402046
TRANSCRIPT
Department of Business Finance Author:
ACF project 402046
Finance & Intl. Business Group members:
283888
410189
283900
283894
Do European acquisitions create shareholder wealth?
An event-study of European companies from 2000-2011
Aarhus School of Business and Social Sciences
May 2011
Page 2 of 19
1. Introduction .................................................................................................................................... 3
1.1. Problem statement ..................................................................................................................... 4
1.2 Motivation for the study ............................................................................................................. 4
1.3 Executive summary .................................................................................................................... 5
2. Literature review ............................................................................................................................ 5
2.1 Review of the relevant theory .................................................................................................... 5
2.2 Review of relevant empirical evidence ...................................................................................... 6
3. Hypothesis ....................................................................................................................................... 7
4. Methodology ................................................................................................................................... 8
5. Data ............................................................................................................................................... 10
5.1 Data selection in Zephyr .......................................................................................................... 10
5.2 Datastream ............................................................................................................................... 11
5.3 Descriptive statistics ................................................................................................................ 12
6. Empirical evidence ....................................................................................................................... 14
6.1 Test and results ......................................................................................................................... 14
6.2 Regression ................................................................................................................................ 15
7. Conclusion ..................................................................................................................................... 17
8. Bibliography ................................................................................................................................. 18
9. Appendix ....................................................................................................................................... 20
Page 3 of 19
1. Introduction The purpose of this paper is to study the impact on shareholder wealth of European acquisitions.
Several M&A papers have stressed the fact that M&As happen in waves and within these waves, in
clusters by industry (Andrade, Mitchell, & Stafford, 2001; Goergen & Renneboog, 2004). Since the
late 19th century, the incentives for commencing an acquisition have been several, such as:
• gaining market power, while the market concentration ratio increases
• taking advantage of opportunities for diversification
• obtaining efficiency-related incentives that often could result in economies of scale
(Andrade, Mitchell, & Stafford, 2001), and
• focusing on obtaining a competitive advantage
So, the overall incentives to acquire a target may be the anticipation of certain synergy effects,
economic benefits and maintain competitiveness.
As stated by (Martynova & Renneboog, 2006) European firms have participated noticeably in the
M&A activity, at a level worthy of its US and UK counterparts. Martynova and Renneboog further
argue, that the explanations for this increasing activity may be the introduction of the Euro, the
globalization process, technological innovation, deregulation and privatization, along with the
financial markets’ boom encouraging European companies to be a part of the M&As during the
1990s. Deregulation is by many believed to be the main driver of the 1990s waves (Andrade et al.,
2001).
Lastly, the existing empirical research, regarding wealth for the acquirer and target shareholders, is
mainly based on US data. Therefore, the aim of this paper is to investigate the impact on
shareholder wealth when dealing with European acquisitions from year 2000 until primo 2011.
Page 4 of 19
1.1. Problem Statement
In relation to the above-mentioned introduction, the aim of this paper is to test whether an
acquisition, in general, generates an abnormal return and thereby more wealth to the shareholders.
The quantitative event study approach is used to investigate this further. Moreover, the paper will
investigate the effects of the two different acquisition strategies, being domestic and cross-border
acquisitions, in and between European countries during the time period 2000-2011.
Specifically, the aim is to investigate whether the acquisition will create a significant change in
wealth for both the acquiring and target company’s shareholders on the day of the announcement.
Based on this framework and existing research the following research-question has been conducted:
• Will the announcement of an acquisition create additional wealth for the involved companies, on a short-term basis?
This leads to the following sub-questions:
• Will there be significant differences between the abnormal return of domestic acquisitions
as opposed to cross-border acquisitions?
• Will there be significant differences of the abnormal return from the perspective of the acquirer compared to the target?
1.2 Motivation for the Study The empirical research on acquisitions in Europe, is limited compared to its US and UK
counterparts. As the M&A activity has increased in the recent decades, it seems important to
investigate this increasing activity further. Moreover, it is interesting to investigate whether there is
consistency between some fundamental financial theories and how the real world, i.e. the European
financial markets, reacts to new information.
Considering the situation for US based company DuPont’s shareholders, during the company’s
acquisition a majority share of the Danisco company, it is interesting to further analyze whether it is
beneficial to be a target shareholder and less beneficial to be an acquirer shareholder ("DuPont’s
Danisco Deal Not a Threat to Novozymes, Analysts Say" ).
Page 5 of 19
1.3 Executive Summary The paper contains an event study investigating whether there is an abnormal return for the
acquiring company and or target company on the announcement day of the acquisition. The
following hypothesis has been put forward for the acquirer shareholders:
Hypothesis 1: the event has no impact on the abnormal return.
Additionally, this hypothesis is divided into two different acquisition strategies, resulting in the
following:
Hypothesis 2: the event has no impact on the abnormal return for the cross-border acquiring firm’s
shareholders.
Hypothesis 3: the event has no impact on the abnormal return for the domestic acquiring firm’s
shareholders.
Lastly, the target shareholder is considered by:
Hypothesis 4: the event has no impact on the abnormal return for the target shareholders.
To conclude the result of this study it was found, that it is significantly better to be a target
shareholder than being acquirer shareholder.
2. Literature Review In the following only the relevant theory and empirical findings regarding the event study on
acquisitions is considered.
2.1 Review of the Relevant Theory First, the efficient market hypothesis, EMH, published by E. F. Fama, builds on two key
assumptions of a market. 1) In an efficient market at any given time, the actual price of a share is a
reliable estimate, and 2) the market will react instantly on new information (Fama, 1965). Hence,
investors should not be able to earn above the normal return in the market since all information
should always be imbedded in the share price, instantly after announcement. Therefore, it is not
Page 6 of 19
possible to earn an abnormal profit from information already known by the market (Fama,
1970)(von Gersdorff & Bacon, 2009).
A more profound understanding of efficient market hypothesis is beyond the scope of this paper.
However, the narrow inclusion of the efficient markets’ theory is relevant to gain an understanding,
or at least, a theoretical understanding of how financial markets may act.
In general, the empirical research on M&As has revealed trends and characteristics trying to explain
the motives of these activities and as numerous event studies have found, it effects the shareholder
wealth. Additionally, it might also be crucial to stress the fact, that prices may adjust to firm-
specific information, which an acquisition in fact is (Fama, 1991).
Some incentives for the M&A activities are to some extent clarified in the introduction.
Additionally an empirical finding claim that M&As happen in waves and within these waves
M&As cluster by industry (Andrade et al., 2001).
The relevant empirical literature draws a picture of what characterizes each wave, while defining
the main motive driving the M&A activity. The M&As waves have both been driven by economic,
regulatory, and recently more technological shocks drive industry merger waves (Harford, 2005).
2.2 Review of Relevant Empirical Evidence Much of the existing literature is based on US data, which is an argument to investigate why it is
interesting to test European data.
As mentioned in the introduction, the significant changes within the European Union have
stimulated a restructuring process for European companies. Moreover, the higher activity level in
1998-2000 was found by (Campa, J., M., & Hernando, 2004) mainly, to be caused by domestic
factors.
Campa and Hernando investigated the value creation from the announcement of M&As for acquirer
and target shareholders. They found that the target shareholders receive, on average, a positive and
significant cumulative abnormal return from the announcement. On the contrary, the abnormal
return of the acquiring firms’ shareholders is not significantly different from zero, which is
consistent with the findings of (Bae & Park, 1994). Additionally, in a recent US study by (Moeller,
Sschlingemann, & Stulz, 2005) it was actually found, that acquirer shareholders lost a substantial
amount per dollar spent on acquisition in the period 1998-2001.
Page 7 of 19
The findings of Campa and Hernando are somewhat consistent with (Goergen & Renneboog, 2004
and (Martynova & Renneboog, 2006). However, in both papers the effects of announcement are
found to be statistically significant for both the target and the acquirer shareholders. It should be
noted that the acquirer shareholder’s return is quite modest.
Furthermore, Georgen & Renneboog distinguish between hostile and friendly takeovers, where the
first shows a negative effect for the acquiring firm’s shareholders and a higher effect of target
shareholders. Additionally, a final finding of the paper is that domestic acquisitions generate higher
wealth effects, than cross-border acquisitions, which is supported by (Kang, 1993). This, however,
is inconsistent with the findings of (Lowinski, Schiereck, & Thomas, 2004) who find no significant
difference in wealth between the two acquisition strategies.
To sum up, the evidence presented is obviously quite contradicting. As (MacKinlay, 1997) states,
the general picture is that, the abnormal returns of the target are positive, whereas the acquirer are
close to zero.
3. Hypothesis The hypothesis finds its inspiration from the stated research questions from section 1.1. The goal of
the stated hypotheses is to investigate the acquirer versus the target shareholder wealth. Further, it
is interesting to examine whether one of the two acquisition strategies is significantly beneficial
compared to the other.
Based on the existing literature, there is an anticipation of no abnormal return for the acquiring
company (MacKinlay, 1997)(Goergen & Renneboog, 2004), hence the null hypothesis:
Hypothesis 1: the event has no impact on the abnormal return.
It is interesting to investigate whether the two different acquisitions strategies generate any
significant abnormal return (Lowinski et al., 2004) (Kang, 1993). Therefore, the following
hypothesis is put forward for cross-border and domestic acquisitions respectively:
Page 8 of 19
Hypothesis 2: the event has no impact on the abnormal return for the cross-border acquiring
firm’s shareholders.
Hypothesis 3: the event has no impact on the abnormal return for the domestic acquiring firm’s
shareholders.
And finally, the hypothesis for the target shareholders is put forward. This is regardless of the
acquisition strategy, but motivated to a strong degree by (Campa, J., M., & Hernando, 2004)
(Martynova & Renneboog, 2006):
Hypothesis 4: the event has no impact on the abnormal return for the target shareholders.
