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

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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

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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.

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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" ).

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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

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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.

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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:

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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.

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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

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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

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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

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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

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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.

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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.

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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

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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

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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.

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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.

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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

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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

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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  

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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: