Post merger profitability analysis of shareholders. Evidence from ...

Post merger profitability analysis of shareholders.
Evidence from Europe.
by
Varun Daga
2007
A Dissertation in part consideration for the degree of
Master in Finance and Investment

Dedicated to my Grandparents and Parents
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Acknowledgements
The author would like to thank his supervisor, Professor John Hasseldine
for the guidance and advice through this project.
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Abstract
The effects of takeovers on the value of both, target and bidder firms
have been studied by many researchers. While in the United States there
is extensive empirical evidence on the effects of consolidation on share
price movements, the empirical literature remains limited in Europe.
Reviewing the relevant literature suggests that the majority of previous
work concludes that the bulk of mergers perform strongly pre merger and
poorly afterwards. It is subject of the Hubris Hypothesis that bidders
outperform the market pre merger and that bidder and target combined
value is around zero. Systematically nonzero abnormal share returns after
a particular event is inconsistent with market efficiency. The hubris
hypothesis argues that bidders make systematic mistakes. Modigliani and
Miller stress in their irrelevancy preposition that the means by which an
investment is financed is irrelevant. Splitting merger deals into relevant
characteristics suggests that the majority of research does not support
this hypothesis.
In terms of methodology, this study uses an event-study type approach,
in which changes in the prices of specific financial market assets around
the time of the announcement of the acquisition are analyzed. Different
valuation approaches brought up in research and practical approaches are
presented. The data is a sample of major European deals from 1995 to
2004. Abnormal returns are derived from the market model.
The author finds that pre merger, companies outperform the benchmark
and that during the event period there is insignificant underperformance.
However, during the post event period, the sample firms significantly
underperform on average.
By and large, the main conclusion is that acquisitions destroy
aggregate wealth. It is found that pre acquisition performance is not
an indicator for post acquisition performance. Several effects are
identified (higher combined bidder-target stock returns for friendly
offers and lower for related offers). The long-run post-acquisition
performance is insignificant for equity to shares offers.
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Abbreviations
AAR
AR
ARIMA
BHAR
CAPM
CAAR
CAR
GDP
M&A
Ri
RiC
Rm
RmC
NPV
SDC
average abnormal return
abnormal return
autoregressive integrated
moving average
buy-and-hold abnormal
returns
capital asset pricing model
Cumulated average abnormal
return
Cumulated abnormal return
Gross domestic product
Mergers and Acquisitions
Return of the firm
Return of the firm cumulated
Return of the market
Return of the market
cumulated
Net present value
Securities Data Corporation
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Contents
Acknowledgements 03
Abstract 04
Abbreviations 05
List of Figures and Tables
Chapter 1 Introduction 07
Chapter 2 Literature review 10
Chapter 3 Methodology 38
Chapter 4 Results 60
Chapter 5 Analysis 68
Chapter 6 Conclusions 90
References 94
Appendices 104
List of Figures and Tables
Table 1 Summary performance during the estimation period
Table 2: Summary performance during the event period
Table 3 Summary performance during the post-event period
Table 4 Alpha and beta coefficients
Table 5 Portfolios of cash-shares acquisitions
Table 6 Portfolios of hostile-friendly acquisitions
Table 7 Portfolios of related-unrelated acquisitions
Figure 1 Major European and US deals
Figure 2 Mean abnormal performance
Figure 3 Mean abnormal performance post event period
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Chapter 1: Introduction
In combination with other trends, such as privatisation and
deregulation of financial markets, a large and accelerating process
of consolidation of public listed firms has taken place in Europe
during the last decade. Analysing investment decisions reveals that
the largest investment decisions that most firms make are
acquisitions of other firms.
Figure 1 illustrates the strong growth of major European
acquisitions during the last decade. According to the Securities Data
Corporation, comparing US deals and European deals reveals that
US acquisition activity is of larger frequency. However, the amount
of deals in Europe more than tripled from 1995 to 2000 whereas in
the US the amount of deals grew more slowly.
Figure 1 Major European US and deals
Conclusions of post-merger stock performance are that there is
evidence that the majority of M&As are unsuccessful. However,
what minimizes the explanatory power of the bulk of the studies is
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that, while in the United States there is extensive empirical
evidence on the effects of financial consolidation, the empirical
literature remains limited in Europe. Next to implications for the
efficient market hypothesis, the more interesting question for the
European manager is whether mergers, on average, destroy
shareholders’ value.
Given that corporate managers have two choices of growth: organic
growth and growth via acquisition, there are plenty of winners and
losers in organic growth investments as well as in acquisitions.
Reasons for the overall failure are various but, put simply, an
acquisition can be characterized in various steps and the source of
failure can be found in those steps (Damodaran, date unknown):
1.) Developing a rationale and a strategy for doing acquisitions.
2.) Choice of a target for the acquisition and the valuation of the
target firm, with premiums for the value of control and any synergy.
3.) Determination of how much to pay on the acquisition, how best
to raise funds to do it, and whether to use stock or cash.
4.) Finally to make the acquisition work after the deal is complete.
Within the acquisition process, this paper aims to shed light on
point three. More precisely, it is attempted to examine whether
major European mergers are positive NPV projects. The authors of
the classical corporate finance textbook, Brealey & Myers (2003),
argue that acquisitions fail because of wrong pricing “Some
acquisitions may result from mistakes in valuation on the part of the
stock market … Why don’t we see just as many firms hunting for
bargain acquisitions when the stock market is low”
Firstly, this paper attempts to answer the question whether
acquisition announcements have a similar impact on share prices of
European companies. This is done with an event study approach.
The event study has many applications. In accounting, finance and
economics research, event studies have been applied to a variety of
firm-specific and economy-wide events.
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Secondly, it is of interest to explore the possibility of a relationship
between deal characteristics in order to evaluate which indicator
suggests if a merged company wins for the shareholder. It will be
focused on the acquirer, the average loser in the literature, and it
will be investigated whether there is guidance to the managers in
the form of statistical patterns.
The dissertation is structured as follows. The subsequent section
provides a brief literature review of reports and publications.
Section three outlines the methodology; how merger-related factors
influence the bidding firms’ share price and how merger-related
performance can be captured. Several studies can be criticized for
their weak methodologies. Also a traditional finance model is
adjusted in order to predict possible abnormal performance. Section
four describes the findings gained during the respective event
windows. This paper then tries to evaluate whether the two firms
are worth more together than apart. Section five provides the
analysis where explanations for negative bidder returns such as the
method of payments hypothesis are tested. Concluding remarks can
be found in section six.
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Chapter 2: Literature review
Merger – Definitions
Narrow definition of merger according to Sudarsanam (1995) is “…a
pooling of the interest of two companies into a new enterprise,
requiring the agreement by both sets of shareholders…” According
to Buckley (1995) a broad definition comes along the lines of “…the
corporations come together to combine and share their resources to
achieve common objectives. The shareholders of the combining
company often remain as joint owners of the combined entity…” In
the following section the broad definition of merger activity is
selected.
In the literature, ‘Merger’ is a combination of organisations, where
both the merging companies wish to join together and do so on
roughly equal terms and which “create an organisation where
neither party can be seen as acquirer” (Vaara, 2000 pp.82).
‘Acquisition’ is termed as “a purchase by one company of a
substantial part of the assets or securities of another, normally for
the purpose of restructuring the operations of the acquired entity.
The purchase may be of all or a substantial part of the target’s
voting shares or of a division of the target firm (The new Palgrave
dictionary of money and finance, 1992, pp.10). However, in line
with common practice (Chiplin and Wright, 1988), these terms
would be used synonymously.
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Reasons on Undertaking Mergers
There has been an increase in merger activity over the whole of
U.K. in 1980’s and according to Peacock and Bannock (1991) the
attraction of mergers to be a route of expansion can be represented
to three main points.
The first point is that the merger activity of an existing business is
less time consuming, especially in a global environment. Merger
process may be pushed through in a period of weeks or months,
unlike the slow process of internal growth, which require detailed
planning, recruitment of human resource, trial and error, building
relationship with the suppliers and buyers, establishing strategies
etc.
The second point is that merger activity in many cases is a cheaper
alternative, especially when the stock market is in its inefficiency
and market information asymmetry. Another example is when the
target company processes intangible assets like patents, brand
identities, goodwill, which could be effortlessly obtained through
merger activities. Moreover, compared to internal expansion that
may cost a great amount in establishing a new plant, mergers do
benefit an enterprise in financial concern.
The third point is referred to the region of economic opportunities.
The rapid technical change gives a new means to the advantage of
time possible with merger activities. In other words, the longer time
to enter into a market and the more competitors are already
entrenched. In establishing entry barriers, mergers allow quick
participation in new technological markets to realise potential
profits.
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The author (Peacock and Bannock) conclude that the trends of
undertaking mergers to enhance competitive strategy will achieve
another boom in foreseeing future not only in U.K. but also in U.S.S
and South East Asia.
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Types of Merger Activity
To have a more thorough idea and better understanding of merger
activity, its types must be examined and explained through their
specific characteristics with reference to recent examples.
In particular, according to merger literature (Stacey (1996),
Thompson (1978), Sudarsanam (1995), Arnold (1998)), there are
three main types of mergers: horizontal, vertical and conglomerate.
Theses differ by the type of the involved firm, the benefits sought
and the motivations behind them.
Horizontal Merger
In horizontal merger two companies, which are engaged in the
same or similar field of activity, are combined. Recent examples of
horizontal mergers are the combination of Glaxo with Wollcome,
LloydsBank with TSB, and Sainsbury’s own already Homebase with
Texas Homecare. Main motives behind this type are the
improvement of market power as a result of the reduction in market
competition, the acquisition of a more profitable firm for its
technological know-how, or the achievement of economies of scales
as the companies operate in the same line of business. A possible
effect of this kind of merger is the creation of monopoly power by
competitors’ reduction and building of entry barriers due to the
assumption that new entrants fear increasing market share has
tendency to raise the profitability of intervention from regulatory
agencies concerned with competition in the market. Some examples
of these government bodies are the “Monopolies and Merger
Commission” and the “Office of Fair Trading” in the U.K. (Arnold,
1998)
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Vertical Merger
Stacey (1996) claims that vertical merger is a more complicated
process, as the buyer expands not into his own field but into a
different one. The vertical process can be characterised as
“upstream” or “downstream”. At the “upstream” the entrepreneur
proceeds towards the source of his supply, such as supplier of raw
material. An example could be a manufacturer of footwear that
merges with a leather producer. On the “downstream” merger the
entrepreneur proceeds through the channels of distribution towards
the final consumer, who may be another industrial user. A possible
example is if the manufacturer of footwear merges with a retailer of
shoes.
Vertical merger can also threaten competition as the same with
horizontal. By definition, the firm expands vertically by integrating
the successive stages of production-backward towards the raw
material or forward towards the consumer. Thus, vertical mergers
are used as a means to control production processes. Suppliers in
this type of merger can raise barriers to entry by reducing
possibilities for potential competitors to participate at one of the
integrated production levels (Thompson 1978). Allan (1996) states
that this type of expansion is dangerous, because both companies
that merge face the same volatility in the business cycle. Hence, it
increases the effect of the cycles on the combined company.
Vertical is a common type of mergers in industries where
companies’ actively rely heavily on suppliers and buyers for
example a soft drink company acquiring a bottling company.
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Conglomerate Merger
A conglomerate merger is the combination of two firms that operate
in unrelated business areas. Arnold (1998) states that the majority
of mergers of this kind are motivated by risk reduction through
diversification or by the opportunity for cost reduction, improved
efficiency or technical know how of other partners in unrelated
businesses. An example is that of Sony, which is teaming up with
US investment bank JP Morgan and Japanese bank Sakura to let
Playstation 2 consumer’s bank online using their consoles. The
internet bank combines Sony’s technical know-how with Sakura’s
knowledge of Japan’s banking industry and JP Morgan’s expertise in
offering investment advice to clients. Sudarsanam (1995) argues
that conglomerate mergers are done in the interest of managers
rather than in the interest of shareholders, who try to avoid closedown
of a business and consequent unemployment. According to
Goldberg (1983), among conglomerate mergers, there are three
types that have been distinguished. (I) Concentric Mergers - that
are the mergers between firms in related business activities. Such
kind of mergers is an expansion toward the company’s strengths
and away from its weaknesses. (II) Geographic Market-Extension
Merger. This type involves two firms whose operations have been
conducted in non-overlapping geographical regions. (III) Pure
conglomerate mergers, which include unrelated business activities.
The advantage of conglomerate mergers is not only in reducing risk,
but also in the transaction of management functions. When any two
firms of unequal management competence are combined, the
performance of the consolidated firm will benefit from the impact of
the superior management firm and the total performance of the
combined firm will be greater than the sum of the individual parts.
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It is a kind of synergy that will be mentioned at the following
section.
Cartwright and Cooper, (1992) define another type of merger
known as Concentric mergers’ in which the organisation acquired is
in an unfamiliar but related field into which the acquiring company
wishes to expand.
Two other terms, which frequently arise, are ‘mergers’ and ‘tender
offers’. Loughran and Vijh (1997) differentiate between these two
types of acquisitions. They define ‘mergers’ if some of the following
characteristics are present: the tone was friendly, the target’s
managers were favourable and the board of directors and the
shareholders voted and approved the deal. A ‘tender offer’ is when
the tone is aggressive, there was no shareholder meeting or
approval, the word tender was used and the percentage of shares
sought was mentioned. Further, Rau and Vermaelen (1998)
believed that tender offers tended to be more hostile transactions
and mergers friendly transactions.
Concluding
According to the merger literature review, horizontal, vertical and
conglomerate are the three main types of mergers, which differ by
the type of the involved firm, the benefits sought and the
motivation behind them.
However, it should be noted that in reality most mergers are
difficult to be classified into such distinct categories since the
different types of mergers may sometimes overlap each other. For
example, a merger can be classified both as horizontal and vertical
depending on the partner. This can be the case when a bank
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merging with another bank owns a company that is also in
insurance business.
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Theoretical Background of Merger Activity
This chapter examines the theoretical background of merger
process, dealing particularly with issues relating to why merger take
place, but without making a deep and thorough investigation on the
reasons behind this process. It just provides a reference for a
general understanding of takeover activity, since an analysis of this
kind is out of the scope of this paper.
Efficiency Theory
According to Copeland and Weston (1992), the most general
theory, associated with mergers, involves differential efficiency. In
theory if the management of firm A is more efficient than the
management of firm B, and after firm A acquires firm B, the
efficiency of firm B is bought up to the level of efficiency of firm A.
This would be a social gain as well as a private gain and such
mergers would raise the level of efficiency in the economy.
One difficulty with the theory is that if it carried to its extreme, it
would result in only one firm in the economy, the firm with the
greatest managerial efficiency. Hence according to its basic
assumption there are always many firms that exhibit below-average
efficiency or that they are not operating up to their potentials.
Efficiency also includes the possibility of achieving some form of
synergy. Synergy is the occasion where the two firms together are
worth more than the value of the firms apart. If two firms, A and B,
are to be combined a gain may result from synergistic benefits to
provide a value above that of the present value of the two
independent cash flows:
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PV of AB = PV of A + PV of B + Gains
Where,
PV of A = discounted cash flows of company A.
PV of B = discounted cash flows of company B.
PV of AB = discounted cash flows of the merged company.
Synergy is often expressed in the form of 2 + 2 = 5. This can be
achieved through the exploitation of economies of scale, where
fixed costs become a smaller proportion of greater output, and thus
output can expand at lower cost. In specific, synergy is the ability to
exploit economies in marketing through the use of common
distribution channels or joint advertising or join research and
development facilities, especially in the case of horizontal mergers.
There are also economies in administration, research and
development, purchasing and finance. Efficiency theories provide a
basis for mergers to achieve strategic planning goals in response to
a rapidly changing environment. However, besides the basic
assumption that many firms exhibit below average efficiency,
efficiency theories are also based on the assumption that economies
of scale do exist in the industry and that prior to the merger, the
firms are operating at levels of activity that fall short of achieving
the potential economies of scales.
Information Theories
The information or signalling hypothesis refers to the revaluation of
the ownership shares of firm owning to new information that is
generated during the merger process. Bradley (1983) has
distinguished the information hypothesis in two explanations. One is
the Kick-in the pants explanation and the second is the sitting-on-agold-mine
hypothesis. According to the former, management of the
target company is stimulated to operate into a higher valued
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strategy that would lead to the revaluation of the company, while
according to the latter the merging activity may involve the
distribution of new information or lead the market to judge that the
bidders have superior information. The market may then revalue
previously “undervalued” shares of the bidder company
automatically after the announcement of merger activities. In
theory, information that the “target company is undervalued”,
becomes one of the motives for bidder to be engaged in merger or
acquisitions activities.
Agency Problem Theory
Managers are the agents of shareholders, and because both parties
are self-interested, there are serious conflicts between them over
the choice of the best corporate strategy. Agency costs are the total
costs that arise in such arrangements and they consist of the costs
of monitoring managerial behaviour and the efficiency losses that
are occurred because the conflicts of interest can never be resolved
perfectly (Jensen, 1986). According to Jensen and Meckling (1976),
an agency problem arises when managers own only a small fraction
of the ownership shares of the firm. This limited ownership may
cause managers to work less vigorously than otherwise, to increase
expenditures by purchasing luxurious offices, company cars etc. or
to make decisions that are opposed to the objectives of
shareholders’ wealth maximisation.
The agency problem theory of mergers has two aspects. On one
hand the threat of takeover may mitigate the agency problem by
substituting for the need of individual shareholders to monitor the
managers. Manne (1965) emphasized the market for corporate
control and viewed mergers as a threat of takeover if a firm’s
management bummed in performance either because of inefficiency
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or because of agency problem. On the other hand, mergers may be
a cause of agency problem rather than a solution. This is known as
the “managerialism” explanation of mergers and was set up by
Mueller (1987). According to it the compensation to managers is a
function of the size of the firm, therefore they try to increase the
size of the firm further. However, Lev and Huntsman (1983) present
findings that managers’ compensation is significantly correlated with
the firm’s profit rate. Not its level of sales.
Roll’s Hubris hypothesis suggests that the agency problem theory is
not checked by the market control mechanisms. Hubris is a Greek
word meaning “animal spirits”, “with connotations of overexuberance
and excess pride”. Roll suggests that managers commit
errors of over-optimism in evaluating potential merger candidates,
thus bidding more than they should and transferring virtually all
gains from the transaction to the target shareholders. A study by
Moeller et al (2004) showed that larger firms, which might
reasonably be run by hubris filled managers, tended to offer higher
premium and were more likely to complete a takeover than their
smaller counterparts. Gaugham (2005) further states that research
from the field of management also supported the hubris hypothesis.
He cites the study of Hayward and Hambrick which studied 106
acquisitions and found that CEO hubris was positively related with
the size of premiums paid, which was in line with the above
hypothesis.
Fama (1980) mention that the agency problem can be solved by a
good internal control system in which strategic planning and control
should be separated, a number of compensation arrangements and
by the market for managers.
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Greater Market Power
In economics market power is defined as the ability to raise price
above the competitive price. Market power implies that a company
has a greater chance of enjoying profits for a period of time as
opposed to other competitors (Gaugham, 2005). Thus, M&A can
enable companies to attain a larger market share and thereby
increase the price of their products or services, relative to their
cost. Hence, the desire and drive to gain more market power can be
another objective for mergers. Increased market power is not only
confined to the area of sales but can also be achieved in the area of
purchases. However, anti-trust laws curb such intentions of
companies in gaining power.
Tax Advantages
Another motive for M&A is the possibility of availing tax incentives.
A target firm becomes valuable if it has transferable tax losses,
which can be offset against the acquirer’s income. Moreover, higher
deductibility of interest and deprecation allowances in acquired
assets can also induce merger activity. Furthermore, other tax
incentives like structuring a tax-exempt deal also increase the
possibility of mergers.
Concluding
According to the above theoretical issues, some of the main reasons
that lead companies into the process of merging are achieving a
more efficient management or some sort of synergy accomplished
by the exploitation of economies of scales or taking advantage of
the information that the “target company is undervalued”.
Furthermore, the threat of a possible takeover or an attempt to
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solve the agency problem can also be some reason behind merger
activity.
The scope of this study is to examine the post merger profitability
of a consolidated company and compare it to the pre merger
profitability of two individual companies by using U.K. accounting
data. If the analysis undertaken later comes up with an outcome
where the former is found to be less than the latter, then this
implies that there is no positive economic relationship between
merger activity and financial performance, and therefore the
theoretical issues mentioned above can be perceived as a rational
explanation to the query of why mergers have been and continue to
be so prevalent. Hence, a short reference to them, as the above
attempted to be, was considered essential.
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The Effects of Mergers
This chapter outlines some of the positive and negative effects of
takeover activity, so hat we can have an overall view of this process
in conjunction with the outcome of the oncoming analysis. This will
help us compose our final comments about mergers at the end of
that paper after having examined them first based on their
profitability.
Arnold (1998) argues that one way with which the society can be
benefited by merger is if the combination produces goods at a lower
cost as a result of economies of scale or improved management.
However, he states that merger may also result to social costs in
the form of monopoly power. For example, increase market power
leads to higher prices to consumers.
Jensen (1986) argues that mergers represent a noticeably positive
shifting of assets into their best use and they provide the best
mechanism for ensuring that managers act in the shareholders’
interest.
However, Ravenscraft and Scherer (1987) have a negative view
associated with mergers. They see acquired entities as “lines of
business” that almost always suffering declining profitability after
merging and Scherer, because of this fact, concludes that increased
acquisition activity is likely to be a wasteful thing for the economy
as a whole. Roll (1986) argues that an increase in mergers is
associated with an increase in corporate “hubris”, which is not good
for the economy as a whole.
According to Aaranovitch (1975) and Hannah and Kay (1977),
mergers are expected to directly affect structure by increasing
concentration in the industry. Authors have concluded that mergers
are responsible for at least 50% of the increase in concentration in
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the industry. Increasing concentration infers that market power has
increased, and firms will use this market power to increase prices
and as a result to achieve higher profits for the firm. Thus, merger
has a positive welfare effect for the firms that are engaged in it and
a negative welfare effect on consumers, as higher prices will be
imposed on them. However, concentration may not be an accurate
measure of market power in many cases, as either a high level of
import competition or countervailing power may seriously weaken
the merged firm’s power despite evidence of increasing
concentration (Clarke, 1984 cited in George et al 1992)
Farrell and Shapiro (1990) by using traditional Cournot oligopoly
theory for firms with different cost structures 1 , show that price will
rise if the merged firm does not enjoy significant lower marginal
costs as a result of considerable synergies. Hence, if “outside” firms
do not react and consumers and “outsiders” both lose, it is more
likely that merger will increase price. This result is similar to that of
Williamson (1968, cited in Farrell and Shapiro (1990)), who found
that if the private gains are offsetting, price increases and output
reactions may increase welfare. His difference with Farrell and
Shapiro was that he incorporates the reactions of non-merging
firms.
As far as labour effects are concerned, Brozen (1982) claims that
when the U.S. Bureau of Labour Statistics was asked by the
Temporary National Economic Committee to investigate the
consequences of mergers in America Industry to the earnings of
workers, it had reported that “workers in the plants of big
companies have higher earnings than those in small companies”.
Yale Brozen, after an investigation on the same issue, argues that in
1 If a firm occurs between firms with identical costs and the merged business has the same cost then
mergers are purely anti-competitive. If private gains arise, they will be solely a result of higher prices.
25

1963 the top four firms in 409 industries on average paid wages
15% higher than the wages paid in other firms in their industries.
Another effect mentioned by Jensen (1988) is that takeovers
facilitates exit from an industry or activity. For example, major
changes in energy markets have required a radical restructuring in
that industry and takeovers have played an important role in
accomplishing these changes. Indeed managers who are slow to
recognize that many old practices and strategies are no longer
viable are finding that possible takeovers are doing the job for
them.
However, Jensen argues that from pushing managers to be engaged
in structural changes, growing equity holdings and the fear of
takeover, cause managers to behave myopically and therefore to
sacrifice long-term benefits to increase short-term profits. This
phenomenon does occur when managers hold little stock in their
companies and are compensated in a way that motivates them to
increase accounting earnings rather than the value of the firm.
Another effect mentioned by the same author is that research and
development expenditure (R&D) is increasing when the merger and
acquisition activity occurs. In 1985 and 1986, two record years for
merger activity, R&D also set new records. R&D spending increased
by 10% (to 3.1% of sales) in 1985 and in 1986 R&D spending again
increased by 10% to $51 billion (to 3.5% of sales), in a year when
total sales decreased by 1%.
Hall (1986) argues that takeover and R&D may be substitutes. This
can be done in two ways. Either by investing within the firm for an
R&D programme, or by purchasing another firm after its R&D
programme has yielded successful results. However, he mentions
that a pre-merger level manager may try to increase short-term
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cash flows at the expense of long-term profits by cutting spending
on R&D etc.
It has been mentioned that acquisitions and mergers are one-way
managers spend cash instead of paying it out to shareholders. A
major benefit of mergers, according to Jensen (1986) may be that
they involve less waste of resources than if the funds had been
invested internally in unprofitable projects. Acquisitions made with
cash or securities other than stocks, involve payout of resources to
shareholders of the target company, and this can create net
benefits, even if the merger creates operating inefficiencies.
Concluding
According to the literature review, takeovers can lead to a declining
profitability for the acquiring company, affect negatively the welfare
of consumers as higher prices might be imposed on them and
increase concentration that is a possible indication of the creation of
a monopoly market.
On the other hand, some of the positive effects of mergers are
products’ cost reduction since the consolidated firm produces at
lower cost as a result of economies of scales, an increase in wage
rates and a decrease in the waste of resources. Moreover, they
provide an easy way to exit from an industry and lead to an
improvement of the research and development activities (R&D).
In case that our research concludes in a non-existing positive
relationship between merger profitability and financial performance,
the positive effects of mergers stated above will justify the
existence of mergers even if they lead to operating inefficiencies.
On the other hand, if this study concludes that post merger
profitability is higher than pre merger profitability then the negative
27

effects of merger process should affect our final comments about
merger activity.
28

Post-Merger Profitability
Corporate mergers can occur for many reasons: to achieve
economies of scales and scope in production, increase firms’ size
and achieve competitive advantage, increase innovation, achieve
risk diversification and potential tax shields, increase market power,
improve technological equipment and displace inefficient managers.
However, the scope of this paper is to give emphasis on examining
the mergers in terms of their profitability rather than the reasons
they occur.
Prior research into the profitability of takeovers has focussed on two
distinct types of methodology. The first type has examined the
financial characteristics of acquired and acquiring firms before and
after the merger activity based on accounting data. The second
method has measured the impact of merger activity on
shareholders returns of firms engaged in the takeovers. Both types
of research are viewed below.
Post-Merger Performance Based on Accounting Data
According to Meeks and Meeks (1981) profitability can increase
either from a decrease in real costs or from a rise in prices relative
to costs. However they note that since a rise in prices relative to
costs can result from an increase in market power consequent upon
the merger, a rise in profitability does not prove that efficiency has
necessarily increased. On the other hand, if profitability declines,
they argue that it is possible to conclude that efficiency has fallen.
Singh (1975) compared the combined pre-merger profitability with
the post-merger rate of return adjusted for the industry average.
He used a sample of 77 firms and made two types of comparisons
between firms acquired and those, which are not. First, he
compared the characteristics of each acquired firm with the
29

corresponding median value of those characteristics for the firm’s
industry. Second he formed a sample of non-acquired firms
matched with the group of acquired firms in terms of size. His
concern was with the differences in profitability between acquired
and non-acquired firms and with both methods he found that twothirds
of his sample had lower profits in the year of the merger than
previously. Also, in the first, second and third years after merger a
substantial number experienced reduced profitability. Thus, he
concluded that in at least a half of the cases there was a decline in
profitability after merger.
Newbould (1970 cited in Caves (1989)) examined merger
profitability for the years 1967-1968 in 38 mergers. He argues that
because these mergers were horizontal, they should have provided
the maximum opportunity for synergistic gains. He concluded that a
sample realised no gains or very little, and the other half medium to
high gains.
Meeks also investigated the difference in profitability pre-merger
and post-merger activity for the period1964-1972 by using a
sample of 233 large quoted companies. He concluded that between
one-half and two-thirds of companies in the sample experienced a
decline in profits each year after the merger. However, Meeks
results apply to single-firm mergers only, because once a firm
acquired a second company it was dropped from the sample.
Cowling et al (1980) also studied productivity changes occurring in
nine largely horizontal mergers in Britain; using profit margin on
sales adjusted for changes in input and output prices as an
efficiency measure. None of the nine mergers that were studies
exhibited extensive gains in efficiency, and two-thirds showed
extensive declines in the few years following the merger.
30

Ravenscraft and Scherer (1989), using data of 2,732 lines of
business operated by U.S. manufacturing corporations, they
analysed the pre-merger profitability of acquisition targets and
post-merger operating results for the years 1955-1977. In their
investigation of post-merger performance, they used operating
income/end-of-year assets, operating income/sales and cash flow
as profitability variables and concluded that the smaller the size of
the acquired companies is the more profitable they are pre-merger.
For the most part of their research there is no significant increase in
post-merger profitability except among pooling-of-interests merger
partners of roughly equal pre-merger size.
Healy, Palepu and Ruback (1992) used cash flow of companies to
determine whether the merger activity succeeds to improve
corporate performance. According to them improvement in cash
flow returns is an indicator of increased asset productivity. They
conclude that if the target company is undervalued before the
merger, improvements in cash flows would happen even without
merger. On the other hand, mergers could be the reason behind the
improvement if new opportunities with existing resources arise from
the merger.
O’Sullivan (1997) argues that even though some event studies
seem to provide support for economic gains after a merger, the
methods fail to identify the origin of the gains. He states that these
gains may be the result of the reasons leading to corporate mergers
such as a better management team, tax savings, increased market
power or reallocation of resources.
One explanation of negative bidder returns can be found in the
methods of payment hypothesis. Researchers such as Han et al.
(1998) find that under the methods of payment hypothesis the
observed negative returns to bidders are attributed to dominant
31

stock exchange offers in takeovers. Myers and Majluf (1984) state
that, according to the announcement effect, current owners of the
firm prefer share offerings as bid instrument if the management
estimate shares are overvalued. Han et al. (1998) argue that the
information effect of the method of payment is empirically
supported. Modigliani’s and Miller’s irrelevancy argument seems to
hold true only under their stringent assumptions.
32

Hostile versus friendly acquisitions
Companies can be acquired in two ways: friendly or hostile. Servaes
(1991) investigates these opportunities. Not surprisingly, he finds
that takeover premiums are likely to be higher for hostile than for
friendly targets. In addition, Bradley et al. (1988) examine this
pattern and explain that, as a result of competition among bidders,
even higher premiums may be required to be paid in multiple
bidding contests. Comment and Schwert (1995) add that, in
addition to hostile bidding contests, poison pills and control share
laws are introduced, which often result in higher takeover
premiums. On the one hand this is somewhat dangerous as, all
things being equal, it will become more difficult for the bidder to
amortise a higher premium as more synergies will be required in
order to justify the higher premiums. On the other hand, Jennings
and Mazzeo (1993) argue that high premium offers are less likely to
face competition amongst bidders and target resistance. Han et al.
(1998) find that tender offers are preferred by the market to
acquisitions. In addition they stress that the market responds
negatively to bids for firms that have made prior bids or have been
involved in competing bids.
Related versus unrelated acquisitions
Nail et al. (1998) attempt to answer the question whether related or
unrelated acquisitions have a better success rate. They conclude
that firms in related businesses are, on average, acting in their
stockholders’ best interests, while those who execute conglomerate
acquisitions are systematically destroying the wealth of their
stockholders. Considering the combined wealth effects on
stockholders and bondholders, related acquisitions significantly
outperform conglomerate acquisitions – 6.8% versus 3.1% on
33

average and 6.8% versus 1.1% at the median (Nail et al., 1998).
More precisely, fewer than half (48.2%) of conglomerate
acquisitions created positive wealth effects for shareholders, while
almost two-thirds (64.0%) of related acquisitions were wealthcreating.
With respect to risk diversification in conglomerate
mergers, bondholders are often better off in M&A activity than
shareholders.
The size factor
The size of the target, relative to the size of the bidder, has been
found to be a factor of interest in the M&A event study literature.
Asquith et al. (1987) find that bidder returns are greater when the
target is larger relative to the bidder. Jarrell and Poulsen (1989)
also find statistical significance for this factor when they argue that
bidder returns are positively related to relative size in hostile tender
offers. With regard to the methods of payment hypothesis, Asquith
et al. (1987) find strong interactions between the relative size and
payment method. They argue in their studies that there is a positive
size effect for cash-financed acquisitions and a negative size effect
for equity-financed acquisitions.
Methods of payment hypothesis and the information effect
Another explanation for negative bidder returns, called the method
of payment hypothesis, relates to the information effect. Amihud et
al. (1990) ask the question: “Do firms have systematic preferences
for the means of financing investments” Bidding companies
typically offer the shareholders of target companies either cash or
stock, and in some instances both, or the option of either cash or
stock. Modigliani and Miller (1958) state the well known capital
structure irrelevancy theory. Under some rigorous assumptions such
34

as perfect markets and no taxes, they come up with their
hypothesis arguing that the means by which investments are
financed are irrelevant for the total value of the firm. Reacting to
complaints about the somewhat ivory-tower assumptions, Miller
(1977) extended the irrelevance proposition to a case where taxes
exist. Han et al. (1998) attempt to evaluate the market reaction of
M&A deals with regard to the method of payment. They argue:
“casual observation suggests that firms are not indifferent to the
means of financing.” Factors such as agency costs may have an
impact into the capital structure decision process as well as from
asymmetry of information between shareholders and insiders
(management), as discussed by Myers and Majluf (1984).
The information effect is further explained by Myers and Majluf
(1984) when they argue that managers will prefer share financing
of an acquisition when they believe that their company’s shares are
overvalued. This might be the case if management of the bidding
company is better informed about the value of the firm (actually the
share) than outside investors. Given that current bidding
shareholders attempt to avoid dilution of their shares, Amihud et al.
(1990) state that “investors expect this and will, therefore, drive
down the value of firms [when the acquisition medium is shares].”
Assuming that insiders have better information about the value of
their firms, it can be concluded that cash (debt) financing of
acquisitions will, therefore, be preferred unless its cost to insiders is
excessive. Amihud et al. (1990) find that their data supports the
hypothesis that companies with relatively large insiders’ ownership
are more likely to finance acquisitions with cash than with stock.
Eckbo and Langohr (1989) find that, in bids for control, cash offers
result in substantially higher percentage premiums of 73% than
35

equity exchange acquisitions at just 17.2%. Nevertheless, the
payment method not only has an effect on the size of bid premium
but, according to Jennings and Mazzeo (1993), also on target
resistance. Both report that the most frequently resisted offers
involve mixes of cash and securities. Loughran and Vijh (1997, in
Mushidhi and Ward, 2004) find that, on “the post-acquisition
performance over a five-year period, companies that utilised sharebased
acquisitions earned significant, negative abnormal returns (-
25%) whereas companies that completed cash-based takeovers
earned significant positive abnormal returns (61,7%).”
Empirical evidence has shown that on average, long run abnormal
returns to bidders are negative in share financed acquisitions and
positive in cash financed acquisitions. Abhyankar et al (2005) found
that cash financed merger portfolios dominated the benchmark
portfolio and remarked that their results corroborates earlier studies
that cash financed mergers outperform stock financed ones.
Therefore it can be concluded that the majority of research suggests
that market participants value a cash offer higher than a share
value and act accordingly. With reference to overvaluation, Shleifer
and Vishny (2003) argue that their analysis illustrates the role of
defensive acquisitions by firms with overpriced shares: “using these
shares to buy assets available for p

the 1990s. The share of acquisitions that were all for stock rose
from 32.9% in the 1980s to 57.8% in the 1990s.” In summary,
Shleifer and Vishny (2003) find that:
1) Acquisitions are disproportionably for stock when aggregate or
industry valuations are high and for cash when they are low.
2) Bidders in stock acquisitions earn high returns, whereas targets
in cash acquisitions earn low returns prior to the acquisitions.
3) Bidders in stock acquisitions are likely to show signs of
overvaluation, such as earnings manipulation and insider selling.
Shleifer and Vishny (2003) stress that using overvalued shares as a
means of payment enhances the claim on capital of the bidding
shareholders, “and thereby cushions the collapse of the shares in
the long run.” They state that this approach would be the reason for
some high flying firms, such as America Online and Cisco, acquiring
lower valuation firms for stock during the 1990s.
Franks et al. (1988) conducted a long-term study, with a horizon of
30 years, of payment methods in US and UK acquisitions between
1955 and 1985. They support the Shleifer and Vishny (2003)
argumentation in their performance study that “target shareholders
earn a risk adjusted return of 30% in all cash, and 15% in all share
offers during the month surrounding the bid.” Not surprisingly they
conclude also that mixed cash/equity bids produce higher returns
than pure equity offers.
37

Chapter 3: Methodology
Foreword
The aim of this paper is to focus on the value of assets around an
event and to provide evidence relevant for understanding corporate
policy decisions; frankly speaking, a t-test of the increase or
decrease in share price. Event studies have looked at many issues
in corporate finance. To name a few, stock splits, spin-offs, dividend
announcements and acquisitions have been the subject of analysis.
The first event study is attributed to Fama et al. (1969) who
investigated stock splits of public listed companies. In the following,
the event study methodology will be discussed.
Share prices, accounting figures and other measurements
The impact of the acquisition on the value of the firm can be
measured by examining security prices, accounting figures, industry
production, macro data and much more. With reference to the
above-mentioned discussion and the majority of academic results
that stock markets are at least semi-strong efficient, the market
value of a public listed company should be worth what its shares are
worth. However, previous event studies have shown that
information about a possible takeover typically leaks into the
market in advance of the actual transaction announcement. Hence,
target and to an extent target share prices in the run up of an
acquisition related bid, embed some element of expectation of the
planned takeover, or even the impact of a pre-bid buying by the
acquirer. In essence, pre-announcement share price movements
suggest a value transfer for the market’s perceptions of synergies
that the deal will be consummated.
38

An alternative approach to shares could be to work with industrial
production or earning figures, as followed by Han et al. (1998) who
measure overpayment in acquisition deals by using earnings-price
ratios. The author rejects this approach. Firstly, the key authors in
finance and in particular in the event study literature argue that the
earnings figure is a noisy measure because it is sensitive to more or
less arbitrary accounting methods (e.g. Fama, 1997). Secondly,
industrial production data is not available for the purpose of this
study. Thirdly, historic methodology literature, such as Weston
(1953) and Markham (1955) show that acquisition activity is
statistically significant related to share prices, not to industrial
production. Markham (1955) calculated correlation coefficients that
were statistically significant, but were larger between acquisitions
and stock prices than between acquisitions and industrial
production. Alternative approaches to shares do not seem to
promise better results. Therefore the subsequent analysis will be
undertaken with share prices. The approach is to calculate and
analyse the return of securities around the time of an event.
Event studies in finance
An event study can be conducted in many ways. According to
Kothari and Warner (2004), the focus almost always is on the mean
of the distribution of abnormal returns. Typically, the specific null
hypothesis to be tested is whether the abnormal return (sometimes
referred to as the residual, R) at time t is equal to zero. They
furthermore explain that parameters of the cross-sectional
distribution (e.g. median, variance) and determinants of the crosssectional
variation in abnormal returns are sometimes studied as
well.
According to the approach laid out by Weston et al. (1997) the first
step in measuring the effect on stock value of an event is to define
39

an event period. Estimation period, event period and post-event
period are defined as follows (derived from Campbell et al., 1997):
risk adjustment and expected/abnormal return modelling, the
aggregation of security-specific abnormal returns and the calibration
of the statistical significance of abnormal returns (Kothari & Warner,
2004).
The event period
The different lengths of event windows in the relevant literature are
remarkable. Extreme examples are Schwert (1996) who works with
an event window of -256 days to announcement and Boehmer
(1998) who works with -10 days to +2 days to announcement.
Usually, the event window is centred around the announcement
40

date, which is day 0 in the event time. According to Kothari and
Warner (2004), Lyon et al. (1999) stress that, while long-event
horizon methods have improved, inferences from long-horizon tests
still require caution. The major problem is risk adjustment. Kothari
and Warner (1999) explain that the risk adjustment error is
exacerbated in long-horizon event studies because the potential for
such error is greater for longer horizons.
On the other hand, short-horizon methods are relatively
straightforward and trouble-free. In addition, short-horizon studies
might be powerful if it can be assumed that the abnormal
performance is concentrated in the event window. Mushidzhi and
Ward (2004) argue that shorter event windows (when compared to
most prior event studies) should be preferred to avoid confounding
effects; longer event windows are more likely to suffer confounding
effects. It is attempted to ensure that any possible release of preannouncement
date information is caught in the evaluation. On the
other hand a very short-horizon test is less sensitive to benchmark
models of normal returns. It is decided to work with -20 tradingdays
before the acquisition announcement up to the announcement
date. This approach is in line with Meulbroek and Hart (1997) and
Mushidzhi and Ward (2004).
The estimation and post-event period
A ‘clean’ (estimation period) prior event period is required in order
to estimate the average daily return for a period. This period
includes days on which no information related to the event is
released. It yields an expected return that takes the risk of the firm
into account. Albeit the choice of the length of the estimation period
is somewhat arbitrary, several M&A publications work with those
one month to one year prior to announcement, suggesting that this
41

period is long enough to filter out much of the ‘abnormal’ price
changes.
With regard to the post-event period, Philippatos and Baird (1996)
evaluate acquisition performance during the three-year period after
the acquisition is announced to the media, hence to the
shareholders. This long-term approach is criticised by Roll (1986)
who agues: “The bid can convey contaminating information, that is,
information about the bidder rather than about the takeover itself.”
As discussed above, the author rejects the long-term approach due
to possible high degrees of noise in the share price. Given that the
author cannot exclude noise completely, but wants to measure a
possible impact on share price performance, an estimation period
and post-event period of 250 trading-days pre- and postannouncement
date is chosen. For consistency reasons estimation
and event period should be of equal length, here trading-days -270
to -20 for the estimation period and trading-days 1 to 250 for the
post-event period.
Investigated time
A discussion of the length of the investigated time period is
important because it demonstrates how easy it is to conclude there
is abnormal performance when none exists. Event study literature
usually distinguishes between long-horizon and short-horizon
studies. Much work has been conducted on short-term analysis and
acquisition announcement studies seem to vary from a daily or even
hourly basis to 30-year long-term studies. This paper focuses on the
time period between 01.01.1995 in order to detect differences over
a sufficient time horizon. The most recent date is the 30.06.2004,
given that post-event share price performance is examined 250
trading-days post-event.
42