4. Methodology In order to test the aforementioned hypothesis, an event study approach is used. The following
description of the applied methodology is inspired by (MacKinlay, 1997). As mentioned in section
2, the usefulness of such a quantitative study comes from the fact, that given rationality in the
market, the effects of an event will be reflected instantly in the share price and the idea is to capture
this possible change.
First, we define the event of interest to be acquisitions within the European Union and the data
collected transpires from year 2000 until primo march 2011. Each acquisition announcement has an
estimation period of 200 (trading days) before the event, and an event window of three days. The
day prior to the event, the event day, and the post event is noted as t-1, t0 and t+1 respectively. The
day prior is included as the market may acquire information regarding the announcement
beforehand. The day post the event is included since it is then possible to capture the change in the
share prices.
By making the event window as small as possible we may eliminate most variance, but on the other
hand we may not be able to measure the effect completely. It is always a balance between the two.
The selection of a relatively short event window is consistent with the EMH, thereby trying to
capture the instant response to new information.
Page 9 of 19
The time line for the event study is illustrated in the figure below:
Figure 4.1: Time line
Source: interpretation 9/4/2011 The impact of the event requires a measure of the impact on abnormal profit. The calculation of this
is beyond the scope of this paper, but it defined, in short, as the surplus of the normal return in the
chosen event window, which is presented in Appendix D on the CD. The approach to determine the
normal performance is in full alignment with the MacKinlay paper’s suggestion of applying the
market model. In our study we have used the S&P Euro index, which will be elaborated on in the
data section.
In order to test for abnormal performance on event days we make use of both parametric tests and
non-parametric tests. The parametric tests are restricted by several assumptions, whereas the non-
parametric test is not restricted by such assumptions. Both types of tests are included to ensure a
degree of robustness of the conclusions, as stated by (MacKinlay, 1997).
The selected tests are in alignment with (Bartholdy, Olson, & Peare, 2007) and lecture 3 in ACF
class.
Table 4.1: statistical tests
Parametric tests
T1 – Cross-sectional dependence
T2 – Cross-sectional independence
T3 – Standardized abnormal return
T4 – Adjusted standardized abnormal return
Page 10 of 19
T5 – Rank test
T6 – Sign test
For further details about all the test statistics look in Appendix C and D on the CD.
After conducting the tests it is beneficial to present the results and compare this to the relevant
literature and existing empirical findings. This will hopefully lead to some insight in understanding
the effects of M&As. Finally, a regression analysis is presented to shed some additional light on the
explanation of CAR.
5. Data An overview of the data process is presented below:
Figure 5.1 data process
5.1 Data Selection in Zephyr In order to increase the validity of the results presented in the paper, the following describes how
the final sample was constructed in detail. The initial selection criteria are presented in Appendix 4.
The initial screening resulted in 70,030 deals, which obviously should be decreased even further.
Therefore the screening process was subject to change by implementing additional selection
criteria. Our second screening added that the acquirer should be quoted. Furthermore, the acquirer
and target assets should amount to a minimum sum of € 100m and the percentage of stake acquired
should amount to minimum 75% of the target company’s shares.
Zephyr
DataStream SAS
Excel
Page 11 of 19
Table 5.1 Zephyr search criteria.
Deal type Acquisition
World Regions Acquiror European Union (27)
Target European Union (27)
Time period 2001 – Until current date
Quoted companies Quoted acquiror
Acquiror financials (million EUR( a. Total assets, min = 100
Percentage of Stake Acquired Stake Min = 75
Current deal status Completed
Target financials (million EUR) a. Total assets, min = 100
After this process acquirers and targets with no ISIN numbers were removed as well as inter-firm
deals. Accordingly, the sample size dropped from 956 to 70. Moreover we were alleged to include
data from the fiscal year 2011, but it was not possible to retrieve any deals, which satisfied our
selection criteria.
It is important to address some of the above listed factors a bit further. Namely, the current deal
status, since it is crucial for the rumor and announcement date to be the same. This is due to the
fact, that if the market is aware of the new information, i.e. a month before, it will affect the share
prices before the actual announcement day. Thus, the three day event window is not able to capture
the effect completely.
Last, a noteworthy downside of Zephyr is the need to go through the output one-by-one, since it
does not fulfill the listed criteria. As mentioned, our screening resulted in data of 956, but some data
did not fulfill our requirements. For instance, we only assigned Zephyr to show data from 2001 and
onwards, but ended up with data from 2000 as well as US-Euro deals.
5.2 DataStream The key from transferring data from Zephyr to DataStream is the unique ISIN number, and in the
following the transformation process is described in more detail.
We have used the Standard & Poor’s Euro Index, S&P Euro, as we consider this index to be
representative for our EU27-chosen countries. This index is assumed to be similarly applicable as
Page 12 of 19
the Morgan Stanley Euro Index, MSEI, as it consists of 182 large European-traded stocks. By
relating the return of any given security to the return of the market portfolio, i.e. S&P Euro, we are
making use of the market model to measure the normal performance, as mentioned in section 4.
Some elements of the DataStream process are worth addressing even further. First, we have chosen
daily returns since it contributes to a precise and quick response of the price of a security. As stated,
this supports the second of the two key assumptions of the EMH (Fama, 1991). Furthermore, we
have used log return, as one can see the relative changes in the prices and compare it to series with
different base values. This ensures that the comparability between variables is reliable.1
Second, when considering the estimation period it is necessary to go approximately 365 days back,
so we are able to capture about 200 trading days (observations). Actually, we ended up with 204
observations since we needed 203 + 1, where the one extra is necessary for the return
transformation. The actual observation amounted to 203.
Furthermore, our dataset dropped from 70 to 67, since DataStream was unable to extract some
necessary data. The sample is however assumed to be large enough for further investigation even
though a number of stocks signaled signs of thin trading issues, which we assumed to be negligible.
So, the final acquirer sample of 67 is split up into2:
• Cross-border deals (26)
• Domestic deals (41)
And we only have return data from 16 target companies, which makes it a very small sample. This
results in four samples for which the four hypotheses have been fabricated. The four sample are
then implemented to SAS and Excel sheets for further analysis, which is illustrated in figure x.
5.3 Descriptive Statistics In the end our total sample consists of 67 acquisitions where the majority are domestic deals, which
is amplified in Appendix 1. Our sample consists of 45 deals with a full acquisition (67%) where the
lowest acquired deal sums up to approximately 75% (33%). However, in our test all deals
1 However, this proved not to be necessary, as we have used daily data. 2 It is assumed that all deals fulfill the criteria of being a 100% acquisition
Page 13 of 19
assumedly qualifies as full acquisitions. One must refer to Appendix 1 to see the distribution of
domestic versus cross-border deals. Furthermore, our target sample consists of 16 deals, since it was
only possible to obtain prices for this limited number of deals. Even though the target sample size is
too small to generalize, we included it to confirm what numerous empirical researches states.
It seems reasonable to assume that since we are applying daily data, returns are comparable and
normally distributed. Obviously the results of the CAR can both be positive and negative, which is
why we used a two-sided test. The tests are dealt with in Appendix D on the CD.
Considering the descriptive statistics of our target sample:
Table 5.2: descriptive statistics for target shareholders
Abnormal returnt=i SUM Mean Skewness Std. Deviation
-1 1,946 0,122 1,677 0,167
0 0,476 0,030 3,600 0,076
1 0,240 0,015 3,635 0,064
CARt=0 2,662 0,166 0,986 0,171 Source: own interpretation 4/5/2011
Table 1 illustrates that it, on average, is advantageous to be a target shareholder. Furthermore, the
positive skewness indicates a distribution with an asymmetric tail extending towards positive
values. This is also amplified in Appendix 1 in figure 3. Further test on the assumptions of the data
is beyond the scope of this paper, as we assume the data to be normally distributed and comparable.
Descriptive statistics for the other samples are presented in Appendix 1.
Page 14 of 19
6. Empirical Evidence In this section first the six parametric and non-parametric test results are presented followed by a
regression analysis.
6.1 Test and Results In general, the aim is to test whether the observed differs statistically from zero. In testing for this
we apply six test statistics, as mentioned in section 4. The test results are presented below:
Table 6.1 presentation of tests
CAR T1 T2 T3 T4 T5 T6
Acquirer(67) 0,704 -2,367* 1,983* 1,915 0,233 0,836 0,198
Cross-
border(26)3
0,158 -0,933 0,675 0,676 0,131 0,336 0,618
Domestic(41) 0,546 -2,240* 1,929 0,171 0,295 0,724 0,025
Target(16) 2,662 12,707* 15,351* 15,389* 3,332* 3,388* 2,032
Notes: The figures marked by * are statistically significant from zero. The significant figures have a p-value ≤0,05. Two-sided test since we are testing for both positive and negative returns. Source: own interpretation 4/5/2011 and based on Appendix D on CD.
Regarding the acquirer there is inconsistency in the results presented (T1-T2 differs from T3-T6).
When facing inconsistency between the parametric and the non-parametric it may indicate that the
assumptions of the parametric tests are not fulfilled. Therefore, it is favorable to rely on the non-
parametric test result, thus fail to reject the null hypothesis of no abnormal return for acquiring firm
shareholders. Additionally, it may be relevant to comment on the fact, that if we changed the level
of significance to 1% the conclusion of every test would be the same, namely fail to reject the null .
Accordingly the conclusion is uncertain due to this matter.
Considering the two different acquisition strategies, cross-border and domestic, it is a somewhat
uniform conclusion.
Moreover, when facing the result of the target shareholders it presents a different story. It seems
very advantageous to be a shareholder of a target firm as we reject the null hypothesis of no
abnormal return. This states that the abnormal return it statistically significant from zero, hence
there is an abnormal return for the target shareholders.
