared to general assumptions of interest rates and GDP growth.
As described above, there is logical demand for accounting information and the use of sophisticated
company valuation models during the first three stages of the Abhyaywansa et al. (2015) framework,
but for the development of an investment recommendation with an expected share price development
that will convince the client, the analysts seem to rely less on accounting information and sophisticated
models. One would expect analysts’ incentives to play an important role for what information they
perceive worthwhile collecting and processing. As information intermediaries, financial analysts can
potentially mitigate agency problems associated with corporate financing and investment decisions,
however, research has also pointed at problems related to analysts’ incentives resulting in opportunistic
use of accounting information, optimistic forecast bias and inadequate analyst pressure on companies
for growth (e.g. Baik et al. 2009; Doukas, Kim, & Pantzalis, 2008; Cowen, Groysberg, & Healy, 2006).
In a similar vein, Barker & Imam (2008) relate their results to analysts’ economic incentives to generate
trading volume and to maintain good contacts with companies (p. 326):
Prior research suggests that analysts’ economic incentives lead them to introduce news to the market in order
to generate commission income and to show a favourable bias towards companies. Analysts are therefore
drawn towards making greater relative use of non-accounting-based information, because it is inherently
subjective and more amenable to variation in opinion and to the generation of news. When using accounting-
based information, analysts are particularly sparing in their use of negative references to earnings quality,
because these are more readily verifiable and demonstrably inconsistent with analysts’ inherent bias in favour
of companies. Overall therefore, positive and non-accounting-based references to earnings quality are most
common, which is evidence that analysts use information opportunistically.
The results presented by Barker & Imam (2008) suggest that analysts may behave somewhat
opportunistically in their use of both accounting and non-accounting information for the purpose of
developing coherent investment cases. Knowledge of accounting standards and diligent reading of
information based on accounting standards might not be considered as worthwhile investments in this
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context. This reasoning may be related to the large variation in analysts’ treatment of financial
instrument reclassifications observed in the study by Bischof et al. (2014) referred to earlier. Bischof et
al. (2014) studied banks’ conference calls and related analyst reports from the first quarter 2008 until
the fourth quarter 2010 and they observe that analysts’ interest in the banks’ fair value accounting
practices vary considerably between the highest quarter (fourth calendar quarter 2008) when many
questions were asked during the conference calls compared to the second calendar quarter of 2010 when
almost no questions were asked. This indicates that the analysts were particularly interested in the
accounting information when they could use it to support a particular investment case. Next, the results
of Bischof et al. (2014) showed that there was large variation with regard to how analysts treated
financial value related information for valuation purposes (p. 365):
While some analysts add back unrealised fair value changes of reclassified assets going forward, others adjust
their predictions of different earnings components because the profit and loss (P&L) effects of reclassified
assets shift from trading into interest income and impairments.
The authors suggest that there is no standard processing of the fair-value related information in the
analysts’ decision processes because the decision usefulness is likely to be context-specific. The
discussion earlier in this section suggests that another possible reason may be that some analysts have
more knowledge about what the accounting numbers are capturing and put more effort into making a
consistent and relevant classification of the financial statements effects whereas there are other analysts
who do not have well-founded opinions on fair value measurement of financial instruments due to lack
of knowledge of accounting in this area and/or insufficient reading of the relevant notes. The former
group are presumably dominating the group of analysts who ask questions about fair value issues during
the conference calls. With regard to the latter group, lack of knowledge or diligent use might be caused
by insufficient economic incentives to make such ‘investments’.
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2.3 Evaluation of corporate acquisitions
Acquisitions are often big enough to have significant long-term cash flow effects and therefore affect
the fundamental company value according to sophisticated valuation methods. Furthermore, the short-
term impact of acquisitions on earnings and PE ratios will be influenced by, for example, the purchase
price allocation and how the analyst chooses to define earnings. An analyst’s earnings forecast refers
directly to accounting information and represents a visible and concrete outcome. Analysts’ forecasts
have received much attention in prior research, but already two decades ago Schipper (1991) pointed at
the risk of focusing too much on the output of the forecasting process (properties of the forecasts as
such) rather than the inputs to analysts’ processing of information. Accounting information plays a key
role in such processing since the forecasts must adhere to the format and the accounting principles
applied by the company being analysed. It is common for analysts to work with spreadsheet models that
comprise the history and the future of the analysed firms’ operating segments and consolidated financial
statements. Each quarter, the financial analyst gets the outcome of the previous quarter, which provides
feedback on the previous forecast and forms a basis for forecast revisions.
Analysts need to consider acquisitions when making forecasts; they could be characterised as discrete
corporate events with potentially major effects on the future strategic and financial development of the
acquiring firm. There is much research on stock market reactions to corporate acquisitions, most often
in the context of evaluating whether or not they are successful (e.g. Moeller, Schlingemann, & Schultz,
2005). Research on stock market data also suggests that investors may be subject to behavioural bias
when reacting to corporate events such as acquisitions (Kadiyala & Rau, 2004). The new approach to
accounting for acquisitions under both U.S. GAAP (SFAS 141 and 142) and IFRS (IFRS 3 in
combination with IAS 36) introduced in the beginning of the new millennium implied that acquisition
premiums should, to a greater extent compared to prior practice, be allocated to the target’s identifiable
assets and liabilities at their fair values, and goodwill should no longer be amortised but become subject
to periodical impairment tests. The pooling method was prohibited.
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Information about acquisitions is announced in stages. Assuming no insider information, an analyst will
typically first receive information about an acquisition from the acquirer’s press release, followed by
information at the public presentation, the following quarterly report, the prospectus, and the subsequent
annual report. Pieces of information from the purchase price allocation (e.g. the amount of goodwill)
are often announced early on, but the complete acquisition analysis may not be reported until the annual
report is published. With regard to purchase price allocation, the new standards for business
combinations, both under IFRS and US GAAP, have been criticised for relying too much on unverifiable
values and giving management too much discretion (e.g. Glaum et al., 2013; Ramanna & Watts, 2012;).
One example concerns the purchase price allocation that management undertakes in the acquisition
analysis in order to identify previously unrecognised intangible assets such as brands or product rights;
to make fair value adjustments of identifiable assets and liabilities; and to determine the goodwill
amount. On the basis of a study of 1,019 business combinations in the USA, Shalev (2009) reports that
companies that allocated lower proportions of the purchase price to identifiable net assets had lower
levels of disclosure. In line with disclosure theory, Shalev interpreted this as a downplaying of ‘bad
news’ for investors, as lower allocation to identifiable net assets increased post-acquisition earnings per
share. Results from experimental research suggest that financial analysts are materially affected by the
acquisition accounting method chosen by the preparer (Hopkins et al., 2000; Hellman et al., 2016
Later on in the process, analysts can follow up on previously made acquisitions in order to evaluate
whether they were successful. This may affect analysts’ forecasts and valuations. From an accounting
point of view, this relates to the impairment tests of goodwill and other acquired assets, where there is
much empirical research suggesting deficient accounting quality and insufficient information content
for users (e.g. Ramanna, 2008; Hamberg, Paananen, & Noval, 2011; Petersen & Plenborg, 2010). In a
study by Li, Shroff, Ventkataraman, & Zhang (2011), the authors compare goodwill impairments with
the economics of the original acquisitions for which goodwill was paid and find that, on average, firms
who announce goodwill impairment losses may have overpaid for targets at the time of the original
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acquisition. Chen et al. (2015) investigates the impact of goodwill impairment on analyst forecasts. They
find that analyst forecasts are impaired following the disclosure of goodwill impairments. They write
(p. 144):
Our results indicate that although financial analysts may also incorporate goodwill impairment information
into their forecasts, the forecasts are less accurate and more dispersed. From this perspective, our paper is in
line with Ramanna (2008) [...] who argue that the unverifiable nature of goodwill impairments enables
managers to exercise their discretion in recording the impairments.