Daily versus monthly data
Given that return data is available at different intervals, with daily
and monthly intervals being the most common, the sampling
interval has been subject to discussion in the event study literature.
More precisely, the question of the gains of using more frequent
sampling arises and power gains from shorter intervals have to be
considered. MacKinley (1997) conducted research in this field and
stresses: “the decrease in power going from a daily interval to a
monthly interval is severe. For example, with 50 securities the
power for 5 % tests using daily data is 0.94, whereas the power
using weekly and monthly data is only 0.35 and 0.12 respectively.”
Given that there seems to be a big gain in terms of power from
increasing the sampling interval, the analysis will be undertaken
with daily stock market data.
The measurement of abnormal returns
The aim is to calculate abnormal returns (rather than returns) and
volatility over the investigated time period. Firstly, the predicted
return, R for each day in the event period for each firm, must be
calculated. The predicted return presents the benchmark return that
would be expected if no event would have taken place.
For each sample security,
R it
= K it
+ e it
(or AR),
R it
= the return on the security for time period t relative to the
event,
K it
= the ‘normal’ (i.e. expected or predicted return given a
particular model of expected returns),
43

e it
(or AR) = the component of returns which is abnormal or
unexpected; it is the difference between
e it
(or AR) = R it
- K it
e it
is of interest as it is the difference between the observed return
and the predicted return, measured during the estimation period.
Thus, the abnormal return is a direct measure of the (unexpected)
change in share price associated with the event.
According to Kothari and Warner (2004), a model of normal returns
(i.e. expected returns unconditional on the event but conditional on
other information) must be specified before an abnormal return can
be defined. A variety of expected return models (e.g. market model,
constant expected returns model, capital asset pricing model) have
been used in event studies. All these models use the concept of
residual analysis, pioneered by Fama et al. (1969).
The market model and alternative approaches
The market model has been a popular benchmark and is probably
the most common employed method in event studies to measure
abnormal returns.
However, two alternative benchmark models, the market-adjusted
model, and the mean-adjusted returns model shall be reviewed
before it is decided which model to use in order to calculate
abnormal returns.
In contrast to the market model, the market-adjusted model is a
restricted market model with alpha being zero and beta being one.
According to MacKinley (1997), for some events it is not feasible to
have a pre-event estimation period for the normal model
44

parameters and a market-adjusted abnormal return is used.
Because the model coefficients are pre-specified, an estimation
period is not required to obtain a parameter estimate. MacKinley
(1997) however adds: “A general recommendation is to only use
such restricted models if necessary, and if necessary, consider the
possibility of biases arising form the imposition of the restrictions.”
Weston et al. (1988) conduct their research with the market model,
the mean adjusted model and the market adjusted model to
calculate expected returns. They find that the three methods
produce similar results. Also Brown and Warner (1980) compare
performances of the mentioned three models. They recommend not
using complicated methodologies. “We have presented evidence
that more complicated methodologies can actually make the
researcher worse off, both compared to the market model and to
even simpler methods, like mean adjusted returns, which make no
explicit risk adjustment.” Under consideration of expected and
actual returns, the market model yields a better understanding of
what target share prices should be and aids in determining the
element of price movement that is attributable to news concerning
a takeover. Therefore, mean adjusted returns and the market
model are applied in the subsequent analysis.
The market model is defined as:
where, for the event window, τ ranges from T 0
+1
to T 2
where R mt
is the return on a market index for day t,
is the slope
coefficient of the stock and measures the sensitivity of firm i to the
market – this is a measure of systematic risk, (intercept)
measures the return over the period not explained by the market,
and is a statistical error term. In order to calculate the
45

estimations, the ordinary least squares (OLS) regression method is
applied as it is unbiased and efficient. The regression produces
estimates of and , which are and .
The predicted return for a firm for a day in the event period and
post-event period is the return given by the market model on that
day using these estimates. The univariate regression is performed
with Microsoft Excel. Properties of potential abnormal returns are
conditional on the hypothesis that abnormal returns are zero.
In order to capture share prices net of these abnormal
price movements, announcement prices are compared to pre-bid
prices. The possible abnormal return is calculated by
Fama’s approach (1997) is followed, which recommends either to
average abnormal returns (AARs) or to sum cumulative abnormal
returns (CARs). The final step is to cumulate the average residual
for each day over the entire event period to produce the cumulative
average return. The cumulative average residual method (CAR)
uses as the abnormal performance measure the sum of each day’s
average abnormal performance. The CAR, AAR and CAAR formulas
are derived from Agrawal et.al (1992) and are defined as:
46

It is intended to calculate an average impact on share prices in the
form of mean abnormal returns in order to test if the null
hypothesis. Additionally, when applied to post-event periods, tests
using these measures provide information about market efficiency.
This is because of the fact that systematically non-zero abnormal
returns following an event are inconsistent with efficiency and imply
a systematic trading rule. In addition, CARs are aggregated across
different time periods to see if anomalies sustain over time.
Statistical significance
In order to test the respective hypotheses and to determine
whether a result is statistically significant, the level of significance
and rejection must be evaluated. In order to avoid arbitrariness in
the final decision to confirm or reject a hypothesis, the level of
significance found in the existing area of research is applied. The
majority of researchers (e.g. Brown and Warner, 1985; Dodd and
Ruback, 1978) work with significance at the 5% level which reflects
a 95% confidence interval. This suggests an acceptable level of
error and simultaneously is convenient for this type of study with a
random sample.
Sampling distributions of test statistics
In order to compare the performance of the abnormal cumulative
returns, a test statistic is usually computed to compare the
distribution under the null hypothesis; that means abnormal
performance is equal to zero. The t-statistic on the coefficient iβ is
used to test for risk shifts. The null hypothesis that there are no
47

changes in beta implies the coefficient b is zero. A significant
negative t-statistic indicates a decrease in beta and a significant
positive t-statistic an increase in beta after the offer.
The null hypothesis is rejected if the test statistic exceeds a
significant value, here in the 5% tail region. In order to avoid Type
1 (the null hypothesis is falsely rejected) and Type 2 errors (the null
hypothesis is falsely accepted), a test statistic must be correctly
specified. A correctly-specified test statistic yields a Type 1 error
probability equal to the assumed size of the test. The second
concern is power, i.e. a test’s ability to detect abnormal
performance when it is present. Power can be measured as one
minus the probability of a Type 2 error. The standard t-test of mean
abnormal performance assumes that the mean abnormal
performance for the cross-section of securities is normally
distributed. The t-test compares sample means by calculating
Student’s t and displays the two-tailed probability of the difference
between the means. The t-test for independent data is (Berenson et
al., 2004):
48

df=N 1
+N 2
-2
where
o M1 is the mean of the group with the higher mean
o M2 is the mean of the group with the lower mean
o SDM is the standard error of the difference between means
o N1 is the number of cases in group 1
o N2 is the number of cases in group 2
o S1 is the standard deviation of group 1, which will then be
squared
o S2 is the standard deviation of group 2, which will then be
squared
Skewness and cross-dependence in return
Another criterion for a successful event study is power. Generally
speaking, power is higher with increasing sample size. According to
Brav (2000), specification bias in cross-correlation returns reveals a
serious problem in tests of price performance. Particularly longhorizon
tests suffer from this bias because researchers “maintain
the standard assumption that abnormal returns are independent
and normally distributed although these assumptions fail to hold
even approximately at long horizons.” The degree of crossdependence
should decrease in the effectiveness of the riskadjustment
approach and increase in the homogeneity of the
49

sample firms examined (e.g. sample firms clustered on one
industry). Both factors are taken into consideration in this study.
Firstly, the market model is regarded as an effective method in
order to calculate risk-adjusted performance. Secondly, the
investigated deals are from all European countries, excluding
financial deals only. Therefore, the sample should be of
heterogeneous character.
Evaluating post-acquisition performance
Post-acquisition performance is evaluated by the change in the
combined firms’ share price. Mushidzhi et al. (2004) argue that:
“the method or approach for calculating the performance of postacquisition
returns often differs from the event-study approach used
for pre-acquisition performance, and includes accounting measures
such as cash flow, operating profit and cost of capital.” Industry
performance is applied also as a benchmark to evaluate postacquisition
performance. However, Franks et al. (1991) in line with
the majority of researchers and the above discussion suggest that
“accounting rates of return are unreliable as measures of postacquisition
performance.” Therefore, the respective benchmark is
the DS European non-financial stock index, again.
The buy-and-hold abnormal returns (BHAR) and the Jensenalpha
approach
The post-event risk-adjusted performance measurement is crucial.
However, actual measurement is not straightforward. The debate in
the relevant literature focuses on two main methods for assessing
and calibrating post-event risk-adjusted performance: the so-called
characteristic-based matching approach (also known as the buy-
50

and-hold abnormal returns, BHAR approach) and the Jensen’s alpha
approach (also known as the calendar-time portfolio approach).
The calculation of the BHAR matching would identify the portfolio of
all non-event stocks that share the same quintile ranking on size,
book-to-market, and momentum as the event firm. The obtained
result on the matched portfolio would be the benchmark portfolio
return. Fama (1997) investigated both approaches and argues that
working with abnormal returns poses fewer statistical problems than
long-term BHARs. Fama (1997) argues: “The reason is that average
monthly returns avoid the problems (e.g. extreme skewness)
produced by compounding monthly return to get long-term BHARs.”
In addition, assessing the statistical significance of the event
portfolio’s BHAR has been particularly difficult because the volatility
of the event firm returns exceeds that of matched firms because of
event-induced volatility.
Furthermore, cross- correlation increases if some industries might
be over-represented in the event sample (e.g. strong acquisition
activity among technology stocks). Warner and Kothari (2004)
conclude on this point: “one simple solution to the potential bias
due to cross-correlation is to use the Jensen-alpha approach.” This
method is immune to the bias arising from cross-correlated
(abnormal) returns because of the use of calendar-time portfolios.
Put simply, whatever the correlation among security returns, the
event portfolio’s time series of returns in calendar time accounts for
that correlation. The BHAR model is rejected due to two main
problems. Firstly, there is lack of power as reported by Jegadeesh
and Karceski (in Warner & Kothari, 2004). The former find that,
even in samples with substantial CARs of 25% over five years,
detected in 200 firms, the rejection rate of the null would be
typically fewer than 50%.
51

In contrast to the BHAR approach, the Jensen-alpha approach uses
a matched-firm approach to risk adjustment. It has been utilised by
many, including Fama (1998) and Mitchell and Stafford (2000). In
the authors’ opinion identifying a portfolio of all non-event shares is
a cumbersome and imprecise approach with high potential of error
and therefore will be rejected. Instead, calendar-time portfolio
returns are calculated for firms experiencing an event. Then it is
evaluated whether they are abnormal in a multifactor regression as
follows:
Cross-sectional analysis
If pre- or post-acquisition abnormal returns are of high magnitude,
further analysis is necessary in order to evaluate eventual
relationship between mean abnormal returns and firm or deal
characteristics. It is identified that a cross-sectional regression
approach would be helpful when multiple hypotheses exist for the
source of the abnormal return. The statistical software package
SPSS is used for the analysis. In the multivariate regression it is
aimed to examine the association between the magnitude of the
abnormal return and characteristics specific to the event
observation. Event study literature often applies the Fama/French
Three Factor model or the Carhart Four Factor model.
For the Fama/French model the regression is:
R pt
-R ft
=a p
+ b p
(R mt
-R ft
) + s p
SMB t
+ h p
HML t
+ m p
UMD t
+ e pt
where
52

R pt
is the equal or value-weighted return for calendar month t for
the portfolio of event firms that experienced the event within the
previous T months,
R ft
is the risk-free rate,
R mt
is the return on a value-weight market portfolio (typically a
stock index),
SMBp t
is the difference between the return on the portfolio of ‘small’
stocks and ‘big’ stocks,
HMLp t
is the difference between the return on the portfolio of ‘high’
and ‘low’ book-to-market stocks,
UMDp t
is the difference between the return on the portfolio of past
one-year ‘winners’ and ‘losers’,
ap is the average monthly abnormal return (Jensen-alpha) on the
portfolio of event firms over the T-month post-event period,
Bp, sp, hp, and mp are sensitivities (betas) of the event portfolio to
the four factors. Inferences about the abnormal performance are on
the basis of the estimated ap and its statistical significance. The
estimated intercept from the regression of portfolio returns against
factor returns is the post-event abnormal performance of the
sample of event firms. Therefore, in the regression, a p
should be
statistically indistinguishable from zero. If not, there must be some
additional risk factor that is affecting the expected return to the
portfolio.
Also Carhart provides a model (Four Factor model) in order to
provide an adequate description of expected returns by analysing
firm-specific characteristics. The Carhart Four Factor model uses
Fama and French’s (1993) Three Factor model plus an additional
53

factor to capture one-year momentum anomalies. The additional
term is the price momentum factor as defined in Carhart (1997),
the difference between an equally-weighted portfolio return of
stocks with the highest 30% returns and an equally-weighted
portfolio return of stocks with the lowest 30% returns.
In the past, the Fama/French and Carhart approaches have been
changed slightly for the purpose of specific event studies. For
example, Chan et al. (1991) relate cross-sectional differences in
returns on Japanese stocks to four fundamental variables: earnings
yield, size, book-to-market ratios, and cash-flow yield. They find
that the cash-flow yields have the most significantly positive effect
on expected returns.
Regression variables in this study
In order to test possible abnormal returns, factors are tested for
their explanatory power in a multivariate regression analysis. The
calculations are aggregate across firms in order to evaluate exact
statistic dependents on whether or not the abnormal returns are
independent or dependent. The author decides to change the
Fama/French and Carhart models in the following aspects:
R mt
is the return on a value-weight market portfolio, the Europe DS
Non-Financial- stock index.
CSp t
is the difference between the return on the portfolio of cash
financed acquisitions and stock financed acquisitions.
HFp t
is the difference between the return on the portfolio of hostile
and friendly acquisitions.
54

RUp t
is the difference between the return on the portfolio of related
businesses and unrelated businesses.
A statistically significant association between CARs and a particular
variable in the regression indicates that fluctuations in that variable
predict fluctuations in AR levels.
A point to consider is the number of variables applied. The power of
the multiple regression declines when including a large number of
uncontrolled variables. Some variables might come out as
significant; however the power of the results will decline. The
problem exuberates when the number of observations is relatively
small. According to statistical literature (e.g. Berenson et al., 2004)
it is recommend that 10 to 20 times as many observations as
variables should be included, otherwise the estimates of the
regression line are probably very unstable and unlikely to replicate
if one were to do the study over. With 56 samples this requirement
is met.
55

Data
As mentioned above, the aim of this study is to test European
acquisitions. The sample is drawn from the Securities Data
Corporation (SDC) which includes M&A activity searchable by date,
industry and corporate name. The SDC Tear Sheet provides all
transaction details including target and acquirer descriptions using
the following criteria:
(1) All acquiring and target firms are European public firms.
Generally speaking, the European capital markets are of less
importance as equity source in comparison to the stock markets in
the Anglo Saxon countries. Hence some major family-owned
corporations and their acquisition activities are excluded which is a
limitation of this study.
(2) The deal value of the acquisition is over one billion US dollars.
This approach is chosen in order to ensure comparability between
deals. According to Kothari (2004) the methodologies of many
event studies can be criticised as the event sample would consist of
firms with extreme (economic) characteristics such as substantial
differences in size, low market capitalisation stocks or low-priced
stocks. In these cases, correct risk estimation is difficult. Another
reason for the use of substantial deals in terms of size is that it is
aimed at measuring the impact of the acquisition on the share value
of the firm. The power of the findings is inversely related to sample
security variance. Kothari (2004) stresses: “the noisier the returns,
the harder to extract a given signal.” In addition, Dimson and Marsh
(1986) (in Agrawal et al. 1992) present persuasive evidence that
measured performance can be significantly affected by the firm size
effect.
56

(3) Financial firms are of different natures, which would reduce
power in comparability to non-financial firms and therefore are
excluded from the sample. This is in line with related literature (e.g.
Philippartos & Baird, 1996).
(4) Bidders acquire at least 50% of the targets in obtaining an
absolute control. The measurement problem induced by the
acquisition ratio of target and bidder is the subject of a paper by
Jarrell et al. (1988). They argue that, when a bidder is several
times larger than a target, a gain to the bidder equal in size to the
gain observed in the target can be hidden in the noise of the
bidder’s return variability. Statistically, the t-statistic for the
bidder’s effect is likely to be much smaller than for the target’s
effect. The resulting data contains a set of 239 acquisitions and
tender offers since 1995 where an offer price was identifiable for
inclusion in the finial sample.
The sample was further reduced for the following reason: if the
acquisition of the target is a joint venture. In these deals it is
complex to identify a unique bidder-target match and closer
inspection reveals that these cases are rather strategic
reorganisations of the target firm’s ownership structure often
without a change in control structures. Thirdly, if the takeover
commission did not approve the acquisition, the deal is excluded as
well. Also, if the acquisition is an internal group restructuring,
transactions are neither legally nor economically takeovers and no
change in control is involved. Included are acquisitions that are
subject to restrictions, such as the sale of certain assets due to
commission ruling.
(5) What further complicates the analysis is that the transaction
payment is by no means confined to just cash or shares, but may
57

comprise a mixture of the two, complex hybrid instruments like
convertible loan stock, preferred shares and equity warrants, albeit
rarely used. For consistency reasons these deals are excluded also.
(6) Deals are further distinguished by the nature of industry. In
order to construct industry groups, each merging firm’s primary 4-
digit SIC code in the year prior to acquisition was obtained from the
SDC Platinum database. The first two digits of an SIC code reveal
the industry and sub-industry of a firm. If buyers and targets
match, the acquisition is regarded as related and vice versa.
The risk-free rate is the three month money market interest rate for
the respective deal and announcement date. For the 25 European
Union countries the data is derived from the source
eurostat.cec.eu.int. For those non-EU countries, such as
Switzerland, the interest rates are derived from the respective
central bank homepages.
Stock market data is obtained from the financial database
DataStream. In the period from 01.01.1995 and 31.06.2004 daily
bidding company stock price data was available for 56 transactions.
This is approximately in line with Franks and Mayer (1998) or
Boehmer (1998), who investigated 57 and 46 deals over a nine year
and 11 year time horizon, respectively. One limitation of the
commercial source DataStream data is that data is available only for
existing stock market listed firms. Hence all acquired bidders,
delisted buyers or insolvent buyers are automatically excluded.
Therefore the sample suffers from survivorship bias. However it
should be noted that, according to a report compiled by the Funds
Management Research Centre (2002) survivorship bias is common
in event studies and authors such as Sharpe (1966), Jensen (1968),
Goetzmann and Ibbotson (1994), Malkiel (1995) and more recently
58

Blake, et al. (1999) had to accept this limitation in their studies. An
alternative approach would have been to search for relevant stock
market data in annual reports and similar publications. Given the
investigated span of 10 years and the limited time for this study,
survivorship bias has to be accepted.
59

Chapter 4: Results
Foreword
This chapter presents the descriptive findings and tests the
respective hypotheses. Then the findings are analysed and
compared to the results in the literature review. In a further section
it is intended to explore the possibility of a relationship between
abnormal share returns and the method of payment factor, the deal
approach (friendly or hostile) and whether the deal was in a related
or unrelated field of the bidding firm. The aim of this approach is to
evaluate the significance of selected M&A characteristics in
explaining the level of possible abnormal returns to the combined
firm shareholders.
Performance estimation period
The majority of researchers reports outperformance of the acquiring
firm to the market. Therefore the null hypothesis is stated by:
The null hypothesis states that during the estimation period the
bidding firm outperforms the benchmark.
In order to describe the findings in the respective periods, the
approach of Agrawal et al. (1992) is applied. Therefore the samples
are subdivided into annual portfolios. The estimation period (clean
period) is characterized by strong bidder performance, relative to
the benchmark. More precisely, the mean return of the investigated
56 deals is 19% for bidders, approximately. In comparison, the
mean stock index, the benchmark, performed at 10% on average
during the investigated 9½ years. However it should be noted that
the market performance is characterised by less volatility. The
outperformance of the stocks is of strong magnitude as, during the
60

year 2000, the 16 samples cumulated by more than 300% stronger
than the benchmark. Given a significance level of 5% the
hypothesis can be confirmed.
Table 1 Summary performance during the estimation period
Year N Ri RiC Rm RmC
1995 3 0.09 0.09 0.24 0.24
1996 4 0.30 0.40 0.57 0.81
1997 3 0.75 1.15 0.63 1.44
1998 7 0.98 2.13 1.47 2.91
1999 12 1.22 3.35 1.08 3.99
2000 16 5.02 8.37 1.79 5.78
2001 2 -0.04 8.33 -0.42 5.36
2002 4 0.32 8.65 -0.59 4.77
2003 3 1.06 9.72 0.01 4.78
2004 2 0.73 10.44 0.63 5.41
MEAN 0.19 0.10
MEDIAN 0.15 0.13
STDEV 0.41 0.14
MAX 2.26 0.33
MIN -0.47 -0.24
% winners 69.64 82.14
% losers 30.36 17.86
Note: 2004 was investigated until 30.06.2004
Overall, empirical evidence shows that bidding firms, on average,
suffer from acquisitions, experiencing negative returns over the
announcement period.
Firstly, the null hypothesis is formulated:
The mean abnormal return during the event period, derived from
the market model, is negative.
61

Table 2 summarizes the event period’s individual security abnormal
returns. For explanatory reasons CARs, AARs and CAARs are
reported as well. The average residuals are the sums of the annual
average residuals from days 20 to the announcement day. The
cumulative abnormal return of the analysed 56 transactions in the
event period is -192% cumulated over 9½ years.
Table 2: Summary Performance during the event period
Year N AR CAR AAR CAAR
1995 3 -0,13 -0,13 -0,04 -0,04
1996 4 -0,02 -0,15 0,00 -0,05
1997 3 0,06 -0,09 0,02 -0,03
1998 7 -0,08 -0,17 -0,01 -0,04
1999 12 -0,45 -0,62 -0,04 -0,08
2000 16 -1,36 -1,98 -0,08 -0,16
2001 2 0,29 -1,70 0,14 -0,02
2002 4 0,18 -1,52 0,04 0,02
2003 3 -0,26 -1,78 -0,09 -0,06
2004 2 -0,14 -1,92 -0,07 -0,13
MEAN -0,03
MEDIAN -0,03
MAX 0,18
MIN -0,39
Bidders
Significant 1
Significant No significant
Increases Decreases change
Total
% 29 43 29 100
1
Significant at the 5% level
62

The figures highlight an immense rise in blue chip firm transaction
activity in 1999 and 2000 accompanied by strong stock market
performance in Europe. Amongst the investigated 56 deals, a
notable decrease in ARs during the peak years 1999 and 2000 is
identified. The returns are abnormal as they represent the average
deviation of the annual returns on these securities from their
normal relationships with the market as derived from the market
model. Furthermore, the significantly different numbers of samples
in the respective years led to extreme differences in cumulative
abnormal returns. AAR figures are presented to provide a clearer
picture. Negative CARs are indicative of under-performing relative
to the benchmark and vice versa. However, this is how the deals
appear and is irrelevant for the hypothesis testing as every year is
weighted equally in order to calculate mean abnormal performance.
Graph three presents mean abnormal returns for the whole sample
divided into annual event windows. It clearly illustrates that in some
periods mean abnormal performance is different from zero.
However, the average abnormal return in the event period is -0.03.
A more detailed table of individual firm performance can be found in
the appendix.
The findings furthermore reveal that 29% of the deals are winners
and 49% loose amongst the investigated deals. Excessive outliers
are common, with 16 transactions featuring returns over 5% and 24
deals significantly underperforming the benchmark during the event
period.
Given the results of mean abnormal performance of -0.03, the null
hypothesis must be rejected.
Performance post-event period
The null hypothesis states:
63

The mean abnormal return during the post-event period, derived
from the market model, is significantly negative.
Similar to the above paragraph, this section summarizes mean
abnormal returns and cumulative average abnormal returns
determined through the market model. The mean abnormal
performance is minus 14%, which reveals significant negative
abnormal performance. The CARs indicates a massive -757% during
the 9½ years post-event period.
Table 3 Summary Performance during the post-event period
Year N AR CAR AAR CAAR
1995 3 -0.42 -0.42 -0.14 -0.14
1996 4 0.70 0.28 0.17 0.04
1997 3 -0.91 -0.63 -0.30 -0.27
1998 7 -0.41 -1.04 -0.06 -0.33
1999 12 -1.08 -2.12 -0.09 -0.42
2000 16 -4.53 -6.65 -0.28 -0.70
2001 2 0.00 -6.64 0.00 -0.70
2002 4 -0.66 -7.30 -0.16 -0.86
2003 3 0.09 -7.22 0.03 -0.83
2004 2 -0.35 -7.57 -0.18 -1.01
MEAN -0.14
MEDIAN -0.10
MAX 0.60
MIN -1.30
Significant 1
Significant No significant
Bidders Increases
Total
Decreases change
IN
% 32 51 16 100
1
Significant at the 5% level
64

Similar to the event period abnormal performance, a significant
increase in the magnitude of abnormal performance is identified in
1999 and particularly in 2000. Again, AAR figures are provided in
order to present a clearer picture about the unequally distributed
abnormal returns. Looking at the aggregate performance of
acquisitions, the economic importance of acquisitions with large
announcement losses overwhelms that of strong performing firms.
The CAAR, in line with the strongly negative AR is -101%. There are
32% of significant winners and 51% of deals underperforming the
benchmark by more than 5%. The deviation from zero is illustrated
in figure three.
The findings reveal that shareholders of bidding firms experience a
statistically significant wealth loss of about 14% on average after
the acquisition completion date. Given these results and a 95%
significance level, the null hypothesis can be confirmed; there is
insufficient evidence to warrant its rejection.
65

Jensen’s alpha and beta coefficients
Given that, for the event period,
estimated alpha and
beta coefficients are reviewed briefly before abnormal performance
is discussed. The control firm of this sample is provided by the
market, risk and alternative returns are presented by alpha and
beta coefficients. The strong pre-merger performance leads to
significant positive alpha coefficients. This explains much of the
negative abnormal returns during the event period and post-event
period. The following table summarizes average beta and alpha
coefficients, derived during the 250 trading-days pre-merger period.
Table 4 Alpha and beta coefficients
Average daily Average daily
Year
N
Alpha
coefficients
Beta
coefficients
1995 3 0.000178 0.25
1996 4 0.000319 0.02
1997 3 0.001068 -0.08
1998 7 0.000570 -0.03
1999 12 0.000386 0.22
2000 16 0.001521 0.01
2001 2 -0.000603 0.00
2002 4 0.000340 0.04
2003 3 0.001295 0.01
2004 2 0.001109 0.27
Note: 2004 was investigated until 30.06.2004
66

Positive alpha values are indicative of an over-performance of target
share prices with respect to share prices expected on the basis of
the market model. Beta coefficients stand for market risk. Generally
speaking, a low average beta coefficient indicates that target stocks
are defensive and vice versa. In other words, a low beta stock leads
to a decline in the value of in the above equation. Overall these
results closely resemble the trends summarized in the previous
sections.
67