3 Both cross-border and target are subject to a t-distribution since the n<30.
Page 15 of 19
Our findings support some of the existing empirical work regarding no significant return to
acquiring firm shareholders, and are aligned with (Bae & Park, 1994; Campa, J., M., & Hernando,
2004) as covered in the literature review in section 2. The motives for commencing an acquisition
are somewhat obvious, but the reasons to acquirers ending as the losers are blurry. From a market
perspective, one reason may be, that the deal will never yield the company-anticipated synergy
effects.
However, it has been found by (Martynova & Renneboog, 2006) that acquiring firms using
domestic acquisition are more favorable compared to its cross-border counterpart. This is a
conclusion our test does not fully support, as none of the strategies yield an abnormal return,
significantly different from zero, which is supported by (Lowinski et al., 2004).
One incentive for the de-regulation, which has flourished across the European Union, may be to
remove the upside of following a cross-border strategy compared to doing domestic acquisitions.
Arguments as to why it is not lucrative to follow a cross-border strategy, might be due to the fact
that legal, economic and regulatory obstacles still matter heavily (Campa, J., M., & Hernando,
2004).
Finally, the findings of target shareholders do support the reviewed literature and further supports a
lot of the existing literature on target shareholder wealth regarding acquisitions (Goergen &
Renneboog, 2004; MacKinlay, 1997). One obvious reason for target shareholders to experience an
abnormal return during the announcement window is the fact that there is paid an excess price in
order to buy a given share. Moreover, the acquisition of a target may signal to the market, that the
target is a strong company with growth potential, which makes their shares attractive to buy.
6.2 Regression The purpose of including a regression is analyzing the relationship among the variables. The
regression analysis should be seen irrespective of the latter section. In order to be able to conclude
anything from the regression model, it is assumed that the underlying assumptions are fulfilled.
The estimated model is presented below:
CARt=-1;+1 = α – acquirer x β1 + cross-border x β2 + error term
Page 16 of 19
The regression is run in the statistical program, SAS, where the output is presented in Appendix 2.
The model is estimated from the CAR data on acquirer and target (=83) at time t-1;+1. Additionally,
both the acquirer and cross-border parameters are dummy variables. The linear relationship in the
data is illustrated in Appendix 2, however, this should be seen in connection with the adj. R2
described below.
We want to look at the relationship between shareholder wealth for our four samples and CAR.
Accordingly we want to predict CAR from acquirer and cross-border variables.
Table 6.2. Results of the regression analysis
Source: own interpretation 3/5/2011
The model with CARt-1;t+1 as dependent variable has one statistically significant variable and the
adj. R2 equals 28,87%. Interpretation of the model tells us that being an acquiring firm shareholder
we obtain a smaller return compared to its target counterpart that receives a higher return.
We see that the relationship between CAR and acquiror is negative (-0,158). This relationship must
be concluded to be statically significant. Thus, there is a statistically significant negative linear
relationship between CAR and acquirer. Turning to the target, which is found in the intercept
parameter we see a positive relationship which also is statistically significant. Hence, there is a
statistically significant positive linear relationship between CAR and target.
Looking at the relationship between CAR and the cross-border, we actually find a positive
relationship (0,013). However, this is not statistically significant (SAS interpretation of the REG
Procedure).
Variable Parameter estimates P-value
Intercept 0,163 0,01
Acquirer -0,158 0,01
Cross-border 0,013 0,55
Page 17 of 19
7. Conclusion An event study approach was used in order to test for acquisitions with the European Union from
the period 2000-2011. It was found, that acquisitions do not generate any abnormal return for the
shareholders of the acquiring firm regardless of being domestic or cross-border. However, it was
found, that it is indeed beneficial to be a target shareholder, although it was a small sample. The
sample consisted of 67 deals with four sub samples, each with 203 observations. It should be noted,
that the tests, both parametric and non-parametric, did not perform uniform results at the selected
significance level, except for the cross-border sample.
Furthermore, a regression has been put forward trying to explain the relationship between CAR and
acquirer (including cross-border and domestic) along with the target. It was found, that the acquirer
contributed a significantly negative CAR, whereas the target contributed a significantly positive
CAR.
Finally, our results are consistent with most empirical findings, and in that manner validate a range
of published findings regarding the European M&A topic.
Page 18 of 19
8. Bibliography
Andrade, G., Mitchell, M., & Stafford, E. (2001). New evidence and perspectives on mergers.
Journal of Economic Perspectives, 15(2), 103-120.
Bae, S., C., & Park, J., R. (1994). Acquisition of failing firms and stockholder returns. Journal of
Accounting, Auditing & Finance, 9(3), 511-529.
Bartholdy, J., Olson, D., & Peare, P. (2007). Conducting event studies on a small stock exchange.
European Journal of Finance, 13(3), 227-252.
Campa, J., M., & Hernando, I. (2004). Shareholder value creation in european M&As. European
Financial Management, 10(1), 47-81.