Similar conclusions were drawn by Bens, Heltzer, & Segal, (2011) based on an extensive empirical
study of SFAS 142. In sum, the information related to the acquisition analysis based on IFRS 3 (or the
US counterpart SFAS 141) and the impairment test of goodwill based on IAS 36 (or the US counterpart
SFAS 142) is clearly comprehensive and complex, both to prepare and to use.
3. Research propositions
3.1 Communication with clients
We expect financial analysts to focus both on the company’s value based on fundamental analysis (cf.
Abhyaywansa et al., 2015, stages 1-3) and the development of an investment case that will convince the
client about the expected share price development (cf. Abhyaywansa et al., 2015, stages 4-6). The use
of fundamental analysis is well established, but empirical findings further point at the importance of
satisfying clients (e.g. Brown et al., 2015) and generating trading income (Barker & Imam, 2008). We
therefore believe financial analysts will also put much on both the fundamental analysis and the expected
share price development in their communication with clients.
Two situations where financial analysts will communicate with their clients are: (1) when presenting the
results of a full analyst report based on a comprehensive analysis of an industry with various listed
companies, and (2) when responding to an event, such as a quarterly report announcement from a listed
company. It is plausible that analysts will adopt a more long-term perspective in the first context (growth
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and profitability prospect for the industry) and a more short-term perspective in the second context
(updating of quarterly and annual earnings forecasts, short-term share price reactions). Based on this
difference in time perspective, we expect financial analysts to have stronger focus on fundamentals when
communicating with clients in first context, and a stronger focus on the expected share price
development in the second context. On the basis of this, we will evaluate the following research
propositions:
RP 1A: In a situation where the financial analyst has made a comprehensive analysis of an industry,
the financial analyst’s client communication will focus more on the fundamental analysis than on the
expected share price development.
RP 1B: In a situation where the financial analyst is responding to a quarterly report announcement,
the financial analyst’s client communication will focus more on the expected share price
development than on the fundamental analysis.
Furthermore, based on the literature review, we expect professional and experienced financial analysts
to have task-specific knowledge which enable them to search for relevant information in a direct non-
sequential way, and to be able to mentally access knowledge of similar or related situations when solving
tasks. However, the literature provides little guidance on how analysts deal with the issue of
communicating with clients. As referred to in Section 2.2, research from the auditing area attributed
superior performance at the high organizational levels to tacit managerial knowledge rather than
technical knowledge. We believe it is plausible to assume that one form of ‘tacit managerial knowledge’
for financial analysts is the ability to successfully communicate with clients. Accordingly, we believe
financial analysts who have more experience will, in general, be better at communicating with clients
compared to analysts with less experience. The next question is how this will show. A greater ability to
communicate with clients might involve a stronger focus on the expected share price development as
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this is of much interest to the client. At the same time, share prices are affected by many factors and in
order to generate credibility (cf. Brown et al., 2015) it may be better for the analyst to focus on the
development of company fundamentals. On the basis of this, we will evaluate the following research
proposition:
RP 2: Financial analysts with more working experience will communicate with clients differently
compared to financial analysts with less experience.
We will evaluate this proposition with regard to the emphasis on expected share price development
versus the company’s value based on fundamental analysis, and for both the situations referred to in
research proposition (RP) 1.
3.2 Analysts’ knowledge of accounting standards
Based on the literature review, it seems reasonable to assume that financial analysts can be considered
information users who are expected to fulfil the IASB requirement of having reasonable accounting
knowledge. Furthermore, prior experimental research has suggested that financial analysts have task-
specific knowledge of the kind associated with effective search behaviour and problem-solving. This
applies also to technically complex areas. There are factors implying that experienced analyst might not
devote enough time to stay updated on accounting standards (more critical knowledge for junior
analysts, insufficient economic incentives), however, we believe the following research proposition is
the most plausible one:
RP 3: Financial analysts (with experience of evaluating the effects of corporate acquisitions) will
have a stated knowledge level of IFRS 3 and IAS 36 which is high.
18
3.3 Analysts’ valuation approaches
The literature review suggests that analysts use a combination of sophisticated valuation methods (e.g.
the DCF model) and less sophisticated methods (e.g. various valuation multiples). In relation to the
Abhyaywansa et al. (2015) framework, we expect the former methods to dominate during stages 1-3,
while the less sophisticated methods will be more used when aiming to convince the client about the
attractiveness of the investment. In Section 3.1, we described two situations when analysts will
communicate with their clients, i.e. (1) following a comprehensive analysis and (2) in response to a
quarterly report announcement. With regard to the choice of valuation approach, we propose that
analysts will favour a more sophisticated approach (discounted cash flow) in situation 1 and a less
sophisticated approach (earnings development) in situation 2. On the basis of this, we will evaluate the
following research proposition:
RP 4A: In a situation where the financial analyst has made a comprehensive analysis of an industry,
the financial analyst’s company valuations will primarily focus on discounted cash flows.
RP 4B: In a situation where the financial analyst is responding to a quarterly report announcement,
the financial analyst’s company valuations will primarily focus on earnings development.
Following the same reasoning as in Section 3.1, there may be ‘tacit managerial knowledge’ for financial
analysts with regard to the choice of valuation approach in different situations. Accordingly, we believe
financial analysts who have more experience will, in general, be better in choosing the adequate
valuation approach for the situation at hand. On the basis of this, we will evaluate the following research
proposition:
RP 5: Financial analysts with more working experience will choose valuation approaches differently
compared to financial analysts with less experience.
19
We will evaluate this proposition with regard to the two situations referred to in RP 4.
3.4 Analysts’ use of accounting information for valuation purposes
On the basis of the literature review, we expect financial analysts to use accounting information quite
extensively – earnings forecasts constitute a key output of analysts’ work, their investment cases will
need to incorporate accounting aspects, and valuation methods require the use of accounting data. With
regard to the last point, the sophisticated valuation models put high demands on the analyst’s accounting
knowledge as the analyst must use input data at a detailed level which will require understanding of
complex accounting information (e.g. how to deal with the separately acquired intangibles in the area
of acquisitions). We therefore expect the use of more sophisticated methods to be positively correlated
with higher accounting knowledge. We formulate the following research proposition.
RP 6: Financial analysts who are more knowledgeable of international accounting standards will use
more sophisticated valuation measures than less knowledgeable analysts, when evaluating the effects
of corporate acquisitions.
Analysts are expected to have high accounting knowledge, corresponding to their role of being financial
advisers in line with the IASB framework. Although they may choose to disregard accounting
information considered too complex or too ambiguous, we posit the following research propositions to
be plausible:
RP 7: Financial analysts (with experience of evaluating the effects of corporate acquisitions) will
assign high importance to accounting information concerning ‘acquisition analysis’ (IFRS 3) when
appraising the acquirer’s share.
20
RP 8: Financial analysts (with experience of evaluating the effects of corporate acquisitions) will
often take accounting information concerning ‘acquisition analysis’ (IFRS 3) into account when
evaluating corporate acquisitions.
RP 9A: Financial analysts (with experience of evaluating the effects of corporate acquisitions) will
often take annual report descriptions of impairment tests into account in their work.
RP 9A: Financial analysts (with experience of evaluating the effects of corporate acquisitions) will
often take into account in their analysis whether the acquiring company will report future impairment
on goodwill accounting information.
It is plausible that the analysts who choose to invest more time in gaining accounting knowledge will
also find this information more important compared to less knowledgeable analysts. We will evaluate
the following research propositions.
RP 10: Financial analysts who are more knowledgeable of international accounting standards will
take the acquisition analysis into account to a greater extent than less knowledgeable analysts, when
evaluating the effects of corporate acquisitions.
RP 11: Financial analysts who are more knowledgeable of international accounting standards will
assign higher importance to the detailed items of the acquisition analysis than less knowledgeable
analysts, when evaluating the effects of corporate acquisitions.
With regard to the following up of previously made acquisitions, the analyst must find ways to capture
the outcome of these acquisitions in the valuation. For an analyst who knows IAS 36 very well this may
not necessarily imply that the valuation will be closely linked to the impairment losses reported by the
21
company, as the impairment tests may lack validity (cf. Ramanna & Watts, 2012). We therefore refrain
from stating any research propositions concerning the relationship between accounting knowledge and
the use of impairment-related information.
As discussed earlier in this section, more experienced analysts may differ from less experienced ones as
‘tacit managerial knowledge’ may be needed in order to become successful and stay on the job (cf. Tan
& Libby, 1997). This may result in variation in the use of valuation measures, and the use of acquisition
analysis information, when evaluating the effects of corporate acquisition. In line with RP 3 and RP 5,
we will evaluate the following research propositions:
RP 12: Financial analysts with more working experience will differ from analysts with less
experience as regards their use of valuation measures when evaluating the effects of corporate
acquisitions.
RP 13: Financial analysts with more working experience will differ from analysts with less
experience as regards the extent to which they take the acquisition analysis into account when
evaluating corporate acquisitions.
RP 14: Financial analysts with more working experience will differ from analysts with less
experience as regards their use of information from the acquisition analysis, when evaluating the
effects of corporate acquisitions.
4. Methodology
Based on the literature review, we believe the complexity of the standards regarding accounting for
acquisitions, and the IASB’s expectations on users, provide a rationale for studying financial analysts’
knowledge and practical use of acquisition-related accounting information. In addition, although there
22
is much prior research on analysts’ forecasts and accounting information, there appears to be room for
more survey-based research focusing on financial analysts’ handling of accounting information in
connection with specific corporate events such as acquisitions.
We use survey methodology to investigate the questions of interest outlined above. We constructed a
web-based questionnaire (with the Qualtrics Survey Software); several drafts were produced and tested
by four PhD students in the finance and accounting area and one financial analyst. The final survey,
which is in Swedish and available upon request, comprised four blocks of questions pertaining to the
areas referred to in Section 2.6 Specifically, the respective contents of the blocks were as follows:
Block 1: In all, this block had 14 questions. The first six questions concerned background details (e.g., age,
gender, education, job characteristics, and analyst certification). Then came two questions on whether the
respondent analysed the effects of corporate acquisitions in her/his present job and had performed such analyses
in prior jobs. The block ended with six questions aimed to measure knowledge of IFRS in general and two
specific standards: IFRS 3 and IAS 36. The knowledge of each standard was measured in two ways: First, the
respondent was asked to rate how well s/he knew the standard on a six-point scale with verbal anchors ranging
from ‘Very little’ to ‘Very much’. Second, s/he rated how good his/her knowledge was in comparison to her/his
colleagues on a seven-point scale with verbal anchors ranging from ‘much worse’ to ‘much better’.
Block 2: In all, this block included questions pertaining to use of accounting information in the evaluation of
corporate acquisitions. Three questions concerned the extent to which the respondents considered the
acquisition analysis and the impairment tests of goodwill in their work. One question concerned whether the
analyst conducted follow-up analyses regarding the outcome of corporate acquisitions. These questions were
separately answered on seven-point scales with verbal anchors ranging from ‘never’ to ‘always’. The block
ended with a question that prompted the respondent to rate the respective importance of seven items (i.e.,
6 There was also a fifth block of questions concerning two psychological measures, which pertains to another study
where people with different occupations are compared. These measures and their results are not described in this
paper.
23
consideration transferred, the size of the goodwill amount, the amortisation period, the size of the intangible
assets, and intangible assets in the form of product rights, brands, and customer relations) from the acquisition
analysis using a seven-point scale with verbal anchors ranging between ‘not important at all’ and ‘extremely
important’.
Block 3: This block had three questions of which two prompted the respondent to state to what extent he/she
agreed with two statements about the significance of impairment tests. Agreement was measured on a five-
point scale ranging from ‘strongly disagree’ to ‘strongly agree’. The third question asked the respondent to
report on a seven-point scale (with the anchors ‘never’ and ‘always’) her/his use of five financial measures
(i.e., discounted cash-flow, EV/EBITDA, EV/EBIT, EV/sales, price / book value, and P/E-ratio) when
evaluating the effects of corporate acquisitions.7
Block 4: This block prompted the respondent to state how s/he would act in two hypothetical situations: (1) in
response to a quarterly report announcement from a company and (2) after conducting a comprehensive
analysis of an industry. For each situation, the respondent was asked to rate her/his degree of agreement with
four statements of which two related to the communication with clients and two concerned the appraisal of the
company. The degree of agreement was rated on a five-point scale (ranging from ‘strongly disagree’ to
‘strongly agree’).
It should be noted that Blocks 2–4 of the survey only appeared to the respondent if s/he evaluated
corporate acquisitions in her/his current work or had experience of such evaluations. Otherwise the
respondent was automatically directed to the end of the questionnaire (i.e., Block 5).
For the distribution of the survey we cooperated with the Swedish Society of Financial Analysts
(Sveriges Finansanalytikers Förening, SFF), which embodies professionals active in the sphere of
qualified financial analysis within Sweden and is also a member of the European Federation of Financial
7 EV refers to enterprise value, which is the sum of the market capitalisation and the fair value of debt. EBIT refers
to the operating profit (earnings before interest and tax).
24
Analyst Societies (EFFAS). The general secretary of SFF distributed the survey as a web link in a short
e-mail where he briefly described the research study and called for the members of the society to
respond. The e-mail was sent out on December 16, 2010, and the timing was chosen in order to avoid
the corporate reporting periods, when analysts’ workload is high. The response period was December
16 to February 10, 2011. Two reminder e-mails were sent out by the general secretary. The survey was
distributed to the 1,131 members of SFF. Eight e-mails did not reach the receiver (undeliverable), 768
never opened the e-mail, and 355 ‘read’ the e-mail. Out of the latter group, 112 individuals opened and
started to answer the survey. Sixty-seven of them claimed that they analysed the effects of corporate
acquisition as part of their work.8 However, all of the 67 analysts did not respond to all four blocks of
questions. In order, the following numbers of respondents were observed for Blocks 1, 2, 3, and 4: 61,
53, 49, and 42. Thus, some 42 analysts, who worked with analyses of the effects of corporate acquisition,
completed the whole survey, meaning the actual response rate was about 3.7%.9 Rather than reporting
only the responses from this group, we will rely on varying number of respondents (ranging from 67 to
42) depending on whether they answered the respective question.
Admittedly, the response rate of the present study is somewhat poor, but should be viewed in light of
the following circumstances. According to Sax et al. (2003), web surveys generally have lower response
rates than paper surveys. The high opportunity cost of the surveyed population may also be a major
reason for the low response rate. A relatively recent study investigating how professional investors and
8 Obviously, the respondents who did not work with analyses of the effects of corporate acquisitions were not the
targeted subjects for the present study and, thus, they did not obtain the relevant questions. In short, those
respondents had the following characteristics: 26% were females, mean age = 46.9, mean years of experience as
financial analysts = 8.8, and 53% had no certification. 9 Analyses of the responses to the questions in Block 1 with regard to the 42 analysts who completed the whole
survey and the 27 analysts completing only parts of the survey, suggested that the two groups had similar
background details except for the perceived knowledge of IFRS 3. Specifically, the former group seemed to have
significantly better knowledge of this standard compared to the latter group (means = 4.02 vs. 3.25, SDs = 1.41
vs. 1.52, t = -2.00, p = 0.05). Tentatively, poor knowledge of IFRS 3 might have affected the response rate.
25
advisors perceived the decision usefulness of various financial accounting measurement concepts, which
relates to the present study, yielded a response rate of 1.9% (Gassen & Schwedler, 2010).
{Insert Table 1 about here}
As shown by Table 1 the response sample includes a notable variety among the financial analysts in
terms of work experience and fields of work (henceforth referred to as respondents). The latter implies
that their incentive structures may differ and that their ‘customer categories’ varies and do not only
include institutional investors. This must be taken into account when interpreting the results. There is
generally a weak tradition of analyst certification in Sweden and therefore the relatively low share of
analysts holding the Swedish (AFA), European (CeFA) or American (CFA) certificates is not that
surprising, but worth noting.
5. Findings
5.1 Communication with clients
In Section 3.1, we argued that financial analysts will need to focus both on analysing company
fundamentals and on developing attractive investment cases involving expectations on future share price
development. The results in Table 2 show that, in their communication with clients, the respondents
agree with the statement that they focus on “how the company’s value based on fundamental analysis
will develop in the future” (average score of 4.0), whereas they are hesitant to the statement that they
focus on “how the company’s share will develop in the future” (average score of 3.3).
{Insert Table 2 about here}
In a situation where the financial analyst has made a comprehensive analysis of an industry, the results
suggest (Table 2) that the client communication is more focused on the fundamental analysis outcome
26
(M = 3.95) compared to the expected share price development (M = 3.33). This result supports RP 1A.
In a situation where the financial analyst is responding to a quarterly report announcement, the results
suggest (Table 2) that the client communication is also more focused on the fundamental analysis
outcome (M = 4.07) compared to the expected share price development (M = 3.35). This result is
opposite to RP 1B.
In sum, the studied analysts tended to put much emphasis on the outcome of their fundamental analyses
in communication with clients. The measures for the two decision situations were strongly correlated (r
= 0.77, p < 0.01), indicating that the respondents were prone to base their client communication on this
information regardless of the situation. The expected share price development was, on average, less
emphasised in the communication with clients. Again, the measures for the two decision situations were
strongly correlated (r = 0.93, p < 0.01), suggesting that the respondents relied on similar information
regardless of situation.
In line with the reasoning behind RP 2, there was a tendency for more experienced analyst to focus more
on the expected share price development in their communication with clients. For the comprehensive
analysis situation, this difference in focus between more and less experienced analysts was significant
(Ms = 3.81 vs. 2.94).
Overall, the results reported in this section would appear to be consistent with a communication context
where all analysts in all situations strive to generate credibility by focusing on company fundamentals,
but, more experienced analysts will to a greater extent add their views on the expected share price
development. The impact of acquisitions on the analysts’ use of accounting information must consider
the context. When an acquisition is first announced, the amount of accounting information is generally
very limited, but the analyst must still give her/his views very quickly on expected share price effects
and with regard to the impact on company fundamentals.
27
5.2 Analysts’ perceived knowledge of accounting related to acquisitions
Table 3 reports the results from the survey concerning the financial analysts’ perceived accounting
knowledge.
{Insert Table 3 about here}
Table 3 shows that the respondents’ perceived general knowledge about IFRS corresponded to ‘very
well’ (8 respondents, 13%), ‘fairly well’ (25 resp., 40%), ‘to some extent’ (26 resp., 42%), ‘to a slight
extent’ (1 resp., 2%), or ‘to a very slight extent’ (2 resp., 3%). The perceived knowledge of the specific
standards IFRS 3 and IAS 36 was lower. About 30 per cent of the respondents perceived they knew
IFRS 3 and IAS 36 ‘fairly well’ or ‘very well’, whereas about 45 per cent only perceived they knew
these standards ‘to some extent’ or less. The average score corresponded to the respondents knowing
IFRS 3 and IAS 36 ‘to some extent’. The three measures concerning perceived knowledge of IFRS,
IFRS 3, and IAS 36 correlated strongly with each other (0.62 < r < 0.80, p < 0.01), but were unrelated
to years of experience as financial analysts. As the responses only pertain to analysts who analyse
acquisitions as a part of their work (have experience of evaluating the effects of corporate acquisitions),
their perceived average level of knowledge may be interpreted as weaker compared to the IASB’s
expectations concerning understandability, referred to in Section 2.1. Thus, RP 3 is not supported.
Table 3 further shows that the respondents perceive they have, on average, about as good (or even
slightly better) knowledge as their colleagues of IFRS 3 and IAS 36. According to the table, the
respondents also perceived they had better general knowledge of IFRS compared to the more detailed
standards related to acquisitions. Those three measures were also strongly related (0.75 < r < 0.84, p <
0.01).
28
Finally, Table 3 shows that the level of knowledge of IFRS 3 and IAS 36 were unrelated to the number
of years of experience as financial analysts, i.e. the data do not support that more experienced analysts
were more knowledgeable. If it was a key success factor to be knowledgeable of IFRS 3 and IAS 36 for
analysts evaluating acquisitions, more experienced analysts would have invested in such knowledge,
however, the results indicate that such investments in accounting knowledge may not be viewed as being
of primary importance.
The variation in perceived knowledge in Table 3 is notable and in Section 5.4 we will analyse further
whether the variation in knowledge level is correlated with the analysts’ use of acquisition-related
information and their valuation measures. As the three measures of knowledge of accounting standards
were highly correlated, an index variable was constructed by averaging those measures. This variable
had a strong degree of reliability (Cronbach’ alpha = 0.86). Using median-split the respondents were
then divided into two groups: less knowledgeable and more knowledgeable of accounting standards (n
= 36 vs. 26; Ms = 3.31 vs. 5.10; SDs = 0.74 vs. 0.57).10 Those two groups will be used in the following
sections.
5.3 Financial analysts’ valuation approaches
In line with the findings of the literature review in Section 2.2, the results reported in Table 4 suggests
that the respondents tended to use both earnings-based valuation and DCF valuation (average scores
around 4 on the 5-grade scale for both of the valuation approaches).
{Insert Table 4 about here}
We argued that analysts would focus more on the sophisticated approach (DCF) in connection with the
comprehensive analysis (RP 4A) and more on the less sophisticated approach (earnings development)
10 ‘Accounting standards’ refer to index variable based on responses for IFRS in general, IFRS 3 and IAS 36.
29
when responding to a quarterly report (RP 4B). There was no empirical support for such a difference in
valuation approach depending on the situation. Across the two situations, each measure was strongly
correlated (r = 0.76, p < 0.01), indicating that the respondents tended to make their valuations similarly
in both situations. Contrary to the results related to client communication, there was no marked tendency
for experienced analysts to prefer either earnings-based valuation or DCF, i.e. RP 5 was not supported
by the data. Thus, although experience appears to have an impact on client communication
considerations, this cannot be traced to any differences in the valuation approach.
5.4 Analysts’ use of accounting information when evaluating acquisitions
Table 5 suggests that the respondents, when evaluating acquisitions, took both DCF and various
multiples into account to a quite high extent (between 4.59 and 5.47 on the seven-grade scale). DCF and
EV/EBIT received the highest average scores (5.44 and 5.47), whereas Price-to-Book received the
lowest (4.59). The average values for the EV/EBITDA, the EV/Sales, and the PE ratio were somewhat
in between (5.36, 4.94 and 4.78, respectively).
{Insert Table 5 about here}
Both the frequent use of non-sophisticated measures and the combined use of multiples and DCF appear
to be well in line with the results reported in the literature review. The responses to the questions
concerning the valuation measures were also analysed with respect to the aforementioned index variable
of perceived knowledge of accounting standards and experience as financial analysts.
{Insert Table 6 about here}
Firstly, as shown in Table 6 there were no significant differences between the respondents with greater
knowledge and lesser knowledge of the accounting standards. On the whole, the two groups rated their
30
use of the measures equally and RP 6 was not supported by the data. One important observation is that
the less knowledgeable analysts will still use DCF to a great extent (M = 5.42 on the 7-point scale). This
raises questions of how they deal with complex accounting issues when entering such input data into
the model.
Secondly, Table 6 also shows that the respondents with more experience of working as financial analysts
tended to a significantly greater extent consider four of the five financial measures (discounted cash
flow, EV/EVITDA, EV/EBIT, and PE-ratio) than the less experienced respondents. In general, the more
experienced analysts use both sophisticated and non-sophisticated valuation measures to a greater extent
than the analysts with less experience. As reported in Section 5.1, all analysts seemed to focus on
company fundamentals in their communication with clients, but the more experienced analysts tended
add their views on the expected share price development to a greater extent. The results from Table 6
suggest that the more experienced analysts are also different in another dimension (in line with RP 12),
namely that they generally use valuation measures to a greater extent.
Let us now turn to the questionnaire results related to the acquisition analysis reported by the acquirer.
{Insert Table 7 about here}
Table 7 suggests that the valuations made by the respondents were ‘to some extent’ affected by the
acquisition analysis (M = 4.11 on the 7-point scale) which is below the expected level according to RP
7 (‘high importance’). However, there was considerable variation among the respondents as 47%
assigned moderate, high or very high importance to the acquisition analysis. Furthermore, Table 7 also
shows that the acquisition analysis was taken into account ‘often’ (M = 5.02 on the 7-point scale) for
the evaluation of acquisitions, which is in accordance with the expected level according to RP 8. Even
higher levels of importance were assigned to some of the individual items of the acquisition analysis are
reported (Panel B of Table 7). Information about the ‘Consideration transferred’, ‘Size of the goodwill
31
amount’ and ‘Size of the intangible assets’ received the highest average scores (6.40, 5.42 and 5.26,
respectively, on the 7-grade scale), whereas ‘Customer relations’, ‘Amortisation period’, and ‘Product
rights’ received the lowest (4.79, 4.79, and 4.98, respectively). The average for ‘Brands’ was 5.00.
We expected financial analysts who are more knowledgeable of international accounting standards to
take the acquisition analysis into account to a greater extent than less knowledgeable analysts (RP 10),
but no significant difference could be was identified between the groups (Ms = 4.96 vs. 5.07, Table 7,
Panel A). This implies that the analysts with less knowledge of the relevant accounting standards still
used such information to a quite high extent.
{Insert Table 8 about here}
It was also expected that the respondents’ perceived importance of acquisition analysis prepared in
accordance with IFRS 3 would be positively related to their perceived knowledge of IFRS, IFRS 3 and
IAS 36 (RP 11). As shown by Table 8 no statistical significant differences could be observed between
the respondents with more knowledge of the aforementioned accounting standards and those with less
knowledge. This implies that the analysts with less knowledge of the relevant accounting standards still
assigned high importance to such information. Interestingly, the less knowledgeable analysts seemed to
be a more homogeneous group than the more knowledgeable, as indicated by the fact that standard
deviations were somewhat lower for the former group.
Neither RP 13 nor RP 14 were not supported by the data as there was no significant difference between
more and less experienced analysts with regard to the extent of using the acquisition analysis (Ms = 4.85
vs. 5.16, Table 7, Panel A) and no significant differences between more and less experienced analysts
with regard to the items in the acquisition analysis (see Table 8).
32
5.5 Following up on previously made acquisitions
We would expect analysts to follow up on previously made acquisitions in order to evaluate whether
they were successful. As reported in Table 9, the average response for this question is between
‘sometimes’ and ‘often’ (M = 4.58) even though the sample only consists of analysts with experience
of acquisitions. One might speculate that the relatively low tendency to follow up could be related to the
difficulty of distinguishing previously made acquisitions in the subsequent financial reports, where they
become part of bigger cash-generating units.
{Insert Table 9 about here}
Table 9 shows that the average respondent took future goodwill impairment into account ‘often’ in their
analyses (M = 5.07 on the 7-grade-scale). The degree of use of the annual reports information on
impairment was rated somewhat lower (M = 4.58). Both these results are at the expected level according
to RP 9A and RP 9B (‘often’).
Seventy per cent stated ‘disagree’ or ‘strongly disagree’ to the statement: ‘The valuation of companies
that have made many acquisitions is not affected by the impairment of goodwill and other intangibles.’
This suggests that the actual reporting of impairment losses was of high importance for company
valuation purposes. At the same time, some analysts still made forecasts of a hypothetical amortisation
of goodwill. Roughly 38% of the respondents agreed to the statement: ‘When I evaluate a company, I
make forecasts of hypothetical amortisation of the acquired goodwill.’ One reason for this could be to
maintain comparability with the accounting treatment of goodwill before the adoption of IFRS.
Table 9 further shows that the less knowledgeable analysts were more strongly influenced by reported
impairment losses as the more knowledgeable analysts. This raises the question of whether analysts with
less knowledge of the relevant accounting standards rely too strongly on such information.
33
6. Discussion and concluding remarks
Summing up, financial analysts are expected to be knowledgeable, experienced, diligent users of
accounting information. We know that experts in general, including financial analysts, have the ability
to mentally access task-relevant information when solving problems. However, we also know that
analysts have to cope with the fact that preparers may present complex information in deliberately
obscure ways and that differences in cognitive style will cause greater obstacles for some individual
analysts. Furthermore, the analysts must be able to communicate successfully with clients, considering
also economic incentives of generating trading volume.
Equity investors place considerable reliance on financial analysts’ research, forecasts and
recommendations. Being such important information intermediaries, the analysts need to understand the
interplay between firm strategies, financial reporting, and corporate valuation. Corporate acquisitions
represent challenging events for analysts in that there is often insufficient information and analytical
difficulties concerning how to appraise the valuation effects. Accounting standards related to
acquisitions are complex and financial analysts may not have sufficient knowledge, or do not study the
financial reports diligently enough, to understand the reported information. A high degree of accounting
knowledge in the area of acquisitions will make it easier to evaluate the impact of acquisitions on
accounting numbers. The degree of knowledge and the level of using acquisition-related accounting
information may also be related to the analyst’s approach to company valuation. Prior research suggest
that analysts will generally rely both on sophisticated multi-period valuation techniques and/or less
sophisticated comparisons of valuation multiples (Demirakos et al., 2004; Imam et al., 2008). We
investigate the relationship between the preference for various valuation measures and the use and
knowledge of acquisition-related accounting information.
On the basis of survey evidence, we find that the analysts’ stated level of knowledge of IFRS 3 and IAS
36 corresponded to the response alternative ‘to some extent’ which was below the available alternatives
34
of knowing the standards ‘fairly well’ or ‘very well’. Considering the fact that the sample was restricted
to analysts with experience of evaluating acquisitions, we believe this suggests that the analysts had
lower-than-expected levels of knowledge and diligent use. In contrast, we find that analysts have a
relatively high use of information from the acquisition analysis prepared in accordance with IFRS 3.
Separating the sample into more and less knowledgeable analysts showed that the latter group was more
inclined to let their valuations be influenced by goodwill impairment, but in most cases the differences
between the two groups were not significant. As the less knowledgeable analysts stated to have a high
use of the DCF model, this raises questions regarding how they deal with complex accounting issues
when entering such input data into the model. Finally, we find that the analysts’ communication with
clients is characterised by a general focus on company fundamentals, but, more experienced analysts
will to a greater extent add their views on the expected share price development. The more experienced
analysts also tended to place higher importance on both more and less sophisticated valuation measures.
The IASB expects primary users and their advisors to understand and diligently use of financial reports,
however, the results of this survey do indicate high use but lower than expected knowledge. Why is this
so? One possible reason relates to the results presented by Barker and Imam (2008), where analysts
behaved somewhat opportunistically in their use of both accounting and non-accounting information for
the purpose of developing coherent investment cases. In this context, investments in accounting
knowledge and diligent use of accounting information will not always pay off. This may explain why
analysts have not invested in gaining high knowledge in accounting for acquisitions despite having to
use such information for company valuation purposes. The results reported by Bischof et al. (2014)
showed similar indications as there were large variation in analysts’ treatment of financial instrument
reclassifications in their study.
35
References
Abhayawansa, S., Aleksanyan, M., & Bahtsevanoglou, J. (2015). The use of intellectual capital
information by sell-side analysts in company valuation. Accounting and Business Research, 45(3), 279–
306.
Adelberg, A. H. (1979). A methodology for measuring the understandability of financial report
messages. Journal of Accounting Research, 17(2), 565–592.
Baik, B., Farber, D. B., & Petroni, K. (2009). Analysts’ incentives and street earnings. Journal of
Accounting Research, 47(1), 46–69.
Barber, B., Lehavy, R., McNichols, M., & Trueman, B. (2001). Can investors profit from the prophets?
Security analyst recommendations and stock returns. Journal of Finance, 56(2), 531–563.
Barker, R. G. (1998). The market for information – evidence from finance directors, analysts and fund
managers. Accounting and Business Research, 29(1), 3–20.
Barker, R. G. (1999). The role of dividends in valuation models used by analysts and fund managers.
European Accounting Review, 8(2), 195–218.
Barker, R. G. (2000). FRS3 and analysts’ use of earnings. Accounting and Business Research, 30(2),
95–109.
Barker, R., & Imam, S. (2008). Analysts’ perceptions of ‘earnings quality’. Accounting and Business
Research, 38(4), 313–329.
Bens, D., Heltzer, W., & Segal, B. (2011). The information content of goodwill impairments and SFAS
142. Journal of Accounting, Auditing and Finance, 26(3), 527–555.
Bischof, J., Daske, H., & Sextroh, C. (2014). Fair value-related information in analysts’ decision
processes: Evidence from the financial crises. Journal of Business Finance & Accounting, 41(3–4), 363–
400.
36
Bouwman, M. J., Frishkoff, P. A., & Frishkoff, P. (1987). How do financial analysts make decisions?
A process model of the investment screening decision. Accounting, Organizations and Society, 12(1),
1–29.
Bouwman, M. J., Frishkoff, P., & Frishkoff, P. A. (1995). The relevance of GAAP-based information:
a case study exploring some uses and limitations. Accounting Horizons, 9(4), 22–47.
Bréton, G., & Taffler, R. J. (1995). Creative accounting and investment analyst response. Accounting
and Business Research, 25(98), 81–92.
Brown, L. D., Call, A. C., Clement, M. B., & Sharp, N. Y. (2015). Inside the ‘black box’ of sell-side
financial analysts. Journal of Accounting Research, 53(1), 1–47.
Chen, L. H., Krishnan, J., & Sami, H. (2015). Goodwill impairment charges and analyst forecast
properties. Accounting Horizons, 29(1), 141–169.
Courtis, J. K. (2004). Corporate report obfuscation: artefact or phenomenon? British Accounting Review,
36(3), 291–312.
Cowen, A., Groysberg, B. & Healy, P. (2006) Which types of analyst firms are more optimistic? Journal
of Accounting and Economics, 41(1–2), 119–146.
DeAngelo, L. E. (1981). Auditor size and audit quality. Journal of Accounting and Economics, 3(3),
183–199.
Demirakos, E., Strong, N., & Walker, M. (2004). What valuation models do analysts use? Accounting
Horizons, 18(4), 221–240.
Doukas, J. A., Kim, C. (F.), & Pantzalis, C. (2008). Do analysts influence corporate financing and
investment? Financial Management, 37(2), 303–339.
FASB. (1978). Statement of Financial Accounting Concepts No. 1: Objectives of Financial Reporting
by Business Enterprises.
37
FASB. (1980). Statement of Financial Accounting Concepts No. 2: Qualitative Characteristics of
Accounting Information.
Frederickson, J. R., & Miller, J. S. (2004). The effects of pro forma earnings disclosures on analysts’
and nonprofessional investors’ equity valuation judgments. The Accounting Review, 79(3), 667–686.
Gassen, J., & Schwedler, K. (2010). The decision usefulness of financial accounting measurement
concepts: Evidence from an online survey of professional investors and their advisors. European
Accounting Review, 19(3), 495–509.
Glaum, M., Schmidt, P., Street, D., & Vogel, S. (2013). Compliance with IFRS 3- and IAS 36-required
disclosures across 17 European countries: company- and country-level determinants, Accounting and
Business Research, 43(3), 163–204.
Groysberg, B., Healy, P. M., & Maber, D. A. (2011). What drives sell-side analyst compensation at
high-status investment banks. Journal of Accounting Research, 49(4), 969–1000.
Hamberg, M., Paananen, M., & Novak, J. (2011). The adoption of IFRS 3: The effects of managerial
discretion and stock market reactions. European Accounting Review, 20(2), 263–288.
Hellman, N., Andersson, P., & Fröberg, E. (2016). The impact of IFRS goodwill reporting on financial
analysts’ equity valuation judgements: some experimental evidence. Accounting & Finance, 56(1), 113–
157.
Hopkins, P. E. (1996). The effect of financial statement classification of hybrid financial instruments on
financial analysts’ stock price judgments. Journal of Accounting Research, 34(1), 33–50.
Hopkins, P. E., Houston, R. W., & Peters, M. F. (2000). Purchase, pooling, and equity analysts’
valuation judgments. The Accounting Review, 75(3), 257–281.
IASC. (1989). Framework for the Preparation and Presentation of Financial Statements, IASCF
Publications Department.
IASB. (2010). Conceptual Framework Phase A: Objectives and Qualitative Characteristics.
38
IASB. (2015). Post-implementation Review of IFRS 3 Business Combinations. Report and Feedback
Statement, IFRS Foundation. July.
Imam, S., Barker, R., & Clubb, C. (2008). The use of valuation models by UK investment analysts.
European Accounting Review, 17(3), 503–535.
Imam, S., Chan, J., & Shah, S. Z. A. (2013). Equity valuation models and target price accuracy in
Europe: evidence from equity reports. International Review of Financial Analysis, 28(1), 9–19.
Jones, M., & Smith, M. (2014). Traditional and alternative methods of measuring the understandability
of accounting narratives. Accounting, Auditing & Accountability Journal, 27(1), 183–208.
Knauer, T., & Wöhrmann, A. (2015). Market reaction to goodwill impairments. European Accounting
Review, forthcoming, DOI: 10.1080/09638180.2015.1042888.
Krishnan, R., & Booker, D. M. (2002). Investors’ use of analysts’ recommendations. Behavioral
Research in Accounting, 14(1), 129–156.
Li, Z., Shroff, P., Venkataraman, R., & Zhang, I. (2011). Causes and consequences of goodwill
impairment losses. Review of Accounting Studies, 16(4), 745–778.
Mikhail, M. B., Walther, B. R., & Willis, R. H. (2007). When security analysts talk, who listens? The
Accounting Review, 82(5), 1227–1253.
Moeller, S. B., Schlingemann, F. P., & Stultz, R. M. (2005). Wealth destruction on a massive scale? A
study of acquiring-firm returns in the recent merger wave. Journal of Finance, 60(2), 757–782.
Orens, R., & Lybaert, N. (2010). Determinants of sell-side financial analysts’ use of non-financial
information. Accounting and Business Research, 40(1), 39–53.
Patel, C., & Day, R. (1996). The influence of cognitive style on the understandability of a professional
accounting pronouncement by accounting students. British Accounting Review, 28(2), 139–154.
39
Petersen, C., & Plenborg, T. (2010). How do firms implement impairment tests of goodwill? Abacus,
46(4), 419–446.
Ramanna, K. (2008). The implications of unverifiable fair-value accounting: Evidence from the political
economy of goodwill accounting. Journal of Accounting and Economics, 45(2–3), 253–281.
Ramanna, K., & Watts, R. (2012). Evidence on the use of unverifiable estimates in required goodwill
impairment. Review of Accounting Studies, 17(4), 749–780.
Ramnath, S., Rock, S., & Shane, P. (2008). The financial analyst forecasting literature: A taxonomy
with suggestions for further research. International Journal of Forecasting, 24(1), 34–75.
Sax, L. J., Gilmartin, S. K., & Bryant, A. N. (2003). Assessing response rates and nonresponse bias in
web and paper surveys. Research in Higher Education, 44(4), 409–432.
Schipper, K. (1991). Analysts’ forecasts. The Accounting Horizons, 5(4), 105–131.
Shalev, R. (2009). The information content of business combination disclosure level. The Accounting
Review, 84(1), 239–270.
Tan, H.-T., & Libby, R. (1997). Tacit managerial versus technical knowledge as determinants of audit
expertise in the field. Journal of Accounting Research, 35(1), 97–113.
Watts, R. L., & Zimmerman, J. L. (1986). Positive Accounting Theory. Edgewood Cliffs, NJ: Prentice
Hall.
40
Tables
Table 1. Descriptive statistics for the response sample
Panel A: Age and years of experience n Mean Std. Dev. Min. Max.
Age (years) 67 44.77 7.75 31 66
Years of experience as financial analyst 47 14.12 7.80 3 35
Years on current job position 59 5.73 5.34 0 27
Panel B: Sex Frequency Percent
Male 56 85
Female 10 15
Total 66 100
Panel C: Analyst certification Frequency Percent
AFA, CeFA or CFA 27 41
No certification 39 59
Total 66 100
Panel D: Field of work Frequency Percent
Sell-side analyst 6 8
Buy-side analyst 4 5
Independent analyst 11 15
Credit analyst 9 12
Corporate finance 21 28
Portfolio management 11 15
Other 13 17
Total 75 100
Notes: The response sample only includes respondents who answered ‘yes’ to the question ‘Do you analyse the
effects of corporate acquisitions as a part of your work?’ This yields a sample size of observations. For Panel A,
a sample size below 67 indicates missing answers. With regard to Panel D, five respondents indicated multiple
fields of work. Other fields of work referred to as a variety of areas like CFO, Client Executive, Private Equity,
and research.
41
Table 2. Communication focus: share price development versus the company’s value development based on
fundamental analysis
n Mean Std.
Dev.
1 Strongly disagree
2
Disagree
3
Hesitant
4
Agree
5 Strongly
agree
In response to a quarterly
report announcement:a
In my communication with
clients I focus on how the
company's share will develop
in the future.
43 3.35 1.36 5 8 8 11 11
Analysts with more
experience
18
3.67
1.32
Analysts with less
experience
17
2.94
1.35
In my communication with
clients I focus on how the
company's value based on
fundamental analysis will
develop in the future.
45 4.07 0.84 1 1 5 25 13
Analysts with more
experience
18
3.83
1.10
Analysts with less
experience
17
3.94
0.94
After conducting a
comprehensive analysis:b
In my communication with
clients I focus on how the
company's share will develop
in the future.
42 3.33 1.20 4 7 8 17 6
Analysts with more
experience
16
3.81c
1.11
Analysts with less
experience
18
2.94c
1.21
In my communication with
clients I focus on how the
company's value based on
fundamental analysis will
develop in the future.
42 3.95 0.70 2 5 28 7
Analysts with more
experience
16
4.13
0.62
Analysts with less
experience
18
3.94
0.80
Notes: The responses to the statements were coded from one (strongly disagree with this statement) to five
(strongly agree with this statement). The groups of more experienced (M=20.4 years) versus less experienced
analysts (M=8.1 years) were constructed by a median split. The two groups did only significantly differ with
respect to one issue c.
a In full, the respondent was asked: Consider the following situation. A company that you follow has recently
announced a quarterly report. Indicate to what extent you agree with the below statements.
42
b In full, the respondent was asked: You have recently performed a comprehensive analysis of an industry
including a company that you follow. Indicate to what extent you agree with the below statements. c Denotes significant difference (t(1, 34) = 2.71, p=0.04).
43
Table 3. Knowledge of IFRSs: Own perception and comparison with colleagues
Panel A Own perceptions of knowledge of
IFRSs
n Mean Std. Dev. 1 Not well at
all
2 To a very
slight extent
3 To a slight
extent
4
To some extent
5 Fairly well
6 Very well
How well do you know the International
Financial Reporting Standards (IFRS)?
62 4.58 0.86 2 1 26 25 8
How well do you know IFRS 3 (Business
combinations)?
61 3.77 1.48 4 10 11 16 11 9
How well do you know about IAS 36
(Impairment)?
61 3.82 1.39 4 8 10 18 15 3
Panel B Perceived knowledge of IFRSs in
comparison with colleagues
n Mean Std. Dev. 1 Very much
worse
2 3 4 About the
same
5 6 7 Very much
better
How good is your knowledge of the
International Financial Reporting Standards
(IFRS) compared to your colleagues?
62 4.52 1.28 2 9 22 14 12 3
How good is your knowledge of IFRS 3
(Business combinations) compared to your
colleagues?
58 4.22 1.26 2 1 13 22 12 8 2
How good is your knowledge of IAS 36
(Impairment) compared to your colleagues?
59 4.2 1.24 3 10 26 10 9 1
Notes: The responses to the statements presented in Table 3, Panel A, were coded from one (not well at all) to six (very well). The responses to the statements presented in
Table 3, Panel B, were coded from one (very much worse) to seven (very much better).
44
Table 4. Valuation approach: Earnings versus cash flow orientation
N Mean Std.
Dev.
1 Strongly
disagree
2 3 4 5 Strongly
agree
In response to a quarterly
report announcement:a
In my appraisal of the
company, I primarily focus
on the company's earnings
development
44 3.84 1.03 2 2 9 19 12
Analysts with more
experience
18
3.94
0.54
Analysts with less
experience
17
4.00
1.00
In my appraisal of the
company, I primarily focus
on the company's discounted
cash flows
45 3.80 0.94 1 3 10 21 10
Analysts with more
experience
18
4.00
0.77
Analysts with less
experience
18
3.67
0.97
After conducting a
comprehensive analysis:b
In my appraisal of the
company, I primarily focus
on the company's earnings
development
42 3.98 0.81 1 8 23 10
Analysts with more
experience
16
3.94
0.57
Analysts with less
experience
18
3.89
0.68
In my appraisal of the
company, I primarily focus
on the company's discounted
cash flows
42 3.9 0.82 1 10 22 9
Analysts with more
experience
16
4.00
0.73
Analysts with less
experience
18
3.94
0.64
Notes: The responses to the statements were coded from one (strongly disagree with this statement) to five (strongly
agree with this statement). The groups of more experienced (M=20.4 years) versus less experienced analysts (M=8.1
years) were constructed by a median split. No significant differences between the groups were observed. a Specifically, the respondent was asked: Consider the following situation. A company that you follow has recently
announced a quarterly report. Indicate to what extent you agree with the below statements.
b Specifically, the respondent was asked: You have recently performed a comprehensive analysis of an industry including
a company that you follow. Indicate to what extent you agree with the below statements.
45
Table 5. The impact of acquisitions on valuation measures
When you evaluate the effects of corporate acquisitions,
to what extent to you take the following measures into
account with regard to the acquiring firm?
n Mean Std. Dev. 1 Never
2
3
4
Sometimes 5
6
7 Always
Discounted cash flows
49 5.47 1.37 1 4 5 11 16 12
EV/EBITDA 49 5.35 1.56 2 2 1 7 9 16 12
EV/EBIT 48 5.44 1.43 1 1 2 7 11 13 13
EV/Sales 48 4.94 1.63 3 4 13 7 12 9
Price/Book ratio
49 4.59 1.41 3 8 15 8 10 5
PE ratio 49 4.78 1.65 3 2 5 8 13 11 7
Notes: The responses to the statements were coded from one (never) to seven (always).
46
Table 6. The impact of acquisitions on valuation measures: Comparisons between respondent groups.
When you evaluate the effects of corporate
acquisitions, to what extent to you take the
following measures into account with regard to the
acquiring firm?
More knowledgeable
of accounting standards
Less knowledgeable
of accounting standards
More experienced
respondents
Less experience
respondents
n Mean Std.
Dev.
n Mean Std.
Dev.
n Mean Std.
Dev.
n Mean Std.
Dev.
Discounted cash flows 23 5.52 1.41 26 5.42 1.33 18 6.06a 0.73 21 5.38a 1.28
EV/EBITDA 22 5.05 1.91 27 5.59 1.22 17 5.88a 0.86 21 4.90a 1.64
EV/EBIT 23 5.17 1.53 25 5.68 1.31 18 5.89a 0.90 19 4.68a 1.73
EV/Sales 22 4.68 1.67 26 5.15 1.59 17 5.12 1.17 20 5.00 1.72
Price/Book ratio 23 4.52 1.44 26 4.65 1.41 18 5.00 1.24 20 4.35 1.35
PE ratio 22 4.82 1.59 27 4.74 1.72 18 5.28a 1.32 20 4.45a 1.64
Notes: The two groups of knowledge of accounting standards were constructed using median split with respect to the index variable reflecting average knowledge of IFRS,
IFRS 3 and IAS 36. No differences between the two groups were observed. In regard to years of experience as a financial analyst, this variable was split into two groups
(using median split): More and less experienced respondents (Means = 20.7 v 8.1 years). The varying numbers of observation were due to missing values. a denotes the
significant differences between those groups in regard to the respective measurement (p < 0.05 as indicated by t-tests).
47
Table 7. The significance of the acquisition analysis
Panel A Overall significance of the acquisition analysis n Mean Std.
Dev.
1 Not at all
2
3
4
To some extent
5
6
7 To a very
high
extent
How does the purchase price allocation into goodwill and other
intangibles affect your appraisal of the acquiring firm?
57 4.11 1.63 5 7 6 12 14 12 1
Panel A. continued n Mean Std.
Dev.
1
Never
2
3
4
Someti
mes
5
6
7
Always
To what extent to you take the acquisition analysis into account when
evaluating corporate acquisitions?
53 5.02 1.23 2 4 9 20 12 6
More knowledgeable of accounting standard 23 4.96 1.36
Less knowledgeable of accounting standard
30 5.07 1.14
More experienced respondents 20 4.85 1.42
Less experienced respondents
19 5.16 1.07
48
Panel B Significance of details in the acquisition analysis
Indicate how important you perceive the following details from the
acquisition analysis to be in your evaluation of corporate acquisitions.
n Mean Std.
Dev.
1 Not
important at all
2
3
4
Hesitant
whether important
or not
5
6
7 Very
important
Consideration transferred
53 6.40 1.01 1 1 2 19 30
The size of the goodwill amount 53 5.42 1.42 2 1 1 7 10 22 10
The size of the intangible assets 53 5.26 1.35 2 2 1 10 15 21 2
Intangible assets in the form of product rights
53 4.98 1.34 2 2 1 10 15 21 2
Intangible assets in the form of brands 53 5.00 1.47 3 2 1 8 14 22 3
Intangible assets in the form of customer relations 52 4.79 1.59 3 2 6 8 9 21 3
Amortisation period 53 4.79 1.61 3 4 3 9 8 24 2
Notes: The responses to the statements were coded from one (never) to seven (always). The two groups of knowledge were constructed using median split. This procedure
meant that while the group with more knowledge of IFRS 3 included the respondents indicating to some extent or fairly high knowledge (see Table 3), the group with less
knowledge involved the respondents stating the other responses to this scale. No differences between those two groups were observed.
Table 7 continued
49
Table 8. The impact of acquisitions on valuation measures: Comparisons between respondent groups.
Significance of details in the acquisition analysis:
Indicate how important you perceive the following
details from the acquisition analysis to be in your
evaluation of corporate acquisitions.
More knowledgeable
of accounting standards
Less knowledgeable
of accounting standards
More experienced
respondents
Less experience
respondents
n Mean Std.
Dev.
n Mean Std.
Dev.
n Mean Std.
Dev.
n Mean Std.
Dev.
Consideration transferred 25 6.24 1.33 28 6.54 0.58 18 6.61 0.61 21 6.14 1.42
The size of the goodwill amount 25 5.56 1.56 28 5.29 1.30 18 5.61 0.98 21 5.29 1.77
The size of the intangible assets 25 5.28 1.49 28 5.25 1.24 18 5.44 0.92 21 5.10 1.67
Intangible assets in the form of product rights 25 4.76 1.56 28 5.18 1.09 18 4.94 1.16 21 4.95 1.28
Intangible assets in the form of brands 25 4.80 1.73 28 5.18 1.19 18 5.06 1.16 21 4.86 1.62
Intangible assets in the form of customer relations 25 4.52 1.87 27 5.04 1.26 18 4.56 1.46 20 5.00 1.41
Amortisation period 25 4.88 1.83 28 4.71 1.41 18 4.94 1.31 21 5.14 1.53
Notes: The responses to the statements were coded from one (never) to seven (always). The two groups of knowledge of accounting standards were constructed using median
split with respect to the index variable reflecting average knowledge of IFRS, IFRS 3 and IAS 36. No differences between those two groups were observed. In regard to years
of experience as a financial analysts. this variable was split into two groups (using median split): More and less experienced respondents (Means = 20.7 v 8.1 years). No
significant differences were observed.
50
Table 9. Analysts’ follow-ups on acquisitions and the significance of impairment tests
Panel A Follow-ups on acquisitions and the significance
of impairment tests
n Mean Std. Dev. 1 Never
2
3
4
Sometimes 5
6
7 Always
To what extent do you follow up on the outcome of
companies' acquisitions in order to see if they were
successful?
52 4.58 1.35 4 7 18 13 10 5
In your analysis to what extent do you take into account
whether the acquiring company will report future
impairment on goodwill?
57 5.07 1.45 3 3 16 14 7 14
To what extent do you take annual report descriptions of
impairment tests of goodwill into account in your work?
57 4.51 1.44 1 4 5 23 10 7 7
Panel B Significance of impairment tests and
amortisation
n Mean Std. Dev. 1 Strongly
disagree 2 3 4 5 Strongly
agree
To what extent do you agree with the following
statement: The valuation of companies that have made
many acquisitions is not affected by the impairment of
goodwill and other intangibles
50 2.24 0.94 10 25 8 7 0
More knowledgeable of accounting standards 23 2.57a 0.95
Less knowledge of accounting standards 27 1.96a 0.85
To what extent do you agree with the following
statement: When I evaluate a company. I make forecasts
of hypothetical amortisation of the acquired goodwill
50 2.92 1.21 7 12 14 12 5
More knowledge of accounting standards 23 2.70 1.22
Less knowledge of accounting standards 27 3.11 1.19
Notes: The responses to the statements were coded from one (never) to seven (always). The two groups of knowledge of accounting standards were constructed using median
split with respect to the index variable reflecting average knowledge of IFRS, IFRS 3 and IAS 36. a Denotes significant difference between the two groups. as suggested by t-tests (p < 0.05).