Chapter 5: Analysis
Foreword
After the null hypothesis is tested, the subsequent empirical
analysis investigates bidder shareholder abnormal returns and
facilitates comparison with the respective academic literature. The
findings from the three investigated time periods (estimation
period, event period and post-event period) reveal extreme market
movements in the years 1999 and 2000. In fact, the investigated
periods illustrate major differences in performance during the same
periods.
Analysis pre-deal announcement
The estimation period (clean period) is characterized by strong
bidder performance, relative to the benchmark. However, the
outperformance is not of permanent character. As table 2
illustrates, the bulk of over performance can be attributed to the
year 2000. Moeller et al. (2005) conducted research for the US
market but during a similar time period and conclude: “If high
valuations are more likely to correspond to overvaluation in the late
1990s than at other times, it would not be surprising if the relation
between valuation and abnormal returns for that period is different
from what it is earlier.” The findings of this paper are consistent to
the results of Ellert (1976, in Dodd and Ruback, 1978) who finds
that shareholders of acquiring firms earn significant positive returns
over the seven months before the effective date of acquisition. Also
Dodd and Ruback (1978) support that stockholders of bidding firms
earn positive abnormal returns before the announcement of the
tender offer. More precisely, they report that bidders earn
significant positive abnormal returns in the 22 months before the
offer. The cumulative average residuals equal 11.69%. Although
68

Dodd and Ruback (1978) work with monthly average residuals and
cumulative monthly average residuals, they support the findings in
this study. This is not surprising as magnitudes of findings are less
when monthly instead of daily data is applied. All things being
equal, monthly data is a less precise measure, as discussed in the
methodology.
These findings are also consistent with Roll (1986), who argues in
his hubris hypothesis that hubris leads to strong pre-bid
performance. Therefore this paper confirms Roll’s hypothesis in the
sense that pre-acquisition performance provides the manager with
power, liability and cash. In addition, free cash flow theory (Jensen,
1986) can be supported in that “acquirers will tend to have
exceptionally good performance prior to acquisition. That
exceptional performance generates the free cash flow for the
acquisition.” These findings suggest that high valuations give
management more discretion, so that management can make poor
acquisitions if it values firm growth more than shareholder wealth
(Moeller et al., 2005).
Surprisingly, Firth’s (1980) study is contradictory to these findings.
Firth conducted studies about the UK market, and UK firms are also
covered in this study. Firth’s (1980) samples suggest that bidding
firms lose up to the deal announcement. He finds that during this
period 80% of bidders lose. Firstly, he applies a different
methodology (weighted average standardized portfolios) which is
furher discussed in a subsequent section. Secondly, Firth compares
deals for the period 1969-1975. This period is not characterised by
extreme market performance as during the late 1990s. In addition,
the Breadley et al. (1982) study cannot be supported in that bidders
underperform substantially before the deal announcement. Hence,
their pre-offer performance is inconsistent with the widely
supported hypothesis that on average bidders experience good
performance before making the offer.
69

Except for the fact that the above mentioned studies (except for
Firth’s paper) investigate US deals, there must be other reasons for
differences. In a subsequent section it is evaluated why there are
differences in the findings of other authors.
Analysis event period
Anrade et al. (2001, in Shleifer and Vishny, 2001) test a sample of
3,688 mergers between 1973 and 1998. They employ the same
event window as does this study: 20 days before the acquisition
announcement. They find that acquirer firms lose 3.8% on average
over this interval. This is very similar to the findings in this study (-
3.4%) and to Dodd and Ruback (1978) who find a positive
abnormal return of 2.8%. However, the results are contradictory to
Moeller et al. (2005) who find that “acquisitions in the 1990s are
profitable in the aggregate for acquiring-firm shareholders until
1997, but that the losses of acquiring-firm shareholders from 1998
through 2001 wiped out all the gains made earlier, so acquisition
announcements in the latest merger waves are costly for acquiringfirm
shareholders.”
Roll’s (1986) hubris hypothesis predicts that, around a takeover,
the value of the bidding firm should decrease.His hubris hypothesis
can neither be fully confirmed nor rejected with this sample as it
remains unknown to what extent wealth is redistributed from
bidding acquirers to target shareholders due to lack of data for
acquired firms. With respect to the wealth distribution Moeller et al.
(2005) add: “If there are synergy gains, the acquiring-firm
shareholders gain or lose less than the target shareholders gain.”
The statistically insignificant negative performance in the event
period suggests that decision makers in acquiring firms do not pay
70

too much for their targets on average. This is contradictory to the
Shleifer and Vishny (2003) overpayment theory that acquisition
announcements could have negative abnormal returns because of
the signal that a firm has run out of internal growth opportunities.
This cannot be supported here.
Analysis post-event period
After finding significant negative average abnormal performance
during the post-event period, the underperformance of the sample
firms is analysed. It is further examined whether the
underperformance is limited to acquisitions over certain time
periods. Dodd and Ruback (1977) find that, in the month of the first
public announcement of the offer, the abnormal returns to the
stockholders of target firms dominate the abnormal returns to the
stockholders of bidding firms. They find combined firm normalized
returns of -4.59% after the offer and conclude that this evidence is
inconsistent with the zero impact hypotheses.
On the other hand, Mandelker (1974) provides no support for
negative post-acquisition performance. He concludes: Stockholders
of acquired firms earn abnormal returns approximately 14%, on the
average, in the seven months preceding the merger.” In a later
study Mandelker had to revise his conclusions when he conducted a
study with Agrawal and Jaffe (Agrawal, Jaffe and Mandelker, 1992).
They find that the stocks of acquiring firms perform poorly after
acquisitions. In addition, Langetieg’s (1978, in Agrawal et al. 1992)
findings are supported in that post-acquisition abnormal
performance is constantly underperforming combined firms’ preacquisition
share price movements. Interestingly, Langetieg’s
(1978) methodology is different as he derived abnormal
performance with the BHAR approach, comparing firm performance
71

with firms in the same industry. Moeller et al. (2005) find, in line
with the majority of researchers, that: “The combined value of the
acquiring and acquired firms for the period 1998-2001 falls by more
than 7%, which is significantly different from zero.”
With regard to Roll’s hubris hypothesis, the findings of this paper
are inconsistent with the hubris and synergy hypothesis as the
combined value post-acquisition does not equal zero. The losses of
bidding shares post-acquisition indicate that the firm’s approach of
growth through takeovers is not or is no longer sustainable or is
expected to be less profitable.
Implications on the efficient market hypothesis
A finding of systematic post-underperformance or overperformance
would be inconsistent with the efficient market hypothesis. The
results indicate that the efficient market hypothesis is challenged in
two aspects. According to Khotari and Warner (2004): “…event
studies focusing on long-horizons following an event can provide
key evidence on market efficiency.” A systematic non-zero
abnormal security return after the acquisition is inconsistent with
market efficiency. In addition, an efficient market is characterized
by stock prices that adjust to corporate signals immediately, not
slowly over a period of months.
Given that during the investigated post-deal performance mean
abnormal performance is significantly other than zero (-0.14), the
analysis suggests that the efficient market hypothesis is violated.
Over and underperformances are of systematic character. More
precisely, there is a market anomaly which suggests a profitable
persistent trading rule. Therefore, the requirements of the efficient
market hypothesis are not met. Although the paid premium is not
investigated further in this paper, Shleifer’s and Vishny’s (2003)
argumentation can be supported. They stress that, if the stock
72

market would reflect all available information about an asset, any
paid premium must automatically lead into a reduction in the
bidder’s share price. Jensen and Ruback (1983) explain the
anomalies in post-acquisition returns with respect to market
efficiency, similarly. They stress: “These post-outcome negative
abnormal returns are unsettling because they are inconsistent with
market efficiency and suggest that changes in stock prices during
takeovers overestimate the future efficiency gains from
acquisitions.” Ruback (1988) later says: “Reluctantly, I think we
have to accept this result – significant negative return over the two
years following an acquisition – as a fact.”
The differences in event period and post-event period
abnormal returns
So far this study has found that, pre-merger, companies outperform
the benchmark that during the event period there is insignificant
underperformance and that during the post-event period the sample
significantly underperforms. More precisely, the mean abnormal
return during the post-event period is -14% approximately,
suggesting that the average firm of the sample underperforms the
applied benchmark significantly. Shareholders holding a portfolio of
the investigated samples lost during the 20 trading-days prior to
deal announcement: on average 3%. The difference between event
period and post-event period can be explained as follows: all
observations are weighted equally, and significantly negative mean
performances and CARs are obtained for the longer periods. Shorter
periods yield abnormal performances that are closer to zero.
According to Boehmer (1998), the small magnitude of event period
CARs to post-event period CARs can be attributed to two factors.
Firstly, in addition to the price run-up effects of potential rumours
73

and insider trading, there is substantial event-date uncertainty. This
is associated with lack of immediate publication requirements
in some countries, such as Germany or France. Secondly, there can
never be full confidence in the announcement date. There is no
guarantee that the source (SDC Platinum Database) has identified
the first publication. Some sources may have published the deal
announcement a couple of days earlier. Hence, the exact date
cannot be identified with a precision greater than about one week
(Boehmer, 1998).
Managerial performance
With reference to previous studies, the results shall also lead into a
discussion about managerial performance. The corporate control
literature explains that corporate combinations are considered as a
solution of the agency problem since the threat of being taken over
focuses managers to maximize shareholder wealth of their
companies. Therefore, better-performing firms make better
acquisitions and more value can be created in takeovers of poor
performers. Philippatos and Baird (2004) have tested this
hypothesis in an empirical investigation of the relation between
post-merger performance and merging firms’ pre-merger
performance. They conclude: “Our regression results indicate that
post-merger performance is negatively correlated with the acquiring
firm’s pre-merger performance.” This is in line with the findings in
this study and is contradictory to agency theory. The above
mentioned discussion about hubris applies.
Performance split into deal characteristics
Given the significant negative post-merger performance, further
analysis is necessary. Therefore, the samples are divided into deal
74

characteristics, which are: the nature of the deal (friendly or
hostile), whether the deal was in a related or unrelated field of the
bidding firm, and the method of payment.
Cash versus shares acquisitions
Firstly, it shall be evaluated whether the method of payment
provides any market anomaly. A portfolio is created with the
respective deal characteristics. The status quo in the literature is
that cash financed deals outperform share financed deals.
Therefore:
The null hypothesis states that the mean abnormal return of bidding
companies is higher in cash payments than in share payments.
Table 5 Portfolios of Cash-Shares acquisitions
250 tradingdays
after N
Cumulative
Cash- Shares
Cash-Shares
portfolio, AR
Acquisition
Averages
1995 3 -0.02 -0.02
1996 4 0.27 0.25
1997 3 0.04 0.29
1998 7 0.19 0.48
1999 12 -0.80 -0.32
2000 16 0.90 0.58
2001 2 0.33 0.91
2002 4 -0.01 0.90
2003 3 -0.54 0.36
2004 2 0.06 0.42
Mean abnormal return level: 0.04
75

The results reveal strong volatility during the investigated years,
especially in 1999 and 2000. During these years some extreme over
and underperformance of firms explain the results. For example in
1999, the firm Danisco acquired with cash and performed -34%
whereas the share deals of Cap Gemini and Finmeccanica increased
by 48% and 36% respectively. On the other hand in 2000 Tiscali’s
cumulated negative abnormal performance amounted to -158%
during the investigated 250 trading-days post performance. The
acquisition was financed with shares, which explains some of the
positive performance of the cash portfolio in 2000. Reviewing the
findings in more detail does not suggest any persistent patterns in
form of industry or other characteristics.
In terms of mean values, cash-financed acquisitions produce slightly
higher returns to share offers. Given a significance level of 5%,
mean abnormal returns are zero. Therefore, the null hypothesis is
rejected. This result is not in line with the majority of results of
studies on the impact of the methods of payment. Therefore, the
argument cannot be supported that, as most of the
M&A studies find, market participants value a cash offer higher than
a share value. For example, Loughran and Vijh (1997, in Mushidhi
and Ward, 2004) present their results in the form of CARs and
found that, on the post-acquisition performance over a five-year
period, companies that utilized share-based acquisitions earned
significant, negative abnormal returns (-25%), whereas companies
that completed cash-based takeovers earned significant positive
abnormal returns (61.7%). Also Moeller et al. (2005) find that
equity is used more often with large loss deals than with other
deals. In the literature (e.g. Myers and Majluf, 1984), there is an
excessive discussion of the means of payment in takeovers. An
adverse selection problem is associated with the use of equity as a
method of payment. Shleifer and Vishny (2003) stress in their
overvaluation hypothesis that the market perceives that the firm
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has no investment opportunities and will therefore reduce its value.
If this would be the case, then this were different from Myers and
Majluf (1984) theory that the signal comes form investment policy
rather than from capital structure. However, Jensen (1988) stresses
that cash offers may reveal that the firm has cash in excess of its
internal investment needs, and is likely to squander that cash on
poor investments should the bid fail. According to Bhagat et al.
(2004), an alternative explanation is that cash acquisitions indicate
strong management that is willing to commit itself to discipline in
future investments. Given the insignificant change in value for cash
and equity bidders, none of those theories can be supported here.
Modigliani and Miller (1958) state that the means by which
investments are financed are irrelevant for the value of the firm. In
their world, management is driven purely by a desire to maximize
shareholder wealth by investing in positive NPV projects. According
to the theory, managers of bidding firms cannot increase the value
of their firms by paying for their targets with cash rather than by
offering shares. Interpreting the results suggests that the method of
payment is irrelevant to the success of the acquisition. In other
words, cash paid deals do not significantly outperform share paid
deals and vice versa. This also suggests that the results are
contradictory to the Myers and Majluf (1984) Signalling Theory. The
theory suggests that the long-run acquisition performance is worse
for deals financed by equity rather than cash.
Another important implication of this finding is the Shleifer and
Vishny (2003) overvaluation hypothesis. Shleifer and Vishny (2003)
explain that overvalued firms buy undervalued firms. So-called
acquisition waves with stock would occur as stock of bidders is
overvalued as a purchase instrument. They argue that this is
“because some managers care only for the short-run market price”.
If bidders’ stock would be overvalued, there should be a pattern
that the share price of bidding firms acquiring stock should decrease
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post-acquisition in comparison to cash-financed deals. On the other
hand, target shareholders, acquired by overvalued shares should
increase in value (as explained by Roll’s hubris hypothesis). For
example, Jensen and Ruback (1983) report an average excess
return of 30% to target stockholders in successful tender offers and
20% to target stockholders in successful acquisitions. However, this
cannot be supported here. Therefore, the evidence in this study is
inconsistent with the adverse selection theory’s implication that the
use of equity is an adverse indicator of firm value.
Hostile versus friendly acquisitions
As reported above, the status quo in the literature is that hostile
deals outperform friendly deals. Therefore:
The null hypothesis states that the mean abnormal return of bidding
companies is higher in hostile acquisitions than in friendly
acquisitions.
Table 6 Portfolios of hostile-friendly acquisitions
250 tradingdays
after N
Cumulated
Hostile-Friendly,
Hostile-Friendly
(ARt)
Acquisition
Averages
1995 3 0.55 0.55
1996 4 -0.56 -0.01
1997 3 0.47 0.46
1998 7 -0.74 -0.28
1999 12 -0.31 -0.59
2000 16 0.21 -0.38
2001 2 0.23 -0.16
2002 4 0.64 0.48
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2003 3 -1.18 -0.70
2004 2 -0.06 -0.76
Mean abnormal return level: -0.08
With reference to Table 7, hostile deals significantly underperform
friendly deals. The findings are characterized by strong volatility in
the magnitude of performance. Although there is a statistically
significant underperformance, the results do not suggest any
promising trading rule. In other words, the results do not predict
any hostile or share performance in subsequent years with
confidence.
The literature suggests two contradictory explanations for the
performance of hostile and friendly deals. One school of thought
argues that hostile bids are preferred as the hostile acquisition
allows removing bad management. On the other hand, friendly
offers are perceived as opportunity to exploit business synergies.
The results are contradictory to those of Bhagat et al. (2004), who
identify higher combined bidder-target returns for hostile offers.
Also Cosh and Guest (in Bhagat et al., 2004) find that bidders share
returns in hostile takeovers’ are significantly high. They furthermore
find that friendly takeovers result in significantly negative long run
share returns, which is contradictory to this study. Moeller et al.
(2005) analyse the relationship between the size of bidder and
target and hostile and friendly deal patterns. They find that: “large
loss deals are more likely to be hostile and more likely to be tender
offers than other transactions, but the fraction of large loss deals
that are tender offers or hostile is small enough that these deals’
characteristics seem unlikely explanations.”
Bhagat, et al. (2004) furthermore explain that: “On average the
market revises upward (downward) its stand/alone valuation of
bidders that make hostile (friendly) bids.” This would suggest that
shareholders interpret hostile bids as indicating that the bidder has
79

strong cash flow prospects as a stand-alone equity, and interpreting
friendly bids as indicating agency problems. In addition, the same
authors argue that the negative revelation of friendly bidders and
the positive revelation about hostile bidders can be explained by the
fact that hostile offers are more likely to be cash and friendly offers
more prone to be equity paid deals.
Related versus unrelated acquisitions
Another subject of analysis is if the bidder and target industry
provide guidance for successful and unsuccessful acquisitions.
The null hypothesis states that the mean abnormal return of bidding
companies is higher in related than in unrelated industry fields.
Table 7 Portfolios of Related-Unrelated acquisitions
Related-
250 days after
Related-
Unrelated,
Acquisition N
Unrelated (AR) Cumulated
Completition
Averages
1995 3 0.55 0.55
1996 4 0.47 1.02
1997 3 0.04 1.06
1998 7 0.58 1.64
1999 12 -1.00 0.64
2000 16 -1.76 -1.12
2001 2 -0.22 -1.35
2002 4 -0.93 -2.28
2003 3 0.55 -1.73
2004 2 -0.06 -1.79
Mean abnormal return level: -0.18
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For the combined firm value the mean abnormal returns reveal
statistical significant underperformance for the related-unrelated
portfolio. During the 250 trading-days post-deal, the related
portfolios underperform the unrelated portfolios by 17%
approximately. Therefore, the null hypothesis must be rejected.
These findings are in line with Moeller et al. (2005) who report that
the acquisitions in their large loss deal sample are more likely to be
within the acquirer’s industry than are the other acquisitions. The
findings of this study and the very recent Moeller et al. (2005)
results are somewhat surprising as the majority of previous
research suggests that related mergers outperform unrelated
mergers. For example, Noah et al. (1998) identify lower combined
bids for diversifying offers. Hence, related acquisitions outperform
unrelated acquisitions. The general explanation is that substantial
negative cumulative performance of unrelated acquisitions can be
attributed to the lack of capabilities of acquiring firms’
management. Furthermore, a signal would be given to the market
about the quality of the bidder’s investment opportunities or
management, rather than about the advantages of the combination,
that lead to lower returns in diversifying transactions. However, the
results of this study do not support the theory that investors
perceive diversifying acquisitions as poor investments or that
management is prone to agency problems as investors do not
believe that management is familiar with the target industry (as
stressed by Jensen, 1986). The agency theory of diversification
suggests both lower true value improvements, and certainly lower
bidder returns, in cross-industry transactions than same-industry
transactions. A bulk of literature explains why diversifying
acquisitions are associated with more bidder agency problems.
Nevertheless the findings are also contradictory to the Moeller et al.
(2003 a, b) study where diversification is found to be insignificant
as a predictor of bidder announcement period returns in public
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announcements. However, it should be noted that the bulk of
underperformance occurred in 2000. Extreme stock market
performance and, generally speaking, an increase in diversification
attempts might have contributed to this result. Anecdotal evidence
suggest that during strong declines in share prices as during 2000-
2001 investors prefer less risky financial assets, look for financial
synergies and invest in diversified firms in order to lower individual
business risk. In addition, the rise and fall of some industries during
this period made the investor looking for companies of substantial
size. This might be an indicator for the strong performance of
unrelated to related companies but is by no means exhaustive. A
more sophisticated analysis is impossible due to lack of reliable
data.
Cross sectional analysis
In the last section deals were further broken down into specific
characteristics in order to present a more differentiated picture. The
following section is designed in order to investigate whether
characteristic ratios have a direct effect on the levels of abnormal
return. It is intended to determine the most influential variable.
Particularly, the strong post-event abnormal performance needs
further investigation. Therefore, the post-event window abnormal
returns (dependent variable) in time (t) will be related to firm
characteristics. For this purpose the author modifies the
multivariate regression approach, based on the Fama and French
(1993) three factor model. Abnormal returns are regressed on firm
characteristics expected to affect the return of the combined firm in
the post-event period. Specifically, equity/shares, hostile/friendly
and related/unrelated are tested for their explanatory power
(independent variables). The degree of dependence is measured by
the correlation coefficient between the input and response variable.
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Details of the regression analysis can be found in the appendix,
together with corresponding t-statistics.
Firstly, it is attempted to evaluate how well the model fits the data.
The degree to which two or more predictors (independent or X
variables) are related to the dependent (Y) variable is expressed by
the correlation coefficient R, which is the square root of R-square.
The R2 is 0.77, indicating that 77% of the variance of the abnormal
returns can be explained by the three independent variables. An R-
square of 0.77 indicates that the variability of the Y values around
the regression line is 1-0.77 times the original variance; remaining
is 23% of residual variability. Ideally, one would like to explain most
if not all of the original variability. Given the independence and
possible noise in the data, this result is sufficient in order to explain
a major part of the abnormal returns.
The sample statistic is associated with a p-value (Sig) of 0.024.
Theoretically, this means that risk rejecting the null hypothesis (R2
=O), although it is true, is less than .05. In terms of variables in the
equation, the related-unrelated beta is of the biggest magnitude,
being 1.43 with a corresponding t-statistic of 3.69. Given a positive
beta coefficient, the relationship of related-unrelated with the
abnormal return variable is positive. This is followed by cash-shares
with -1.05 with a corresponding t-statistic of -1.63 and a weak beta
hostile-friendly of 0.420 (0.788). In fact there is no statistical
significance in the hostile-friendly and weak significance in the cashshares
t-statistic. The weak t-statistics do not warrant further
investigation in order to test for the most influential factor.
Therefore the intended significance test in the form of Partial
Differentiation is not conducted. During the post-event period the
tests suggest a positive relationship between the hostile minus
friendly portfolio and the related minus unrelated portfolio. The
cash-shares portfolio is
83

characterized by a negative relationship. The high magnitude of t-
statistics for the related-unrelated portfolio is consistent with Jensen
(1986) who reports that “The t-statistics are actually higher in
magnitude for non-conglomerate acquisitions, even though they
occur with lower frequency than conglomerate acquisitions in our
sample.”
Reasons for deviations in findings
With respect to the findings of the sample information the null
hypothesis is not rejected (the status quo is correct) in the following
cases: The abnormal return in the pre event period is positive and
the post merger performance is negative. This paper finds that the
abnormal return during the event period is insignificant, the means
by which an acquisition is acquired is irrelevant and hostile offers
and related offers are associated with lower combined bidder-target
stock returns. Furthermore, there is no statistical significance found
in the comparison of equity and share post-merger performance.
Generally speaking there seems to be little consistency in findings in
the respective literature. For example Bhagat et al. (2004) find that
friendly offers, equity offers, and diversifying offers are associated
with lower combined bidder-target stock returns. It is of interest to
examine why this study comes up with results other than previous
papers. Given that the samples of this study are European firms,
even applying the same methodology as in this paper, the results
must present systematic deviations to the mostly US-based studies.
Therefore, there must be sample specific observations in average
returns. For example the often stated Mandelker (1974) paper
analyses 241 mergers that took place during 1941- 1962. Both the
acquiring and the acquired firms were listed on the New York Stock
Exchange (NYSE). In reviewing methodologies of authors who
conclude that market efficiency is violated and profitable trading
84

ules are found, Fama (1997) responds that the applied models are
extremely important and a change in models often causes an
anomaly to disappear. Fama (1997) states: “I argue that when this
happens, the anomaly is not much evidence against market
efficiency.” Fama (1997) emphasizes that market efficiency must be
tested jointly with a model for expected (normal) returns. He
stresses that tests of efficiency are always contaminated by a badmodel
problem. Consequently, the problem grows with the return
horizon: a bad-model that produces a spurious abnormal average
return of x% per month eventually becomes statistically reliable,
depending on what it is tested for, cumulative monthly abnormal
returns (CARs) or mean abnormal returns. According to Fama
(1997): “Bad-model problems are most acute with long-term buyand-hold
abnormal returns (BHARs), which compound (multiply) an
expected-return model’s problems in explaining short-term
returns.” The BHAR approach as applied by Langetieg (1978) in the
analysis section estimating abnormal returns as the difference
between an event firm’s return on a non-event firm or portfolio that
is similar in characteristics known to be related to average returns.
Decreasing homogeny in sample characteristics challenges the
BHAR approach. Some authors in the above analysis work with a
less rigorous sample in terms of firm size. If this is combined with
models such as the CAPM of Sharpe (1964) and Lintner (1965)
where these models are said not to describe expected returns on
small stocks sufficiently (Banz, 1981), the chance of less valid
abnormal returns rises. Another source of different results in event
studies is the investigated length of abnormal return measurement.
An example is the Bradley et al. (1988) paper. They investigated
takeovers during the period 1962-1984 and find contradictory to
this study, positive and stable post-merger abnormal performance
(7.4% of combined market value). However, they apply a postevent
window of five days after the public announcement of the bid
85

only. It can be argued that this is not sufficient in order to detect
post-merger abnormal performance as it provides only a fraction of
the market’s assessment. Furthermore, equal-weight returns
produce different results from value-weight returns. This paper
works with an equal-weight approach whereas the Moeller et al.
(2005) study works with value-weight returns. The impact on
results is that abnormal returns shrink a lot and typically become
statistically unreliable. Especially, the effect of event studies on
small stocks is limited in this approach. Fama (1997) stresses:
“small stocks are just a sure source of bad-model problems. Small
stocks always pose problems in tests of asset pricing models, so
they are prime candidates for bad-model problems in tests of
market efficiency on long-term returns.”
In addition, Bhagat et al. (2004) define industry codes using
Compustat SIC’s data, whereas Moeller et al. (2003a), as well as
this paper, use SDC codes.
Reasons of Failure of Merger Activity
Most empirical studies from the literature review either based on
shareholder wealth or accounting as well as the currency survey
based on latter have failed to find positive relationship between
merger activity and financial performance. There are a number of
arguments offered in this regard.
It is often claimed that the lack of market data biases studies of
accounting data. Indeed, it is argued that may be the post-merger
time period is insufficient long to capture the gains. Many
performance gains may take time to either be achieved or be
reflected to financial reports (Barnes (2000), Stickney & Brown
(1999)).
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Another reason that justifies the absence of observed gains in the
empirical evidence focuses on managerial behaviour. It is argued
that there is a significant lack of alignment between the interests of
shareholders and managers (Jenses 1986). Regarding this point of
view, merger activity is in the best interests of managers but not
necessarily of shareholders. Managers are engaged in the takeover
activity to increase their power and remuneration that are both
assumed to be related to the institutional scale. This behaviour,
however, comes at the expense of shareholders of the acquiring
institution who in general overpay for such acquisitions and suffer
dilution due to absence of mutual objectives with their agents.
Buono et al (1985) and Spiegel & Gart (1996) attributed “Human
resource problems” as being responsible for the major proposition
of merger failure. Those studies have also examined the effects of
mergers on a wide range of management issues, such as culture
and argue that the whole human resource problem could be
reflected to the failure of cultural compatibility. Generally, the
difference of culture between two counter parties might be derived
from historical, geographical background, industrial nature and the
attitude of executive managers. The failure of the integration of
culture might result in the employee work inefficiency and then in
the decrease of merger synergy.
Clarck (1991) argues that often the merger deal is a threshold
event for the best customers of the acquired company. If the
acquired company was an important supplier in the past, the
customers wonder whether the change forces it to make changes in
vendor arrangements. Furthermore, the change in ownership has
opened the door for competitors to approach the acquired best
customers. Clarck’s study revealed that it cost approximately five
times more to acquire a new customer than it does to retain and
87

service an existing one. Also, it is revealed that 91% of unhappy
customers will communicate their dissatisfaction to at least nine
other people, which implies that the bad news will spread extremely
quickly. Hence it is of significant importance to retain customers
and new classifications caused by merger process may fail to
achieve this.
Eccles (1999) states that, many failures occur simply because the
acquiring firm paid too much for the acquisition. In specific he
claims, “if it wasn’t a good deal on the day it was made, it will never
be “. Sudarsanam (1995) suggests that even experienced acquires
who should know pricing acquisition better, sometimes get too
attached to a deal. When that happens it is essential to have
organisational disciplines in place that will rein in the emotion. The
question for the two authors is not whether an acquirer has paid too
high a price in an absolute sense rather he has paid more than the
acquisition was worth to that particular company. What one
company can afford will differ from what another company can
afford and, more than likely, from the asking price. They conclude
that the key to success in buying another company is, knowing the
maximum price you can pay and then having the discipline not to
pay a penny more.
An additional reason, which can explain the cause of failure of
merger activity in this specific survey, is antitrust regulations. In
the U.K., mergers have been subject of antitrust regulation since
1965, during which period the U.K. government’s policy has gone
through distinct phases. While the main trust of antitrust regulation
has been the maintenance of effective competition, many other
issues of public interest have been considered, from time to time,
relevant in determining whether a merger should be allowed. To
88

conclude, it is not difficult to find that those regulations 1
emphasised on passive encouragement rather than positive
advocate for those companies that wanted to be engaged into a
takeover process.
Majority of the merger activity has to be permitted or examined by
related authorities, a process that potentially postpones the
proceeding of merger. Indeed to maintain competition the
restriction in the remittance amount is confined, which might
decrease the investment aspiration and opportunity. The role of
government in the U.K. appears to be more of an investigator
rather than an assistant to merger process and this may be an
explanation to the weak post merger performance.
1 U.K. merger regime in accordance with Hughes (1993)
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Chapter 6: Conclusions
Foreword
The vast majority of previous studies have been conducted on the
US market. The aim of this study was to determine if acquisition
announcements have a similar impact on shares prices of European
companies. Applying a rigorous approach by excluding all deals
which do not fulfil the criteria discussed in the methodology, this
study measured abnormal performance with the market model.
Supported and rejected hypothesis’
Earlier studies of completed acquisitions report that stockholders of
the firms involved earn abnormal returns before the effective date
of acquisition (Dodd and Ruback, 1978). This pattern is found in this
study, too. In fact, shareholders of bidding firms earn positive
average abnormal returns, 250 trading-days before the event
period. These gains are of substantial character. All things being
equal, this leads to free cash flow in excess of that required to fund
all positive NPV projects.
If this excess cash flow is invested wisely in merger activities is
evaluated in the event window and post-event window. However, it
is found that pre acquisition performance is not an indicator for post
acquisition performance. The author finds that firms announcing
major acquisitions in 1999 and 2000 are characterised by negative
performance during the post-event period. After 2001 these losses
cannot be recovered. Therefore, acquisitions are costly for bidding
firms during the investigated period. The losses can be attributed to
few substantial negative acquisition announcements during the
1999-2000 periods. It is expected that future results, excluding
extreme periods like 1999 and 2000 reveals a more positive picture.
90

It is concluded that the Jensen and Ruback (1992) findings of
negative post-merger performances are supported and that the
efficient-market anomaly is not resolved. The underperformance
holds for all years from 1997-2004 with the exception of 2001(AR
0) and 2003 (AR 0.09). This paper also finds that hostile offers and
related offers are associated with lower combined firm returns. An
investigation of transaction characteristics shows that abnormal
returns and the related-unrelated portfolio are significantly
positively correlated.
Reviewing the method of payment findings suggests that the
medium with which an acquisition is financed is irrelevant. This
challenges the proposition that deals made with shares signal
payout of resources as a positive signal to investors. It also rejects
the hypothesis that stock acquisitions tend to be more likely to be
associated with growth opportunities and a shortage of free cash
flow. Breaking the results down further into deal characteristics
reveals the surprising result that diversification acquisitions
outperform industry related deals. This is not only contradictory to
the bulk of previous performance studies but also contradictory to
agency theory. Jensen (1986) stresses that diversification
programmes are more likely to generate losses than takeovers in
the same line of business. He describes that managers with excess
cash flows and unused borrowing power are more prone to poor
investment decisions. However, he fails to explain why those factors
are more severe for related than unrelated acquisitions. In addition,
it was attempted to evaluate which characteristic can be used to
predict abnormal returns. Therefore, the author modified the
Fama/French three factor model. Cash to shares, hostile to friendly
and related to unrelated portfolios are the identified independent
variables which typically affect abnormal returns. The investigation
reveals some directional results, but only the related-unrelated
regression reveals statistical significance in t-statistics.
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The management factor
One plus one makes three: this equation is the special alchemy of
an acquisition. Given the weak post merger performance, it can be
concluded that the the price of making a mistake is greater than the
price of missing an opportunity. Reasons for underperformance
vary: there may be a vast difference between the price one
company can pay for an acquisition and the price another can pay.
The key to success in buying another company is knowing the
maximum price to pay and having the discipline not to pay more.
Paying too much because of ‘strategic reasons’ can be attributed to
‘individual decision making’ (Roll, 1986). The poor post-merger
performance can be referred to managerial opportunism and glory
seeking. The executive ego, which is boosted by buying the
competition, is a major force in M&A, especially when combined
with the influences from bankers, lawyers and other assorted
advisers who can earn big fees from clients engaged in acquisitions.
Many studies over the last several decades have found that people
are generally overconfident about the accuracy of their knowledge.
In an M&A environment, an overconfident CEO is prone to pursue
risky deals, or pay too much, because she overestimates the return
she can produce from an acquisition. Shefrin (2004, in Teach, 2004)
argues: “Every CEO who goes into [an acquisition] thinks he is
different – that he will be able to pull it off.” Another reason why
managers engage in acquisition activities beyond the optimal size of
their firm is management compensation. Murphy (1985) finds that
management compensation is positively related to the size of the
firm.
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Unresolved problems and suggestions for further research
The existing literature on the post-acquisition performance of
bidding firms is divided. Given the conflicting results to prior
studies, it cannot be concluded that issues of over and
underperformance are solved. The findings are contradictory to a
number of studies, which is due to several reasons. Two possibilities
seem to be left as to why underperformance is found in event
studies in finance. Either the abnormal returns are due to mispricing,
or the applied methodologies are incorrect. Today, the
reason for the significant underperformance post-merger often
remains unknown. In addition, the unsolved contradiction to the
efficient market hypothesis is why share prices adjust to corporate
signals with some time delay, slowly over a period of months or
years. Given that acquisitions are one way managers spend cash
instead of paying it out to shareholders, the challenge to overcome
is how to solve paying out the excess cash but not investing it in
negative NPV acquisitions.
So far, little is known about European acquisitions as the majority of
researchers have focused on the US market. Given the importance
of this market, this is surprising. The author hopes that this work
contributes to the knowledge in acquisition performance studies.
European specific characteristics such as the bulk of non-stock listed
businesses cannot be excluded on a continuing basis. The author
suggests that stock market listed versus non-stock market listed
deals should be analysed. This is left for further research.
93

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Appendices
Appendix 1 abnormal performance
Performance estimation period
estimation period
Acquiror Ri Rm
Glaxo 1995 0.17 -0.03
Scottish Power 1995 0.01 0.16
Hanson 1995 -0.08 0.10
Rentokil 1996 0.39 0.17
Kvaerner 1996 -0.26 0.15
Scottish Power 1996 0.05 0.13
II
Cable and Wir. 1996 0.11 0.12
Rallye 1997 0.20 0.21
Lafarge 1997 0.26 0.18
Thyssen 1997 0.30 0.25
DSM 1998 0.04 0.16
CGE 1998 -0.45 0.21
Akzo 1998 0.42 0.28
Carrefour I 1998 0.07 0.26
Total I 1998 0.15 0.19
Sanofi 1998 0.46 0.20
Astra 1998 0.29 0.17
Danisco 1999 -0.22 0.19
Gecina 1999 0.16 0.02
Vivendi 1999 0.19 0.04
Cap Gemini 1999 0.16 0.01
Total II 1999 0.08 0.01
Linde 1999 0.39 0.10
Carrefour II 1999 -0.47 0.11
Vedior 1999 0.65 0.13
Finmeccanica 1999 -0.16 0.20
RWE 1999 -0.04 0.16
104

Anglo American 1999 0.66 0.13
Vodafone 1999 -0.18 0.15
Glaxo II 2000 -0.08 0.20
Clariant 2000 0.46 0.24
Saint Gobain 2000 0.15 0.24
BP 2000 0.75 0.22
Telefonica 2000 -0.28 0.16
ENI 2000 0.84 0.15
France Telecom 2000 0.82 0.10
Publics
2000 0.32 0.19
Grouppe
Vivendi II 2000 -0.03 0.12
Vinci 2000 0.10 0.09
Novartis 2000 -0.14 0.08
Ahold 2000 2.26 0.10
Tiscali 2000 0.00 0.07
Smiths 2000 -0.11 -0.17
RWEII 2000 0.19 -0.16
ENI II 2000 -0.25 -0.18
Lafarge II 2001 -0.06 -0.24
Schneider 2001 0.01 -0.06
RWE III 2002 -0.19 -0.11
National Grid 2002 0.22 -0.16
Kone 2002 0.14 0.25
ENI III 2002 0.16 -0.10
Morisson 2003 0.53 -0.19
Roche 2003 0.28 0.29
Svendborg 2003 0.25 0.08
Sanofi II 2004 0.19 0.13
UCB 2004 0.47 0.33
COUNT 56 56
MEAN 0.19 0.10
MEDIAN 0.15 0.13
MAX 2.26 0.33
MIN -0.47 -0.24
Per cent winners 69.64 82.14
Per cent losers 30.36 17.86
105

Performance event period
event period
Acquiror
AR
Glaxo 1995 -0.07
Scottish Power 1995 -0.08
Hanson 1995 0.01
Rentokil 1996 -0.04
Kvaerner 1996 0.07
Scottish Power II 1996 -0.09
Cable and Wir. 1996 0.05
Rallye 1997 -0.08
Lafarge 1997 0.00
Thyssen 1997 -0.02
DSM 1998 0.07
CGE 1998 0.11
Akzo 1998 -0.05
Carrefour I 1998 -0.18
Total I 1998 -0.09
Sanofi 1998 0.06
Astra 1998 0.15
Danisco 1999 0.01
Gecina 1999 -0.07
Vivendi 1999 0.07
Cap Gemini 1999 -0.05
Total II 1999 -0.01
Linde 1999 -0.11
Carrefour II 1999 -0.35
Vedior 1999 0.06
Finmeccanica 1999 0.14
RWE 1999 0.00
Anglo American 1999 -0.09
Vodafone 1999 -0.06
Glaxo II 2000 0.05
Clariant 2000 -0.04
Saint Gobain 2000 -0.34
BP 2000 0.10
Telefonica 2000 -0.15
106

ENI 2000 0.09
France Telecom 2000 -0.12
Publics Grouppe 2000 -0.02
Vivendi II 2000 -0.17
Vinci 2000 0.07
Novartis 2000 -0.03
Ahold 2000 0.01
Tiscali 2000 -0.39
Smiths 2000 -0.33
RWEII 2000 -0.12
ENI II 2000 0.03
Lafarge II 2001 0.18
Schneider 2001 0.10
RWE III 2002 0.05
National Grid 2002 0.15
Kone 2002 -0.07
ENI III 2002 0.05
Morisson 2003 -0.12
Roche 2003 -0.19
Svendborg 2003 0.05
Sanofi II 2004 -0.09
UCB 2004 -0.06
COUNT 56
MEAN -0.03
MEDIAN -0.03
MAX 0.18
MIN -0.39
Per cent winners 0.43
Per cent losers 0.57
107

Performance post-event period
post-event period
Acquiror
AR
Glaxo 1995 -0.11
Scottish Power 1995 -0.05
Hanson 1995 -0.26
Rentokil 1996 -0.10
Kvaerner 1996 0.60
Scottish Power II 1996 -0.05
Cable and Wir. 1996 0.07
Rallye 1997 -0.24
Lafarge 1997 -0.02
Thyssen 1997 -0.66
DSM 1998 -0.04
CGE 1998 0.50
Akzo 1998 -0.69
Carrefour I 1998 0.26
Total I 1998 0.13
Sanofi 1998 -0.34
Astra 1998 -0.21
Danisco 1999 -0.17
Gecina 1999 -0.29
Vivendi 1999 0.03
Cap Gemini 1999 0.23
Total II 1999 0.16
Linde 1999 -0.35
Carrefour II 1999 0.26
Vedior 1999 0.41
Finmeccanica 1999 0.43
RWE 1999 0.17
Anglo American 1999 -0.61
Vodafone 1999 -0.65
Glaxo II 2000 0.21
Clariant 2000 -0.26
Saint Gobain 2000 -1.04
BP 2000 -0.49
Telefonica 2000 -0.86
108

ENI 2000 0.33
France Telecom 2000 -1.30
Publics Grouppe 2000 -0.76
Vivendi II 2000 -0.47
Vinci 2000 0.29
Novartis 2000 -0.15
Ahold 2000 0.05
Tiscali 2000 -0.78
Smiths 2000 0.01
RWEII 2000 0.15
ENI II 2000 -0.24
Lafarge II 2001 0.26
Schneider 2001 -0.26
RWE III 2002 -0.53
National Grid 2002 0.05
Kone 2002 -0.17
ENI III 2002 -0.01
Morisson 2003 0.23
Roche 2003 -0.30
Svendborg 2003 0.16
Sanofi II 2004 -0.12
UCB 2004 -0.23
COUNT 56
MEAN -0.14
MEDIAN -0.10
MAX 0.60
MIN -1.30
Per cent winners 0.39
Per cent losers 0.61
109

Appendix 2 Regression of Characteristics (SPSS)
Two-stage Least Squares
110

Appendix 3 Performance Graph DS non-financial European stock
index to two major European stock indeces.
111