Fama, E., F. (1970). Efficient capital markets - review of theory and empirical work. Journal of
Finance, 25(2), 383-423.
Fama, E., F. (1991). Efficient capital-markets 2. Journal of Finance, 46(5), 1575-1617.
Goergen, M., & Renneboog, L. (2004). Shareholder wealth effects of european domestic and cross-
border takeover bids. European Financial Management, 10(1), 9-45.
Harford, J. (2005). What drives merger waves? Journal of Financial Economics, 77(3), 529-560.
Kang, J. (1993). The international market for corporate control : Mergers and acquisitions of U.S.
firms by japanese firms. Journal of Financial Economics, 34(3), 345-371.
Page 19 of 19
Lowinski, F., Schiereck, D., & Thomas, T. W. (2004). The effect of cross-border acquisitions on
shareholder wealth -- evidence from switzerland. Review of Quantitative Finance &
Accounting, 22(4), 315-330.
MacKinlay, A., C. (1997). Event studies in economics and finance. Journal of Economic Literature,
35(1), 13-39.
Martynova, M., & Renneboog, L. (2006). Mergers and acquisitions in europe.Working Paper No.
114/2006
Moeller, S., B., Sschlingemann, F., P., & Stulz, R. M. (2005). Wealth destruction on a massive
scale? A study of acquiring-firm returns in the recent merger wave. Journal of Finance, 60(2),
757-782.
von Gersdorff, N., & Bacon, F. (2009). U.S. mergers and acquisitions: A test of market efficiency.
Journal of Finance & Accountancy, 1, 1-8.
Internet sources:
http://www.bloomberg.com/news/2011-01-11/dupont-s-danisco-acquisition-not-a-threat-to-
novozymes-analysts-say.html
http://www.ats.ucla.edu/stat/sas/whatstat/whatstat.htm
Page 20 of 19
9. Appendix 1. Descriptive statistics diagrams
2. Regression analysis
3. List of companies used in the analysis including the event dates.
4. Search criteria used in Zephyr, Print-Screen
5. Documentation of literature search – Lars
Page 21 of 19
Appendix 1 – Descriptive statistics
Figure 1
Figure 2
The blue bar illustrates the total number of deals recorded in that specific period. Accordingly, the
two other bars reflect how much they each have contributed for that specific year.
Figure 3
The histogram illustrates the positive skewness within sample. This may emphasize that, on
average, it is advantageous to be a target shareholder.
39%
61%
Two different strategies contribution to the EU acquisition activity from 2001-11
Cross-‐border Domestic
0
2
4
6
8
10
12
14
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Domestic
CB
Acquirer
0%
10%
20%
30%
40%
50%
60%
-‐0,02 -‐ 0 0,01-‐0,2 0,21-‐0,3 0,31-‐0,4 0,41-‐0,55
Target return
Frequency
Page 22 of 19
Acquirer - 67
AR
Cross-border - 26
AR Sum Mean Skewne
ss Std. Dev.
-‐0,039 -‐0,001 0,007 0,034 0,234 0,009 2,335 0,029 -‐0,037 -‐0,001 0,603 0,016 CAR 0,158 0,006 1,623 0,047 Max 0,137 Min -‐0,063
Domestic - 41
AR
Sum Mean Skewness Std. Dev. 0,470 0,011 2,305 0,054 0,028 0,001 -‐0,303 0,038 0,048 0,001 0,393 0,020 CAR 0,546 0,013 1,677 0,075 Max 0,311 Min 0,128
As our sample is consistent with (Martynova & Renneboog, 2006) by a majority of the deals being
domestic, this also influences the sample greatly. When considering the mean of cross-border and
domestic there is an anticipation of a higher wealth in the cross-border acquisition strategy (Kang,
1993). However, this does not seem to support our study, even though this is basic statistics, as the
mean of DomesticCAR outweighs the mean of Cross-borderCAR. A downside of the mean is that it is
Sum Mean Skewness Std. Dev. 0,431 0,006 2,207 0,047 0,262 0,004 0,193 0,034 0,010 0,0001 0,479 0,018 CAR 0,703 0,011 1,798 0,065
Page 23 of 19
vulnerable to extremely high and low numbers, which could affect the mean greatly, since the two
sample sizes are relatively small and not the same size.
Page 24 of 19
Appendix 2 – Regression analysis
Figure 1
Figure 2 illustrating the CARs where the right-hand side is very much influenced by the abnormal
returns from the target sample.
-‐0,2
-‐0,1
0
0,1
0,2
0,3
0,4
0,5
0,6
0 20 40 60 80
CAR
CAR
Lineær (CAR)
Page 25 of 19
Appendix 3 – List of companies Acquiror name
Acquiror country code
Target name Target country code
Date announced Target ISIN Acquiror ISIN
Wiener Städtische Allgemeine Versicherungs AG
AT Zastrakhovatelno Aktsionerno Druzhestvo Bulstrad Viena Inshurans Grup AD
BG 23-12-2008 BG1100015046 AT0000908504
Fortis NV BE ASR Verzekeringsgroep NV
NL 9-10-2000 NL0000301380 BE0003801181
Financiere d'Obourg SA/NV
BE Financiere de Tubize SA
BE 23-03-2005 BE0003768828 BE0003823409
ABB Ltd CH Groupe Entrelec FR 9-04-2001 FR0000035776 CH0012221716 Bilfinger Berger AG DE Rheinhold & Mahla
AG DE 6-06-2002 DE0007016701 DE0005909006
Bilfinger Berger AG DE Abigroup Ltd AU 23-10-2003 AU000000ABG8 DE0005909006 Continental AG DE Phoenix AG DE 29-03-2004 DE0006031008 DE0005439004 Siemens AG DE Broadcastle plc GB 26-07-2005 GB0000042407 DE0007236101 Albis Leasing AG DE Autobank AG AT 15-12-2005 AT0000A0K1J1 DE0006569403 Stada Arzneimittel AG
DE Hemofarm Koncern AD
RS 14-07-2006 CSHMFRE75032 DE0007251803
Siemens AG DE Aktiengesellschaft Kühnle Kopp & Kausch
DE 20-07-2006 DE0005027700 DE0007236101
Nordvestbank A/S DK Vestjysk Bank A/S DK 28-10-2002 DK0010304500 DK0010304500 Vestas Wind Systems A/S
DK Neg Micon A/S DK 12-12-2003 DK0010253681 DK0010268606
Himmerlandsgade 74, Aars A/S
DK Sparekassen Himmerland A/S (old)
DK 10-10-2006 DK0060050045 DK0060050045
Vestjysk Bank A/S DK Ringkjøbing Bank A/S
DK 29-09-2008 DK0010300193 DK0010304500
Max Bank A/S DK Skælskør Bank DK 27-05-2010 DK0010309491 DK0010305903 Acesa Infraestructuras SA
ES Áurea Concesiones de Infrastructuras SA
ES 20-05-2002 ES0111847036 ES0111845014
Grupo Inmocaral SA ES Inmobiliaria Colonial SA (old)
ES 7-06-2006 ES0153440419 ES0139140018
Construcciones Reyal SA
ES Inmobiliaria Urbis SA ES 28-07-2006 ES0154800215 ES0122761010
Metso Oyj FI Svedala Industri AB SE 21-06-2000 SE0000108169 FI0009007835 Elisa Oyj FI Soon
Communications Oyj FI 21-03-2001 FI0009006787 FI0009007884
Tecnomen Holding Oyj
FI Tecnomen Oyj FI 5-04-2001 FI0009009146 FI0009010227
Sponda Oyj FI Castrum Oy FI 31-12-2002 FI0009002273 FI0009006829
Metso Oyj FI Tamfelt Oyj Abp FI 5-11-2009 FI0009000939 FI0009007835
Faurecia SA FR Sai Automotive AG DE 25-10-2000 DE0005009005 FR0000121147
Lafarge SA FR Blue Circle Industries plc
GB 8-01-2001 GB0003863023 FR0000120537
Société Générale FR SKB Banka dd SI 20-01-2001 SI0021103013 FR0000130809
Schneider Electric SA
FR Legrand SA (old) FR 7-06-2001 FR0000120610 FR0000121972
Technip SA FR Isis FR 26-07-2001 FR0000120008 FR0000131708
Lafarge SA FR Cementia Holding AG
CH 15-05-2002 CH0001578472 FR0000120537
Compagnie des Alpes SA
FR Grévin et Compagnie SA
FR 23-05-2002 FR0004251098 FR0000053324
Brime Technologies SA
FR Assystem SA FR 9-09-2003 FR0000053589 FR0000074148
Icade SA FR Société Foncière des Pimonts SA
FR 13-10-2004 FR0000073686 FR0000035081
Sagem SA FR Societe Nationale d'Etude et de Construction de Moteurs d'Aviation SA
FR 29-10-2004 FR0005328747 FR0000073272
Vinci SA FR Sogeparc SA FR 12-12-2001 FR0000035958 FR0000125486
Page 26 of 19
Société de la Tour Eiffel SA
FR Locafimo SAS FR 25-11-2005 FR0000037988 FR0000036816
Taylor Woodrow plc GB Bryant Group plc GB 22-01-2001 GB0001494086 GB0008782301
Hilton Group plc GB Scandic Hotels AB SE 23-04-2001 SE0000351157 GB00B0ZSH635
Balfour Beatty plc GB ABB Ltd's rail electrification business
CH 21-12-2001 CH0012221716 GB0000961622
Davis Service Group plc, The
GB Sophus Berendsen A/S
DK 22-03-2002 DK0010238534 GB00B0F99717
Hammerson plc GB Grantchester Holdings plc
GB 9-09-2002 GB0031461832 GB0004065016
Tesco plc GB T&S Stores plc GB 30-10-2002 GB0008699778 GB0008847096
ISIS Asset Management plc
GB Foreign & Colonial Investment Trust plc
GB 2-07-2004 GB0003466074 GB0004658141
Grainger Trust plc GB City North Group plc GB 22-03-2005 GB0002827672 GB00B04V1276
AstraZeneca plc GB Cambridge Antibody Technology Group
GB 15-05-2006 GB0001662252 GB0009895292
Balfour Beatty plc GB Birse Group plc GB 26-06-2006 GB0001005684 GB0000961622
Warner Estate Holdings plc
GB JS Real Estate plc GB 26-01-2007 GB0008178138 GB0009406561
ShakespeareCo plc GB MyTravel Group plc GB 12-02-2007 GB00B06BLB41 GB00B1VYCH82
Coppereagle plc GB First Choice Holidays plc
GB 19-03-2007 GB0006648827 GB00B1Z7RQ77
DS Smith plc GB Otor SA FR 7-07-2010 FR0000064438 GB0008220112
Hellenic Petroleum SA
GR Petrola Hellas SA GR 30-05-2003 GRS416373009 GRS298343005
Sidenor SA GR Corinth Pipeworks SA
GR 14-04-2009 GRS300103009 GRS283003002
Orszagos Takarekpenztar es Kereskedelmi Bank Rt
HU Investicna a Rozvojova Banka as
SK 12-03-2001 SK1110001452 HU0000061726
Orszagos Takarekpenztar es Kereskedelmi Bank Rt
HU OTP Banka Srbija AD
RS 10-10-2007 RSKULBE40207 HU0000061726
CRH plc IE Gétaz Romang Holding SA
CH 5-03-2007 CH0015418087 IE0001827041
Eni SpA IT Lasmo plc GB 21-12-2000 GB0005316301 IT0003132476
Risanamento SpA IT Bonaparte SpA IT 19-07-2002 IT0003184188 IT0001402269
Banche Popolari Unite SCRL
IT Banca Lombarda e Piemontese SpA
IT 14-11-2006 IT0000062197 IT0003487029
Snam Rete Gas SpA IT Italgas - Societa Italiana per il Gas SpA
IT 12-02-2009 IT0003049217 IT0003153415
Koninklijke Vopak NV NL Ellis & Everard plc GB 10-11-2000 GB0003115424 NL0009432491
Koninklijke BAM NBM NV
NL HBG Hollandsche Beton Groep NV
NL 11-06-2002 NL0000359024 NL0000337319
Asseco Poland SA PL Prokom Software SA PL 29-09-2007 PLPROKM00013 PLSOFTB00016
Gorno-Metallurgicheskaya Kompaniya Norilskii Nikel OAO
RU Talvivaaran Kaivososakeyhtiö Oy
FI 20-11-2006 FI0009014716 RU0007288411
Invik & Co AB SE Industriförvaltnings AB Kinnevik
SE 16-02-2004 SE0000104416 SE0000164626
TeliaSonera AB SE Vollvik Gruppen AS NO 6-07-2005 NO0010058696 SE0000667925
Haldex AB SE Concentric plc GB 22-02-2008 GB0002153095 SE0000105199
Wise Group AB SE Dagon AB SE 23-02-2007 SE0000646606 SE0000646606
Fastighets AB Balder SE Din Bostad Sverige AB
SE 26-06-2009 SE0000614695 SE0000455057
Svenska Handelsbanken AB
SE Midtbank A/S DK 11-04-2001 DK0010001528 SE0000193120
Svenska Handelsbanken AB
SE Lokalbanken i Nordsjælland A/S
DK 15-09-2008 DK0010312446 SE0000193120
* Intially we started out with a sample of 70, but ended up with 67 after extracting return data
Page 27 of 19
Appendix 4 – Print-screen of search criteria
Initial search:
The deal type focus on acquisitions and target, the geographical area of interest is subject to the
Europeans union with data from transpiring from primo 2000 until end of first quarter of 2011. The
acquired stake in the company should be more than half in order to gain some kind of control and
lastly, the deal should be completed:
Final search:
Page 28 of 19
Appendix 5 – Literature search
I have used some of the relevant academic papers from the ACF course to start my literature search.
Thereby, I have located possible sources in the reference section of the academic papers. It quickly
came to my attention the specific authors and search words, were cited and noted in almost every
paper, so I concluded to take that approach. Primarily, I’ve used the Business Source Complete
database, BSP, to search for material.
Key search words include: event study, acquisition, European Union, abnormal return, Fama,
domestic and cross-border takeover bids, merger waves.
My initial search started in an author-based database, where it was relatively easy to note related
headlines where after it was possible to read the abstract.
Moreover, I used the BSP database where it quickly came to my attention, that it was not
satisfactory to use one single search word, but one must specify the search to be able to grasp the
amount of data presented:
Page 29 of 19
Lastly, in the search for useful literature, as mentioned, I investigated several references from
papers concerning the topic, and thereby got an idea of what was relevant. This approach is
illustrated by locating “Fama, E. F.” in numerous papers and searching in an author-based database: