Event study on stock returns from UK acquisitions

Advanced Corporate Finance 3. May 2010 Exam. No. 402387
Event study on the impact of mergers and acquisitions
Group members in regards to collecting and programming:
Exam No. 402380
Exam No. 402387
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Table of Contents
Event study on the impact of mergers and acquisitions..............................................................1
Table of Contents...................................................................................................................................... 2
1. Introduction........................................................................................................................................... 3
1.1 Problem statement ..................................................................................................................................... 3
1.2 Delimitation.................................................................................................................................................. 3
2. Literature review................................................................................................................................. 4
2.1 Motives for acquisitions............................................................................................................................ 4
2.1.1 Neoclassical theories.............................................................................................................................................. 4
2.1.2 Behavioural theories ............................................................................................................................................. 5
2.2 Empirical evidence on short term stock performance on announcement of acquisition.....6
3. Hypothesis.............................................................................................................................................. 7
4. Methodology.......................................................................................................................................... 7
4.1 The event window....................................................................................................................................... 7
4.2 The estimation period................................................................................................................................ 8
4.3 Abnormal return.......................................................................................................................................... 8
4.4 Statistical test............................................................................................................................................. 10
4.4.1 Parametric tests..................................................................................................................................................... 10
4.4.2 Non-parametric test............................................................................................................................................. 10
4.4.3 Cross sectional regression.................................................................................................................................11
5. Data........................................................................................................................................................ 11
5.1 Data collection........................................................................................................................................... 11
5.1.1 Selection criteria.................................................................................................................................................... 11
5.1.2 Deal status, type and final stake......................................................................................................................11
5.1.3 Banking, Insurance and Financial Services Companies.........................................................................11
5.1.4 Deal value ................................................................................................................................................................ 12
5.1.5 Datastream............................................................................................................................................................... 12
5.2 Thin trading................................................................................................................................................ 12
5.3 Data descriptive........................................................................................................................................ 13
6. Empirical evidence............................................................................................................................ 14
6.1 Test result................................................................................................................................................... 14
6.1.1 Cross sectional regression.................................................................................................................................15
6.2 Comparison to existing empirical studies.........................................................................................16
7. Conclusion............................................................................................................................................ 16
8. References............................................................................................................................................ 18
Abstract
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This paper analyses the stock returns to shareholders of firms in the United Kingdom, hereinafter
referred to as the UK, acquiring domestic UK firms and cross border firms within the EU from
2006 until today (2010). The paper includes 92 acquisitions within the UK and 53 cross border
acquisitions within the EU. The paper comes to the conclusion that listed firms have a significant
positive impact on the acquiring shareholders wealth. The study concludes an overall significant
abnormal return of 1,1499% for the entire portfolio.
1. Introduction
Today, mergers and acquisitions, hereinafter referred to as M&A’s, are universal, with companies
acquiring targets all over the world. Mergers and acquisitions represent massive reallocation of
resources, both within and across industries and countries and therefore for many years has been the
interest of empirical studies.
There have been 3 merger waves in the 1960s with the conglomerate takeovers, in the 1980s with
the hostile “bust-up” takeovers and in the 1990s the “strategy” or “global” takeovers. Historically,
large number of these merger and acquisitions were concentrated in the USA and also in the UK.
Extensive research has been undertaken on whether acquisition are wealth creating or wealth
reducing events for shareholders and empirical studies have revealed that mergers appear to provide
at best a mixed performance to the various stakeholders involved. Target-firms shareholders
generally enjoy positive short term returns, while investors in the acquiring firms often experience
share price underperformance in the month following the announcement of a merger.
An interesting viewpoint is to look at the European Union with its single monetary union. This
paper will look on the effect of firms in the UK acquiring domestic UK firms and cross border firms
within the EU.
1.1 Problem statement
The focus of this paper is to examining the effect of UK firms acquiring domestic UK firms and
cross border firms within the EU from 2006 until today (2010). Has there been a wealth creating or
wealth reducing outcome for the acquiring shareholders and is there a difference in the abnormal
return in the acquisition of domestic or cross border firms for the acquiring shareholders. The
empirical tests will be based on event study methodology.
1.2 Delimitation
When examining the effect of mergers and acquisitions it can be done from different point of views
of either the target shareholders, the acquiring shareholders or the firm as a hole. According to very
clear empirical evidence stating that mergers and acquisitions are wealth creating for target
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shareholders, therefore this paper will focus only on acquirer shareholders where it seems more
uncertain as to whether it creates or destruct wealth for the shareholders. There will only be looked
at acquisitions and not on mergers.
Many different factors can take part in explaining the abnormal return as for example firm size,
payment method, debt to equity and merger waves. The paper will only focus on the short-term
effects of an acquisition with a final stake of 100% leaving out acquisitions with a lower stake and
mergers. The paper is also focusing on the effect in the domestic and cross-border variable meaning
differences in returns between UK firms acquiring domestic UK firms and cross border firms within
the EU.
2. Literature review
The literature gives a brief overview of relevant theory and relevant empirical findings concerning
mergers and acquisitions.
2.1 Motives for acquisitions
Many different theories have been stated to explain the phenomenon of M&A and the reasons and
motivations driving them. The theories can roughly be divided into the two main groups of
neoclassical theories and behavioural theories where the first focus on the assumption of managers
being rational and making rational choices in striving to maximize wealth for the shareholders and
the second is based on the assumption that managers not necessarily are rational or representing the
interests of the shareholders. These theories can furthermore be divided into internal and external
motives. Where the internal motives such as hubris, synergy and agency costs can be influenced by
that management and the external factors such as globalization, deregulation and technology cannot
be influenced directly by management.
2.1.1 Neoclassical theories
One of the motive theories under the neoclassical thoughts is the Synergy motive which assumes
that managers only will engage in M&A’s if it results in positive gains for both the target and
acquiring shareholders hence creating a synergy with positively correlated positive gains for both
set of shareholders1
. In other words the synergy motive exists if the combination of the firms has a
greater value than the two separate firms due to factors as improvements in efficiency and increases
in market power of the combined firm. One of the most frequently mentioned synergies in respect
to M&A motives is operating synergies as economies of scope and economies of scale for example
being able to offer a wider range of products. Other kinds of synergies can for example be financial
1
Berkovitch, E. & Narayanan, M. P. (1993): Motives for takeovers: An empirical Investigation
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synergies between a firm with excess capital but small growth possibilities and another with large
growth opportunities but a need for additional financing that together could reach greater results.
According to Jarrad Harford, M&A can also partly be explained by technological, economic and
regulatory shocks to the economy2
. If the environment of a firm changes the rational manager that is
assumed to exist under the neoclassical theory will have to react to these changes in order to keep
the firm performing effectively. If for example a new technologic is introduced in the market that a
given firm does not have access to an M&A action between itself and another company with this
technologic expertise could create positive synergies.
2.1.2 Behavioural theories
Behavioural theories can be divided into agency motives where managers are still assumed rational
but not representing the shareholder’s best interests or Hubris motives where managers are assumed
non‐rational.
Under the Agency theory problems arise because managers do not act in a way that maximizes
value for the shareholders. The agency problems as described by Jensen and Meckling (1976) can
arise due to managers only owning a small part of the ownership shares of a firm and other owners
not owning a large enough share of the company to have sufficiently incentive to monitor the
behaviour of the managers closely. Under these problems Managers may act to maximize their own
interests rather than those of the shareholders for example to avoid control loss which could deprive
them of private benefits and they may therefore settle for a low premium offer from a bidder in
exchange for a share in management control of the merged company which in this case would dilute
the gain to the target shareholders3
. Or management might be reluctant to pay out excess cash flows
to shareholders because it will reduce the control of resources of the management and they will
instead engage in takeover activities even though this might not maximize value for the
shareholders.
Another behavioural theory is that of empire building where managers will maximize the size of the
firm by engaging in acquisition activities and thereby increase their personal compensation that
might be coupled to firm size.
Another dimension of the behavioural theories that does not assume rational managers is that of
Hubris motives. Under this assumption acquisitions can be motivated by managers mistakes in for
example valuation by being overoptimistic and therefore paying too much for a company which will
2
Harford, J. (2005): What drives merger waves?
3
Sudarsanam, Creating value from mergers and acquisitions (2003) p. 57
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dilute any possible gains from real synergies that might exist as suggested by Roll (1986)4
. The
Hubris motive therefore assumes that managers actually try to maximize shareholder value but due
to irrationality isn’t capable of doing it. Shareholders of the acquiring firm will therefore experience
negative returns since there is no real economic rationale for the acquisition and therefore no gains
to offset costs of for example integration.
2.2 Empirical evidence on short term stock performance on announcement of acquisition
Earlier conducted empirical studies have found evidence pointing towards that shareholders of
target firms experience positive abnormal returns while shareholders of acquiring firms experience
significantly lower returns, that if not negative, often at best is around break even.
Jensen and Ruback (1983) for example concluded on the basis of their empirical studies that the
shareholders of target firms earn significantly positive returns whereas the returns to the
shareholders of the acquiring firms were close to zero5
. However the evidence concerning the
acquiring firm’s shareholder return was less uniform and more dependent of the length of the event
window so that the abnormal return detected for acquiring firm shareholders increased if expanding
the window. These findings were backed by a study of returns conducted by Jarrell et. al6
. A study
by Andrade et.al7
. found that average abnormal return to acquiring shareholders were equal to ‐
0,7% but since this result wasn’t significant anything couldn’t be firmly concluded on whether
acquiring shareholders were losers in the acquisition game. Another study by Moeller et.al.8
found
that the average abnormal return to the acquiring firms shareholders over the period had been 1.1%
but due to a small number of takeovers creating extremely large losses the total loss to the
shareholders of the acquiring firms were 216 billion dollars from 1991 to 2001. Positive abnormal
return can therefore not be inferred as meaning that the acquiring shareholders have necessarily
gained from the acquisitions.
A paper by Roades9
provided more diversified results for acquiring firms on the basis of 21 studies
conducted in the period 1980-1993. He found that there were significant negative effects on the
stock returns of the acquiring companies in seven of the papers, in seven others there were no
effect, forgave mixed results and three found significant positive returns giving recognition to the
synergy theory.
4
Roll.R., (1986)The Hubris Hypothesis of Corporate Takeovers p. 200
5
Jensen, M. C. and Ruback R.S., (1983),The market for corporate control: The evidence p. 22
6
Jarrell, G. A. et.al. (1988): The Market for Corporate Control: The Empirical Evidence Since 1980 p 51
7
Andrade, G., Mitchell, M. & Stafford, E: (2001): New Evidence and Perspectives on Mergers
8
Moeller, S. B. et.al. (2005): Wealth Destruction on a Massive Scale? A Study of Acquiring Firm returns in the Recent
Merger Wave
9
Rhoades, Stephen A. (1994) ”A Summary of Merger Performance Studies in Banking, 1980–93, and an Assessment of
the ‘‘Operating Performance’’ and ‘‘Event Study’’ Methodologies”
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3. Hypothesis
The theory and literature reviewed in section 2 point towards that the shareholders of the acquiring
firm doesn’t experience abnormal return but this will be further tested in this paper. According to
the theory of the efficient market hypothesis any effect from the event will be immediately adopted
in the prices and will therefore be detectable in the event window set. According to Moeller et. Al.
(2005) and Andrade et. Al. (2001) acquisitions are in general wealth destructive from the acquiring
shareholders point of view. These earlier findings will therefore be tested whether there is a
significant difference in abnormal return for shareholders of the acquiring firm and whether there is
a significant difference in the abnormal return for shareholders of the acquiring UK firms in regards
to domestic UK target firms or cross border EU target firms. This leads to the formulation of the
following hypotheses to be tested:
1. Acquisitions do not create short term abnormal returns for the shareholders of the
acquiring firm around the period of the announcement of the acquisition.
2. There is a significant difference between the abnormal return created by UK firm
acquiring domestic UK firms and UK firm acquiring cross border firms within the EU.
4. Methodology
To test the hypothesis stated in the section above the method of an event study will be used and
conducted to determine any abnormal return in the event window around the acquisition.
An event study is an econometric method to measure the impact on a company from a certain event
and is one of the most used empirical methods in finance and accounting. The event study
methodology was introduced by Fama et. al. in 1969 in the paper “The adjustment of stock prices to
new information” of measuring changes in security prices from an event or announcement as done
in this paper 10
. An event study is an econometric method to measure the impact on a company from
a certain event and is one of the most used empirical methods in finance and accounting.
Accordingly to the efficient market hypothesis the effects of an event will immediately be reflected
in the security prices and the event study methodology has its strength in measuring these
implications11
.
4.1 The event window
The event window determines the number of days over which we measure the possible abnormal
return caused by the event. The theory of the efficient market hypothesis, mentioned in the literature
review, proposes that any shift in stock prices caused by the event will happen immediately due to
10
Sudarsanam, Creating value from mergers and acquisitions (2003)
11
Pilloff and Santomero, The Values Effects of Bank Mergers and Acqusitions (1997)
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rational behaviour which talks in favour of a short event window since a long window could risk
diluting the possibility if finding any significant evidence. However if the event window is too short
we risk not catching the effect of the event if the information comes out after the closing of the
market and therefore doesn’t reaches the public until the next day or if the information is leaked the
day before the announcement and therefore causes the effect the day before the actual
announcement/event day. To make sure that these possibilities are accounted for, the event window
is set to three days containing the announcement day and the day prior to it and after it.
4.2 The estimation period
The estimation period is used to estimate the expected return of the stocks. The period therefore
needs to be long enough to create a representative measure of returns but too long and estimation
period can risk biasing the estimation with information from other events or changes in the firms
general conditions. It is normally set at around a year of trading prior to the event window12
. In this
paper it is set to 200 trading days when the weekends are excluded and the three days of the event
window are kept separate from the estimation period. This is done to make sure that the normal
returns don’t get influenced by event related returns: The timeline of the event study is illustrated in
figure 1.
Figure 1 - Timeline
4.3 Abnormal return
In order to test for an effect of the announcement on the stock prices we need to find the abnormal
return in the event period. The abnormal return can be expressed as the actual return, subtracted the
expected return if the event had not occurred.
ARit = Rit - E(Rit|Xt)13
Where ARit is the abnormal return, Rit the actual return, and E(Rit|Xt)14
the expected return for
company i.
When estimating the actual return, there are several ways of doing so. In this paper the market
model will be used due to its inclusion of the mean adjusted model and market adjusted model and
12
Bartholdy et. al. Conducting Event studies on a small stock exchange (2005) p.5
13
14
Can also be denoted Rˆit accordingly to Broan and Warner (1985)
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-1 0
1
1-200
Estimation period Event window

incorporation of the constant mean return model. The market model is the most widely used model
because it takes explicit account of the risk associated with the market and means returns15
. The
market model is a statistical model that relates the return of any given security to the return of the
market portfolio16
. The market model for any stock i is:
it i i mt itR Rα β ε= + +
Rit is the actual return of a given stock i at time t and Rmt is the market price index connected with
the stock i at time t. An OLS regression is performed to determine the model parameters estimates
of αi and βi the intercept and slope respectively, for each stocks at every day in the estimation
period. On the basis of this the abnormal return can then by measured for each stocks at every day
in the estimation period and event window. In order to make an overall conclusion of abnormal
return in the event window the concept of cumulative abnormal return (CAR) over the event
window must be used17
CAR is the sum of the abnormal returns for the three days in the event
window.
The market model parameters are obtained in the estimation period and used in the event period to
estimate the expected return, R^it. The expected return is calculated in the following way:
R
^
it=α
^
i+β
^
iRmt
The abnormal return ARit is now possible to calculate in the event window by subtracting the actual
return Rit, with the expected return, Rˆit, as shown in the equation ARit = Rit - E(Rit|Xt).
In order to make an overall conclusion of abnormal return in the event window the concept of
cumulative abnormal return (CAR) over the event window must be used18
CAR is the sum of the
abnormal returns for the three days in the event window, (-1;1), the cumulative abnormal return
(CAR) model is used.
CAR=Ai,−1+Ai,0+Ai,1
15
Brown and Warner, Measuring security price performance (1985)
16
Mackinley, Event Studies in Economics and Finance (1997) p.18
17
18
MacKinlay; Event Studies in Economics and Finance (1997) p.21
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4.4 Statistical test
To test the hypotheses stated in section 3, a battery of both parametric and non-parametric tests are
used and in the end a cross sectional regression is performed to test for differences in the
explanation on abnormal return from UK firms acquiring domestic UK firms or cross border firms
within the EU. The parametric test requires normal distributed returns and the non-parametric test
requires non-normal returns meaning that it does not have the assumption of normal distributed
returns19
. Accordingly to Bartholdy et. al. (2007) the non-parametric tests generally outperform the
parametric test.
4.4.1 Parametric tests
Parametric tests are performed on the assumption of normal distributed returns and the test statistics
for abnormal returns on the event days is based on a standard t test of the difference between two
means20
. The Central Limit Theorem guarantees that the distribution of the mean abnormal return
measure converges to normality as the number of firms in the sample increases if the measures of
abnormal returns in the cross section of firms are independent and identically distributed drawings
from finite variance distributions21
. It is therefore assumed that the conventional t-statistic will be
well specified with a sufficiently large sample. First the parametric test T1 – Cross sectional
dependence is used to test the stated hypotheses. In this test the standard deviation is estimated over
a portfolio using the time series of portfolio returns. The test T3 – Standardized excess return
instead uses a scaling of the abnormal returns by their individual standard deviation and then adds
them together. This test will therefore also be used to test the hypothesis to see if it differs in result.
In an event study performed by Bartholdy et.al. the standardized excess return test is concluded to
perform the best. TCAR is estimated for both the T1 and the T3 test to see whether there is a
significant abnormal return over all days in the event window.
4.4.2 Non-parametric test
When there are problems with normality in the returns, which might occur due to small samples and
few trades, the non-parametric tests can be used since they do not have the assumption of normal
distributed returns and will therefore create more reliable results than the parametric test if this
assumption is not satisfied. Also by including the nonparametric tests it provides a check of the
robustness of conclusions based on the parametric tests22
and the two common non-parametric tests
for event studies; T4 Corrados Rank test and T5 Sign test are therefore conducted as well. The Rank
19
Bartholdy, et. al. Conducting Event studies on a small stock exchange (2007)
20
Bartholdy et.al. Conducting Event studies on a small stock exchange (2007) p.9
21
J. D. Lyon et. al., Improved Methods for Tests of Long Run Abnormal Stock Returns (1999) p.178
22
MacKinlay; Event Studies in Economics and Finance (1997) p.32
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test proved to be power full on the thickly traded stocks. The Sign test tells us about the direction of
the abnormal return since it ascribes a + or – for each return regardless of the size of it.
4.4.3 Cross sectional regression
A cross sectional regression can be used to explain the wealth effect from the announcement by
determining which factors play a part in explaining the effect. In order to test the hypothesis of a
significant difference between the abnormal return created by UK firm acquisitions domestic UK
firms and cross border firms within the EU. A cross sectional regression is conducted in Excel
where CAR for the portfolio of stocks is set as the dependent variable and regressed with a Dummy
of domestic vs. cross border as the explaining variable. The Dummy is activated with a 0 if the
stock is cross border and otherwise 1 if it is a domestic.
5. Data
The following section provides an evaluation of the data collection process and a description of the
selection criteria’s for the chosen firms.
5.1 Data collection
A Number of firms have been found through a screening process in the database Zephyr that holds
data on M&A in Europe since around 2000 and covers more than 600.000 M&A. Since Zephyr
does not contain financial data on the firms the data will afterwards have to be extracted from the
database Datastream.
5.1.1 Selection criteria
The study focus on UK firms acquiring domestic UK firms and cross border firms within the EU
and in the period from 2006 until today (2010). The first criterions provided 61.902 and 5.468
acquisitions of domestic and cross border firms, respectively. In order to narrow down the samples
sample size other selection criteria’s were set up as well.
5.1.2 Deal status, type and final stake
The second criterion set is that only M&A that have been completed and where the company have
acquired a final stake of 100 % of the other company is included. These criteria’s are just too
narrow down the number of M&A to 9.073 domestic and 720 cross border acquisitions.
5.1.3 Banking, Insurance and Financial Services Companies
The third criterion set is that only acquisition with the Banking, Insurance and Financial Service
sector is included. These criteria’s are just too narrow down the number of acquisitions to 2.285
domestic and 175 cross border acquisitions.
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5.1.4 Deal value
To further narrow down the samples in regards to the domestic acquisitions only the top 300 ranked
deals in value terms are selected. This should also have a positive effect on the risk of thin trading.
This leaves 300 domestic deals and still 175 cross border deals.
5.1.5 Datastream
To make the companies easier to find in datastream the ISIN numbers were extracted from Zephyr
and the announcement dates and rumour dates were extracted as well. The reason for extracting the
data with respect to the announcement date and not the completion date is due to the underlying
assumption of efficient markets that assumes that the information is reflected in the stock prices
immediately after the announcement.
Firms that have different rumour and announcement dates are excluded from the data because the
potential shift in prices as an effect of the announcement, in accordance to the efficient market
hypothesis already will have happened at the rumour date since the hypothesis states that any
information will be absorbed in the prices immediately after it reaches the public. So a rumour date
before the announcement date would create bias in the estimation of abnormal return since the
potential shift then will lie in the estimation period instead of on the event day and this will dilute
any possible significant effect from the event.
After correcting for missing information, delisting and firms with more than one acquisition in the
time period and differences in rumour and announcement dates the two samples totals 123 domestic
deals and 70 cross border deals. Accordingly to Bartholdy et. al. (2007), with sample sizes close to
and above 50 events the performance of the test statistics is good, since it provides enough size and
power.
5.2 Thin trading
Thin, medium and thick trading are measures of how frequently a specific stock is traded. Thin
trading is defined as stocks that are traded on less than 40% of all trading days or on average less
than two days per week. Medium traded stocks are traded between 40% and 80% of the trading
days and thick traded stocks are traded on more than 80% of the trading days23
. Thinly traded stocks
can create problems in respect to making reliable analysis on daily data and if the problem is
extensive it can be recommended to use weekly or monthly data. Using daily data with thin trading
can create biases in the regression used to estimate the expected return and I therefore test for thin
trading in my data using the volume as an indicator of when the stock has been traded and when
not.
23
Bartholdy et.al. Conducting Event studies on a small stock exchange (2007) p.7
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The data set has been corrected for non-trading days and therefore on average consists of 200
trading days. All 48 thinly traded companies have been excluded, respectively 31 acquisition of a
domestic firms and 17 acquisitions of cross border firms. The dataset now consists of 92 domestic
acquisitions and 53 cross border acquisitions24
.
5.3 Data descriptive
As mentioned in the data collection section the analysis contain stock return data for 145 UK
companies over 203 days including both the estimation period and the event window which
provides 29.435 observations that are used in the empirical testing.
The stock and market returns over the estimation period for the portfolio of stocks are shown in the
figure below.
Figure 2 - Spread
Over the 200 trading days in the estimation period included in the analysis the average market
return and stock return are 6,81% and 10,16%, respectively, which equals a spread in the estimation
period of 3,35%. The spread is equally explained by the return in the UK firms acquiring domestic
UK firms and cross firms within the EU with an average return of 9,51% and 11,30%, respectively.
The lowest average spread between the market return and an individual stock return is -140,15%
and the highest spread being 81,15%. To test for significance in the event period, a statistical
analysis, which is earlier described, will be conducted in the following section.
24
Figure 8 and 9 in the appendix
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6. Empirical evidence
In this section the hypotheses will be tested and the empirical analysis of the battery of tests
presented. The tests are performed following the methodology stated in section 4 and the results
will be interpreted and compared to the earlier empirical evidence described in section 2.
The results from the empirical analysis for the entire portfolio, the portfolio of domestic acquisition
and the portfolio of cross border acquisition are presented in table 1, 2 and 3 respectively. We test
the following hypotheses of abnormal return
H0: Ait = 0 No significant abnormal return
H1: Ait ≠ 0 Significant abnormal return
Where the alternative hypothesis; H1 covers both the scenario of positive abnormal return and
negative abnormal return. Because the event study method assumes normally distributed security
returns the rank test (T4) and the sign test (T5) are also included25
.
6.1 Test result
Figure 3 – Acquisitions portfolio
Looking at the results of the entire portfolio in table 1 it can be concluded on the basis of the T1, T3
and the T5 Sign test that the average abnormal return to the acquiring shareholders over the entire
event period is significantly different from zero at a 5% significance level equal to 1,96. Especially
on the announcement day (day 0), the results are very strong and indicating a significant abnormal
return in all tests. The T4 Rank test where the t-statistic are negative pointing towards negative
abnormal return - This point towards problems with the efficient market hypothesis stating that the
information will be incorporated in the prices at the same day as the information reaches the public
or it tells us that information has reached some traders the day before the announcement and in
other cases the information might first have reached the shareholders after the closing of the
markets. T5 Sign test being positive indicating a positive abnormal return.
Figure 4 - Domestic
25
Kiymaz & Baker, Short-term Performance, Industry and Effects, and Motives (2008)
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The results from the tests conducted only on the portfolio of UK acquiring domestic UK firms point
towards higher abnormal returns than for UK acquiring cross border firms within the EU and for the
entire portfolio all together. The fact that the non‐parametric tests show different results than the
parametric tests could suggest that the assumption of normality might be violated. Only on the event
day are all the tests significantly different from zero but it is not enough to conclude that the
abnormal return in the event window is significant.
Figure 5 – Cross border
In the analysis of the portfolio of UK firms acquiring cross border firms within the EU the average
abnormal return over the event window is 1,0488% and the result is not significant for any of the
statistic tests and the H0 hypothesis of zero abnormal return can therefore not be rejected at a 5%
significance level and it can thus not be concluded that the acquiring shareholders experience
wealth creating return in regards to the acquiring announcement. The reason that nothing is tested
significant could however be due to abnormal returns too small for the test to detect as Batholdy
et.al suggests that the abnormal return needs to be above 2% for each day in the event window to
reject the null hypothesis, which might be why there is no significant evidence found here26
.
6.1.1 Cross sectional regression
A cross sectional regression has been conducted to test for if it can be significantly proven that there
is a difference in the abnormal return between the acquisition of domestic and cross border firms27
.
The results generated show that the beta value of the dummy (domestic) is 0.0064 which could
point towards greater abnormal return to the shareholders of domestic firms. The R2
is 0,000 which
means that the variable do not explain any of the variations in the CAR variable. The ANOVA
model shows a Sig. value of 0,939, which equals a H0 choice and therefore a rejection of H1
meaning that the difference is not significant at a 5 % significance level. Therefore it is not possible
to conclude anything from the model.
26
Batholdy et.al. Conducting Event studies on a small stock exchange (2007) p.15
27
Please see Figure 10 in the appendix
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6.2 Comparison to existing empirical studies
The findings of the empirical tests of this section are here compared to the empirical findings stated
under section 2.2 by earlier conducted studies on the subject.
As opposed to a lot of the earlier empirical findings this paper shows significant abnormal returns
for the shareholders of the acquiring firm of around 1.1499% when looking at the overall portfolio.
This goes against the findings of Jensen and Ruback who found that the shareholders of acquiring
firms experience returns close to zero. It however fits better to the findings of Roades who found
significant positive results to acquiring shareholders in three of his studies and Moeller et.al. who
found average abnormal returns to the acquiring firms of 1.1% which is close to the findings of this
paper for the overall portfolio.
When looking only at the portfolio of UK firms acquiring cross border firms within the EU nothing
significant can be said about the returns to the acquiring shareholders which is more in line with the
earlier empirical evidence. This can maybe be explained by the motive theories listed earlier in the
paper if for example the market interprets the bidding price as being too high, perhaps as a result of
managers’ over‐optimism or agency reasons, a negative return would be expectable. According to
behavioural theory takeovers are often motivated by the self-interest of the management of the
acquiring firm. Furthermore the behavioural theories argues that the return to the acquiring
shareholders normally is around zero and insignificant, indicating that the acquiring managers do
not create value for their shareholders when they engage in takeover activities. The empirical
findings from this study has proven that the management are acting rational and maximizing
shareholder wealth and thereby supportive of the neoclassical theory.
7. Conclusion
The paper deals with the subject of M&A’s and more specifically on whether UK firms acquisitions
of domestic UK firms or cross border firms within the EU in the period from 2006 until today
(2010) have been wealth creating or wealth reducing events for the acquiring shareholders and if
there was a difference in the abnormal return in acquisitions of domestic or cross border firms. The
theory listed states that M&A’s can be seen either as sound strategic decisions made by rational
managers or as a result of behavioral mistakes by managers as agency problems or hubris. Using the
event study methodology with data extracted from datastream the hypotheses was tested using both
parametric and non‐parametric tests as well as a cross sectional regression to detect differences in
return across the two portfolios. The empirical evidence shows a significant average abnormal
return over the window of 1,1499% for the entire portfolio of 145 firms. The fact that there are
found evidence of overall returns could explain motives for why companies keep engaging in M&A
Page 16 of 25

activities despite unsure empirical evidence for the return of acquiring shareholders, but the findings
of abnormal returns in this paper can be uncertain due to a violations of assumptions.
As outlined in the hypothesis one would expect abnormal positive returns if the market interpreted
the M&A decision as a result of synergies to be exploited thereby implying a higher combined
value than the sum of the two participating companies. The empirical evidence in this paper
supports this motive of acquisitions and the neoclassical theories. The management can be
concluded to have been operating rational and have made rational choices in favour of the
shareholders due to the acquisitions having increased shareholder wealth.
Conducting event studies often experienced problems with its finding in regards to the significant
estimates in the returns to the acquiring shareholders. This paper has been able to find significant
estimates in the entire portfolio and domestic acquisitions especially on the announcement day (day
0), making it possible to conclude on the results with a 95 % probability.
Page 17 of 25

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Appendix
Figure 6 – Selected companies domestic - 300 deals (UK firms acquiring domestic UK firms)
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Page 21 of 25

Figure 7 - Selected companies cross border -175 deals (UK firms acquiring cross border firms
within the EU)
Page 22 of 25

Page 23 of 25

Figure 8 – Volume of stocks on UK firms acquiring domestic UK firms
Figure 9 - Volume of stocks on UK firms acquiring cross border firms within the EU
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Figure 10 – Cross sectional regression analysis
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Event study on stock returns from UK acquisitions

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