European mega deals during the sixth merger wave. Is the legal origin of the bidder and the target a determinant of short-term investor reaction?

Author

Monica Martinez-Blasco

Francesc Martori

Xavier Auguets-Pratsobrerroca

Abstract

In the context of the mega merger and acquisition announcements during the sixth merger wave in Continental Europe, this paper presents an analysis of the influence of the bidder and target legal origins in the short-term reactions of the cumulative abnormal returns, the cumulative absolute abnormal returns and the volume traded. 92 bids occurred between 2003 and 2007 have studied. Our main result is a short term negative abnormal return for the bidder stockholders’ firms as a consequence of the announcement, which can be mainly associated to the presence of companies whose legal origin is German. This reaction is also accompanied with a significant effect above the average level in the market volatility and the volume traded. Finally, there does not seem to be any significant different reaction depending on whether operations happen between companies from the same legal origin or from a different one.

Keywords

  • M&As
  • Mega deals
  • Continental Europe
  • Announcement effects
  • Legal origin

1.        Introduction

Merger activity comes in waves, and European merger and acquisitions (M&A) activity has been increasing in importance over time. The fifth merger wave (1993– 2000) showed that the European and US M&A activity could be equiparated. This increase in European takeover activity during the fifth merger wave resulted in increased research on European characteristics of such corporate transactions, given that, until then, empirical research on M&A activity was mostly focused on the US market. European legal origin differences among countries, and consequently, their distinct governance systems is also a valuable field of research on European corporate events. The Internet Dot Com Bubble burst and the 9/11 terrorist attacks caused an economic recession, and the consequent end of the fifth wave. The takeover market did not recover until 2003, which is considered the beginning of the sixth merger wave. This new wave ended abruptly in late 2007 due to the Financial Crisis of 2007–2008.

 

While shareholders’ short-term wealth effects of European bids during the fifth European merger wave have been studied by several authors (Campa and Hernando, 2004; Goergen and Renneboog, 2004; Campa and Hernando, 2006; Faccio et al., 2006, Martynova and Renneboog, 2006; Martynova and Renneboog, 2011), the sixth merger wave has gone largely unnoticed in academia. To the best of our knowledge, only Campa and Hernando (2006) partially researched it by analysing a timeframe starting from 1998 and ending in 2006. However, they focused their study on financial firms in Germany, the UK, France, and Italy. It left the effects of mega deal announcements unexplored, while Goergen and Renneboog (2004) cut off their sample at US$ 100 million. We, on the other hand, propose an even higher cut off by analysing deals worth US$ 500 million or more.

 

The objective of this paper is to analyse the short-term market reaction of bidder firms toward the announcement of a M&A mega deal in Continental Europe during the sixth merger wave. As shown in related extant literature, we will focus on companies’ location as a determinant of investors’ price reactions. We will analyse the existence of differences in investor reaction that may arise due to the legal origin of the acquirer and target firms within Continental Europe. To obtain a complete picture of the market reaction, we do not only analyse changes in returns, but also expand the frame of analysis to volatilities and volume traded. The inclusion of the aforementioned market reaction indicators in this research is crucial, since it reveals reactions that would have been otherwise hidden by returns compensation.

 

We contribute to existing literature in several ways. First, we present more evidences to a limited stream of M&A research focused on Continental Europe. Research in this area is still centred on Anglo-Saxon countries, thereby increasing the difficulty in understanding Continental European markets. As a consequence, we also achieve a better understanding of investors’ reaction in governance systems different from the Anglo-Saxon system. Second, our research benefits extant literature by studying European takeover bids launched during the sixth takeover wave, particularly for mega deals. It has been already demonstrated that each wave shows different patterns and characteristics from its antecedents (Martynova and Renneboog, 2008), and that the size of transactions should be considered determinants of market reaction (Rosen, 2006). Third, we aim to present an in-depth analysis of investors’ reactions based on the legal origins of the companies involved in the deal.

 

The remainder of the paper is structured as follows. Section 2 presents a literature review about M&A announcements in Europe and postulates our hypothesis. In section 3, we describe the sample and methodology used, and in section 4 we analyse the empirical results obtained. Finally, section 5 presents our final remarks.

 

2.        Literature review

 

Investors’ reaction to M&A announcements involving large, medium, and small firms during the fifth wave was analysed in depth by Martynova and Renneboog (2011). The authors intensely exploited their 2,419 M&A announcementsʼ 1993– 2001 database to analyse factors affecting takeover announcement returns. They obtained a positive abnormal return of 0.53%, significant at the 1% level, to bidding shareholders. The list of determinants of the announcement returns is extensive, taking into consideration the takeover characteristics, characteristics of the bidding, and the target firms, as well as the legal environment and ownership structure. Regarding the legal environment, the authors separately investigated the market reactions to bidding announcements, which involved companies that belonged to two different corporate governance regimes—the UK and Continental Europe. The authors found that shareholders of UK target firms obtained a higher premium than those of Continental Europe. This is especially true for domestic deals, wherein shareholders of UK targets obtained higher premiums than those of Continental Europe not only on the takeover announcement date, but also over two months prior to the event.

 

These results are consistent with Goergen and Renneboog (2004) and Martynova and Renneboog’s (2006) analyses. The latter show that announcements made by bidding firms located in an English, German, or Scandinavian legal origin country returned a significant and positive abnormal return, while French and Socialist legal origin bidding firms did not obtain a significant return. However, Goergen and Renneboog (2004) studied 228 M&A announcements of European acquisitions undertaken between 1993 and 2000 for bids higher than US$ 100 million. The authors found a positive bidders’ reaction of 0.7% to announcements, with an announcement effect substantially larger for UK targets than for the Continental European ones. Furthermore, the authors found evidence that bids which involved a UK target returned a higher premium for both the target firm and the bidder. Moreover, bids on German, Austrian, and Swiss targets also showed significant positive returns for the bidding shareholder firm, although lower than in the previous case. Lastly, bids for southern European targets did not return a statistically significant result to the bidding firm.

 

The results obtained two years later by Faccio et al. (2006) only partially supported those obtained by Goergen and Renneboog (2004) and Martynova and Renneboog (2006, 2011). The authors studied the role of the listing status of targets in the acquirers’ cumulated abnormal returns for a sample of 4,429 M&A announcements made by Western European companies during 1996–2001. They found that bids for publicly traded targets imply a negative cumulative abnormal return (not significant) to acquiring  stockholders, whereas the stockholders of a privately  held target obtained a positive and significant return. Moreover, the authors found no significance in stock returns for bids made by companies located in France, Germany, Italy, Netherlands, and Sweden. Furthermore, taking into account the listing effects, Craninckx and Huyghebaert (2011) analysed intra-European deals during  the  fifth  takeover  wave.  The  authors  found  a  positive  and  significant abnormal bidding return for the sample of firms willing to acquire privately held companies, but non-significantly different from zero returns if the target firms were listed.

 

Finally, Campa and Hernando (2004) examined the effect of 262 M&A announcements related to Continental European listed firms, along with the UK and Ireland, from 1998 to 2001.  Contrary to Goergen and Renneboog (2004) and Martynova and Renneboog (2006, 2011), the authors did not find a reaction significance different from zero with respect to the M&A announcements for the bidding firm. Their results contradict those of previous authors, since they did not find any significance for friendly, domestic, or cross-border takeover bids. Their results regarding the relative size effect of the transaction remain unclear.

 

Following the Brown and Warner (1985) method, our hypothesis have been postulated in his null form:

 

 

Hypothesis 1 (H01): Market participants of Eurostoxx 50 companies do not find a mega M&A announcement informative.

 

We should expect to obtain positive abnormal returns (negative) if the announcement is positively (negatively) valuated by investors. Furthermore, we should also obtain increases (decreases) in volatility and the number of shares traded if investors find the information value-relevant, and then, take an investment decision as a consequence, but they assess the information differently among them.

 

3.        Sample selection and Methodology

 

In subsections 3.1 and 3.2, we present the sample and dataset used in this research, along with the method we propose to analyse the existence of differences in investor reaction to M&A announcements based on the legal origin of the acquirer and the target firm.

 

3.1.     Sample selection

 

We obtained abnormal stock returns, volatilities, and trading volumes related to M&A announcements between January 1, 2003 and December 31, 2007 of the Eurostoxx 50 stock market index components. The daily adjusted trading data and the number of shares traded was obtained from Thompson Reuters 3000Xtra. Information on acquisition announcement dates and transaction size was collected from Thomson Reuters Knowledge database. Finally, accounting and financial characteristics of bidders, payment method, deal attitude, and industrial sector was collected from S&P Capital IQ.

 

To include a transaction in the study, its value should be greater than US$ 500 million, offering a minimum relative size cut-off as proposed in Healy et al. (1992) and Alexandridis et al. (2017). Our cut-off is relatively higher than the one established in Goergen and Renneboog (2004)—US$ 100 million—or in Faccio et al. (2006)—US$ 5 million—in order to ensure a market reaction to the announcement.

 

We considered confounding effects, and as a consequence, cleaned events for companies announcing more than one deal within the pre-event window established in the ‘Methodology’. After all filters are applied, we are left with a final sample of 42 bidding companies announcing relevant transactions over 88 targets, which sums up to 92 events (see Appendix 1).

 

Both acquirers’ and targets’ firms are initially classified by legal origin following Djankov et al. (2003); that is, English, German, Scandinavian, French or Socialist. Appendix 1 lists the companies and their legal origin grouped as acquirers or targets. Evidently, the number of observations for Scandinavian legal origin does not allow us to perform an analysis by itself, so they have been added to the German legal origin sample.

 

Table 1 presents the number of announcements and total transactions values by year, as well as their statistics. There is some variation in the number of bids, 2007 being the year with the highest number of announcements, along with the 2004 Sanofi- Synthelabo offer for 100% control of Aventis, the highest transaction, by value, for the examined period. Graph 1 illustrates how this transaction raises 2004 to the second position for the period with highest value bid, in total transaction value, following year 2007.

 

Year

Number of deals

Total

Transactions value*

Minimum

Maximum

Average

Standard deviation

2003

11

12,750.69

589.19

1,990.00

1,159.15

491.60

2004

16

100,516.59

511.95

61,000.00

6,282.29

15,184.63

2005

18

88,041.05

500.70

30,720.00

4,891.17

8,200.83

2006

21

91,470.69

516.58

32,030.00

4,355.75

7,383.96

2007

26

102,732.49

500.00

24,260.00

3,951.25

5,425.45

* In million of dollars

Source: own elaboration based on data from Thompson Reuters Knowledge

Table 1. Sample statistics.

Source: own elaboration based on data from Thompson Reuters Knowledge

Graph 1. Number of deals and total transactions value per year

Tables 2 and 3 give information on market capitalisation, book value of Equity, Debt, and Total Assets, as well as the leverage for acquirers and EBIT and Net Income for target firms. We note that acquirers are much bigger than targets in both market terms and book values.

 

Bidders

Market Cap*

Equity book value*

Debt book value*

Total Assets*

Leverage

2003

26.96

21.70

50.73

231.77

0.78

2004

34.29

20.25

45.32

209.09

0.73

2005

40.75

22.70

74.74

271.38

0.76

2006

42.95

23.89

77.43

282.63

0.73

2007

50.68

29.27

72.21

280.67

0.76

*in billions of euros

Source: own elaboration based on data from S&P Capital IQ

Table 2. Sample statistics for acquirer firms

 

 

Targets**

Market Cap*

Equity

book value*

Debt book value*

Total Assets*

EBIT

Net Income

2003

8.74

2.97

1.82

44.38

0.11

-0.40

2004

22.70

15.13

13.47

96.95

3.29

2.09

2005

8.02

5.71

16.80

66.30

0.40

0.05

2006

8.73

4.34

3.91

36.78

0.74

0.63

2007

12.61

4.46

8.83

26.15

0.91

0.65

*in billions of euros

** public targets

Source: own elaboration based on data from S&P Capital IQ.

Table 3. Sample statistics for target firms.

 

Target and acquirers’ firm legal origins are summarised in Graphs 2 and 3. Our acquirers sample is mostly formed by companies located in a French legal origin country (France, Italy, and Spain), followed by German ones.

 

Our sample for targets is geographically more diversified than that of acquirers, since it contains acquisition announcements from target firms of 27 different countries. Once targets are grouped by legal origin, French legal origin targets are found to be predominant, followed by English, German, and Socialist legal origin targets.

Source: own elaboration based on Djankov et al. (2003) classification.

Graph 2. Bids by legal origin.

Source: own elaboration based on Djankov et al. (2003) classification.

Graph 3. Targets by legal origin.

Finally, Table 4 provides a comprehensive description of events. As depicted, our sample mostly constitutes friendly cross-border M&A announcements, paid in cash, wherein the primary strategy is to acquire a same industry target and obtain a majority stake or even 100% control.

Year

2003

2004

2005

2006

2007

Total

%

Announcements

11

16

18

21

26

92  100.00%

 

Targets

Public

5

5

9

7

6

32

34.78%

Private

4

8

6

13

15

46

50.00%

Assets

2

3

3

1

4

13

14.13%

NA

1

1

1.09%

 

Legal origin

Same

5

5

7

10

9

36

39.13%

Different

6

10

10

10

16

52

56.52%

NA

0

1

1

1

1

4

4.35%

 

Deal attitude

Hostile

0

0

1

0

0

1

1.09%

Friendly

8

14

14

18

24

78

84.78%

Friendly to Hostile

0

0

0

1

0

1

1.09%

NA

3

2

3

2

2

12

13.04%

 

Geographical scope

Domestic deals

4

3

4

5

4

20

21.74%

Cross-border deals

7

12

13

16

21

69

75.00%

NA

1

1

1

3

3.26%

 

Payment method

Cash

8

12

12

14

21

67

72.83%

Equity

0

0

3

2

2

7

7.61%

Combinations

0

1

0

1

0

2

2.17%

Assets

0

0

0

1

0

1

1.09%

NA

3

3

3

3

3

15

16.30%

 

Strategy

Focus-same industry

7

12

15

21

23

78

82.61%

Diversification

4

4

3

0

3

14

17.39%

Source: own elaboration based on data from S&P Capital IQ and Djankov et al. (2003) classification.

Table 4. Announcements characteristics.

 

3.2     Methodology

 

We follow the Brown and Warner (1985) event study methodology to assess the short-term wealth effects of the announcements for bidding firms’ stockholders. Abnormal price changes (Beaver, 1968) and trading volumes (Kim and Verrecchia, 1991) are investors’ responses to the disclosure of information. We test the aggregate market’s average reaction by testing changes in prices through two different measures: abnormal returns (ARs) and absolute value abnormal returns (AARs). Additionally, we examine the activity of individual investors around M&A announcements by analysing the change in trading volumes. These three indicators of the market reaction to the release of information have been tested by a t-test when the data is normally distributed, and otherwise, by a non-parametric test (Corrado, 1989; Corrado and Zivney, 1992).

 

We compute ARs as the difference between the actual and normal returns, while the latter are defined as the expected returns without conditioning on the event. Expected returns are obtained from the market model. To avoid compensation of positive and negative reactions to acquisition announcements, we also examine stock price volatility measured as the absolute value of abnormal returns. Then, we proceed with the method similar to the ARs. AARs are computed in absolute values, and corrected by the mean value of the pre-event period. Finally, we define abnormal volume (AV) as the number of shares traded on a given day divided by the average shares traded over the pre- and post-event estimation periods.

 

As it is widely used in the literature, we do not limit our research to the day of the event. However, we do additionally examine a five-day event window, starting at day -2 until day +2, and the event day—day 0. Lastly, cumulative average abnormal returns (CAARs), cumulative average absolute value abnormal returns (CAAARs), and cumulative average abnormal volumes (CAAVs) are all obtained by adding AARs, AAARs, or AAVs across different time intervals within the event window. Appendix 2 describes computations in detail.

 

4.        Results

 

In this section, we focus on the univariate analyses of CAARS, CAAARs, and CAAVs for bidding firms. We first present results obtained for the whole sample (see Table 5), the significance levels are tested according to the t-test for normally distributed samples or the Corrado test, otherwise. Tables 6 to 11 and 13 to 18 have identical structure; they present the investor’s reaction to the announcements when we consider all possible combinations of legal origin of acquirers and targets. Each table shows accumulated results reported for five periods. First, for the accumulated periods of [-2,0] and [0,+2], we analyse for the presence of an information leakage prior to the announcement or a delayed reaction, respectively. Periods [-1,0] and [0,1] give us information on a very short-term anticipated or delayed market reaction. Lastly, for the cumulated period of [-2,2], we summarise the cumulative reaction for the whole analysed period. The results have been tested according to the t- or Wilcoxon test.

 

Table 5 shows that the mean AAR for acquirers is negative (-0.29%) and significant on the day of the event . This is true for both the event day and all accumulated studied periods—the two-days [0, 1] accumulated effect of -0.46%. Thus, investors react negatively to a mega deal announcement, showing a five-day accumulated negative reaction from up to -0.92% and significant at the 0.01 level. This investors reaction coexists with a significant increase in volatility and volume traded on the event day and all accumulated periods. To control for the possibility of a listing effect, we consider the public and private firm in acquirers’ stock returns (not reported). The mean CAARs [-2,2] for acquirers of listed targets is negative (-0.97%) and significant at the 5% level, while the same measure for acquirers of private targets show a negative abnormal return of -0.99% and significant at the 5% level. Our results differ from those derived by Faccio et al. (2006), Martynova and Renneboog (2008), and Craninckx and Huyghebaert (2011). These authors also find negative CAARs for acquirers of listed targets, though they are not significant. The authors also report positive and significant returns for acquirers bidding for a non-listed firm.

 

 

 

 

 

Event period

Event day

Event period

Entire period

[-2,0]

[-1,0]

0

[0,1]

[0,2]

[-2,2]

CAARs (%)

-0.55

-0.52

-0.29

-0.46

-0.65

-0.92

p-value a

-2.68***

-3.07***

-2.43**

-2.73***

-3.16***

-3.43***

CAAARs

0.59

0.43

0.32

0.61

0.54

1.12

(%)

p-value b

2.63***

1.71*

2.53**

3.79***

4.76***

4.60***

CAAVs

0.67

0.55

0.45

0.81

1.14

1.36

p-value b

2.11**

2.58**

3.03***

3.14***

3.75***

3.18***

Observations

92

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ

  1. a) t-test
  2. b) Non-parametric test – Corrado test

Table 5 . This table summarizes bidder firms’ accumulated average abnormal returns, absolute value abnormal returns, and abnormal trading volumes around M&A announcements for the whole sample. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

The results of testing for the influence of legal origin in investors’ reaction are reported in Tables 6–8. Table 6 shows that investors of bidding firms bidding for a different legal origin target obtain a less negative return than investors of firms bidding for a same legal origin target. This reaction aligns with previous research, showing that firms may take advantage from operating in two different legal origin systems (Bris and Cabolis, 2008; Martynova and Renneboog, 2008). The results are graphically presented in Graph 4 for the accumulated period [-30, +10].

 

This analysis stands true for four out of five accumulated periods, with the announcement day being the only exception. However, none of the differences is significant for any of the accumulated periods analysed and at any significant level. More notably, subperiod [-2,0] returns an anticipated investor reaction of -1%, significant at the 0.05% level, for companies bidding for targets within the same legal origin.

 

 

 

 

CAARs (%)

Different legal origin

p-value a

Same legal origin

p-value b

Same – different

p-value on difference c

[-2,0]

-0.266

0.396

-1.000

0.014**

-0.735

0.199

[-1,0]

-0.309

0.291b

-0.843

0.064*

-0.532

0.335

[0, 1]

-0.504

0.034**

-0.393

0.085*

0.112

0.926

[0, 2]

-0.698

0.037**

-0.582

0.187

-0.115

0.611

[-2, 2]

-0.711

0.077*

-1.234

0.018**

-0.523

0.628

Observations

56

 

36

   

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ

  1. a) t-test
  2. b) Non-parametric test – Wilcoxon signed rank test
  3. c) Non-parametric test – Wilcoxon rank sum test with continuity correction

Table 6. This table summarizes bidder firms’ accumulated average abnormal returns taking into account bidder and target legal origin. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

Source: own elaboration based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

Graph 4. Bidders’ CAARs while bidding for a same or different legal origin target.

Regarding results for volatility, Table 7 shows an increase in volatility for periods [0,2] and [-2,2] only when bidding for a different legal origin target, although the effects in volatility are greater in some windows for operations with companies from the same legal origin. This is because of the presence of highly biased distributions, and the presence of some outliers prevents us from obtaining a significant result. For the volume analyses, Table 8 show an increase in the number of shares traded at a significance level of 5% for the entire period just when bidding for a same legal origin target.

 

CAAARs (%)

Different legal origin

p-value b

Same legal origin

p-value b

Same – different

p-value on difference c

[-2,0]

0.146

0.431

0.277

0.529

0.131

0.675

[-1,0]

0.171

0.711

0.283

0.798

0.113

0.971

[0, 1]

0.211

0.229

0.454

0.271

0.243

0.845

[0, 2]

0.215

0.012**

0.402

0.171

0.187

0.634

[-2, 2]

0.170

0.044**

0.316

0.371

0.146

0.734

Observations

56

 

36

   

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ

  1. b) Non-parametric test – Wilcoxon signed rank test
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correction

Table 7. This table summarizes bidder firms’ accumulated average absolute value abnormal returns taking into account bidder and target legal origin. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

 

CAAVs

Different legal origin

p-value b

Same legal origin

p-value b

Same – different

p-value on difference c

[-2,0]

0.180

0.465

0.291

0.174

0.110

0.399

[-1,0]

0.265

0.302

0.292

0.259

0.027

0.604

[0, 1]

0.398

0.188

0.418

0.123

0.019

0.651

[0, 2]

0.353

0.394

0.426

0.051*

0.072

0.350

[-2, 2]

0.223

0.622

0.349

0.048**

0.126

0.208

Observations

56

 

35

   

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ

  1. a) Non-parametric test – Wilcoxon signed rank test
  2. b) Non-parametric test – Wilcoxon rank sum test with continuity correction

Table 8. This table summarizes bidder firms’ accumulated average abnormal volume taking into account bidder and target legal origin. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

Tables 9–11 show CAARs, CAAARs, and CAAVs results obtained when splitting the sample between the two most predominant bidders’ legal origins in our sample— French and German. Table 9 shows that investors of firms belonging to German legal origin obtain more negative returns than investors of French legal origin ones. This result is consistent for four accumulated periods examined, with a significant positive difference at 5% level for French legal origin investors in periods [0,1] (+0.838) and [- 2,2] (1%), and at a 1% level for period [0,2] (+1.18%). Our results, surprisingly, contradict previous evidence that German or Scandinavian legal origin bidders generate a significantly positive announcement effect (Goergen and Renneboog, 2004) or with no significant return (Faccio et al. 2006). There is no significant effect for operations where the bidder is from a French legal origin. Our results align with previous literature which reported a lack of significance in stock returns in their analysis of southern European countries (Goergen and Renneboog, 2004), French and the EU enlargement legal  origin  countries  (Martynova  and  Renneboog,  2006),  and  some  by-country analyses in Faccio et al. (2006). Regarding the results in Table 10 on the CAAARs, there is a significant and positive increase in volatility when the bidder is from German legal origin. Contrary to the results obtained for volatility, abnormal and positive volume of shares traded is obtained from the French legal origin subsample (see Table 11) for all accumulated periods. Notwithstanding, none of the differences are significant at any level.

 

CAARs (%)

Bidder French legal origin

p-value b

Bidder German legal origin

p-value a

French – German

p-value on difference c

[-2,0]

-0.425

0.111

-0.786

0.123

0.361

0.360

[-1,0]

-0.370

0.284

-0.718

0.098*

0.348

0.243c

[0, 1]

-0.207

0.312

-1.045

0.002***

0.838

0.018**

[0, 2]

-0.309

0.353

-1.489

0.001***

1.180

0.008***

[-2, 2]

-0.587

0.183

-1.588

0.0098***

1.000

0.022**

Observations

63

 

26

   

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ

  1. a) t-tes
  2. b) Non-parametric test – Wilcoxon signed rank tes

c)Non-parametric test – Wilcoxon rank sum test with continuity correction.

Table 9. This table summarizes bidder firms’ accumulated average abnormal return taking into account the legal origin of the bidder. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

 

 

 

 

CAAARs (%)

Bidder French legal origin

p-value b

Bidder German legal origin

p-value b

French -German

p-value on difference c

[-2,0]

0.185

0.674

0.140

0.565

0.045

0.525

[-1,0]

0.186

0.937

0.206

0.532

-0.021

0.573

[0, 1]

0.310

0.449

0.304

0.165

0.006

0.254

[0, 2]

0.288

0.152

0.272

0.014**

0.016

0.212

[-2, 2]

0.222

0.293

0.170

0.059*

0.052

0.374

Observations

63

 

26

   

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. b) Non-parametric test – Wilcoxon signed rank tes
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 10. This table summarizes bidder firms’ accumulated average absolute value abnormal return taking into account the legal origin of the bidder. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

CAAVs

Bidder French legal origin

p-value b

Bidder German legal origin

p-value b

French – German

p-value on difference c

[-2,0]

0.257

0.097*

0.131

0.727

0.126

0.205

[-1,0]

0.325

0.067*

0.169

0.822

0.155

0.218

[0, 1]

0.453

0.027**

0.330

0.653

0.123

0.350

[0, 2]

0.466

0.026**

0.220

0.708

0.245

0.281

[-2, 2]

0.334

0.036**

0.138

0.727

0.196

0.261

Observations

63

 

26

   

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. b) Non-parametric test – Wilcoxon signed rank tes
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 11. This table summarizes bidder firms’ accumulated average abnormal volume taking into account the legal origin of the bidder. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

We have checked the composition of our two samples for several determinants of price reaction. Table 12 presents the percentage of big and small relative size transactions (relative size of the target out of the bidder’s size, small relative size transactions compute for the number of transactions at the last tercil, and big relative size transactions at the highest tercil, while transactions have been sorted from the highest relative size to the lowest), type of acquisition (full bid, majority, or minority stake), strategy (concentration, diversification), and cross-border or domestic. As almost all transactions are friendly and paid in cash, we do not consider them as price determinant. As is evident, samples do not differ much in composition.

 

 

French

 

German

 

Price determinants

Observations

%

Observations

%

Small relative size

16

25.40%

10

38.46%

Big relative size

24

38.10%

5

19.23%

Minority stake

15

23.81%

2

7.69%

Majority stake

25

39.68%

16

61.54%

Full bid

15

23.81%

4

15.38%

Concentration

53

84.13%

22

84.62%

Diversification

10

15.87%

4

15.38%

Domestic

16

25.40%

4

15.38%

Cross-border

46

73.02%

21

80.77%

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

Table 12: Bids characteristics of French and German legal origin sample

 

Tables 13–18 summarise the bidder firm’s investors’ reaction taking into account both the bidders’ (French or German) and targets’ legal origin (French, English, German, or Socialist). More notably, the sample sizes are extremely small. Tables 13–15 show CAARs, CAAARS, and CAAVs results for French legal origin bidders and English, German, or Socialist targets. Table 9 shows no abnormal returns of French legal origin investors to the announcements, and this result remains the same (see Table 13) even if we split our French legal origin sample by the target’s legal origin (there is a significant difference at the 10% level when bidding for a Socialist target, probably due to multiple testing problem). This is partially contrary to results obtained by Goergen and Renneboog (2004). The authors found a significant and positive higher premium for bids from a UK and German target, although the latter was not as high as the former.

 

With regard to volatility, Table 14 shows that bidding for a German legal origin company creates controversy among French legal origin investors, since we obtained significant increases in volatility in all periods for this specific subsample. No significance or even less than average volatilities are obtained for English or Socialist subsamples. This increase in volatility is also accompanied by an increase in the number of shares traded for English and German targets subsample, as shown in Table 15. Increases in volatility and volume traded indicate that investors find the announcement adequately value-relevant in order to make investment decisions on their portfolio according to their beliefs. Compensation among positive and negative abnormal returns does not allow appreciating the existence of investors’ reaction; therefore, the inclusion in the analyses of volatility and traded volume is crucial.

 

CAARs (%)

Bidder French Target English

p-value a

Bidder French Target German

p-value a

Bidder French Target Socialist

p-value a

[-2,0]

0.564

0.330

-0.421

0.585

-0.928

0.222

[-1,0]

0.363

0.417

-0.229

0.717

-0.436

0.073*

[0, 1]

-0.545

0.259

0.816

0.297

0.187

0.647

[0, 2]

-0.789

0.194

1.020

0.470

0.124

0.754

[-2, 2]

-0.350

0.940 b

0.681

0.635

-0.730

0.398

Observations

16

 

8

 

6

 

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. a) t-tes
  2. b) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 13. This table summarizes bidder firms’ accumulated average abnormal return taking into account the legal origin of the bidder and the target. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

CAAARs (%)

Bidder French Target English

p-value b

Bidder French Target German

p-value b

Bidder French Target Socialist

p-value b

[-2,0]

0.062

1.000

0.358

0.008***

-0.16

0.438

[-1,0]

0.085

0.980

0.416

0.008**

-0.372

0.031**

[0, 1]

0.151

0.900

0.426

0.055*

-0.280

0.063*

[0, 2]

0.101

0.669

0.481

0.055*

-0.134

0.156

[-2, 2]

0.080

0.744

0.397

0.039**

-0.097

0.438

Observations

16

 

8

 

6

 

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. b) Non-parametric test – Wilcoxon signed rank tes
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 14. This table summarizes bidder firms’ accumulated average abnormal absolute value return taking into account the legal origin of the bidder and the target. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

CAAVs

Bidder French Target English

p-value b

Bidder French Target German

p-value b

Bidder French Target Socialist

p-value b

[-2,0]

0.297

0.093*

0.362

0.641

-0.210

0.156

[-1,0]

0.432

0.046**

0.604

0.094*

-0.272

0.094*

[0, 1]

0.605

0.052*

0.822

0.052*

-0.322

0.031**

[0, 2]

0.566

0.074*

0.964

0.250

-0.325

0.031**

[-2, 2]

0.410

0.066*

0.558

0.313

-0.291

0.031**

Observations

16

 

8

 

6

 

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. b) Non-parametric test – Wilcoxon signed rank tes
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 15. This table summarizes bidder firms’ accumulated average abnormal volume taking into account the legal origin of the bidder and the target. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

Table 16 shows that German legal origin investors obtain an even more negative return when the firm is bidding for an English target–up to -1.78% for the period [0,2]–or a Socialist target (-1.80% for the entire period). This return does not go along with increases in volatility (see Table 17), and volume traded does not increase either (see Table 18) beyond marginal results at the 10% significance level.

 

CAARs (%)

Bidder German Target English

p-value a

Bidder German Target French

p-value a

Bidder German Target Socialist

p-value a

Event window

%

 

%

 

%

 

[-2,0]

-1.171

0.149

0.583

0.749

-0.046

0.953

[-1,0]

-1.251

0.070*

-0.095

0.953

0.202

0.792

[0, 1]

-1.262

0.0061***

-0.743

0.570

-1.022

0.179

[0, 2]

-1.784

0.0067***

-0.835

0.574

-1.597

0.081*

[-2, 2]

-1.718

0.015**

0.195

0.932

-1.808

0.037**

Observations

10

 

5

 

5

 

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. a) t-tes
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 16. This table summarizes bidder firms’ accumulated average abnormal return taking into account the legal origin of the bidder and the target. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

 

CAAARs (%)

Bidder German Target English

p-value b

Bidder German Target French

p-value b

Bidder German Target Socialist

p-value b

Event window

%

 

%

 

%

 

[-2,0]

0.161

0.846

0.479

0.188

-0.144

0.313

[-1,0]

0.268

0.846

0.554

0.438

-0.043

1.000

[0, 1]

0.342

0.846

0.425

0.313

0.333

0.813

[0, 2]

0.341

0.084*

0.276

0.188

0.376

0.313

[-2, 2]

0.194

0.084*

0.241

0.313

0.173

0.625

Observations

10

 

5

 

5

 

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. b) Non-parametric test – Wilcoxon signed rank tes
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 17. This table summarizes bidder firms’ accumulated average abnormal absolute value return taking into account the legal origin of the bidder and the target. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

CAAVs

Bidder German Target English

p-value b

Bidder German Target French

p-value b

Bidder German Target Socialist

p-value b

[-2,0]

-0.102

0.864

0.864

0.156

-0.126

0.125

[-1,0]

-0.105

0.275

1.072

0.156

-0.106

0.313

[0, 1]

0.001

0.695

1.550

0.094*

-0.066

0.813

[0, 2]

-0.039

0.625

1.083

0.094*

-0.028

0.813

[-2, 2]

-0.093

0.160

0.824

0.156

-0.067

0.813

Observations

10

 

5

 

5

 

Source: own calculations based on data from Thomson Reuters 3000Xtra and S&P Capital IQ.

  1. b) Non-parametric test – Wilcoxon signed rank tet
  2. c) Non-parametric test – Wilcoxon rank sum test with continuity correc

Table 18. This table summarizes bidder firms’ accumulated average abnormal volume taking into account the legal origin of the bidder and the target. Superscript ***, ** and * indicate significance at 1, 5 and 10% levels, respectively.

 

 

 

 

 

Table 19 presents a summary of the reactions.

 

Bidder legal origin

Abnormal returns

Abnormal volatilitie s

Abnormal volume

Target legal origin

Abnormal returns

Abnormal volatilities

Abnormal volume

TOTAL SAMPLE

YES (-)

YES (+)

YES (+)

French

NO

NO

YES (+)

English

NO

NO

YES

German

NO

YES (+)

SOME

Socialist

NO

SOME

NO

Germany

YES (-)

SOME (+)

NO

English

YES (-)

SOME (+)

NO

French

NO

NO

SOME (+)

Socialist

SOME (-)

NO

NO

         

Source: own elaboration

Table 19. Market reaction to mega M&As announcements.

 

5.        Final remarks

 

This paper analyses investors’ short-term reaction to mega merger and acquisition announcements during the sixth merger wave in Continental Europe. We also analyse the effect of legal origin on this reaction.

 

Our main result is a short-term negative abnormal return for the bidder stockholders’ firms as a consequence of the announcement, which contradicts previous evidence from the fifth merger wave in Continental Europe. This reaction is also accompanied with a significant above average level of market volatility and volume traded, thus indicating a strong controversy to market participants. Considering the listing effects on returns, we find that both bids for listed or unlisted targets concur in a negative and significant abnormal return. This result also contradicts previous literature for Continental Europe. A plausible explanation for both negative results for not only the whole sample, but also when considering listed and unlisted targets, may be due to our focus on analysing mega deals. In this scenario, transaction size is a determinant for investors than other factors.

 

When we take into consideration the legal origin of the bidders—French or German— we have been able to determine that the negative return reaction for the whole sample is mostly due to Germans’ legal origin bidders, although they only represent a little less than 30% of the sample. This is because German legal origin bidding firms concentrate the negative return reaction on the announcements—specifically, negative results concentrate on bids over English and Socialist legal origin target. Moreover, French legal origin bidders do not seem to react, since abnormal returns are not significant. Widening the analysis of French legal origin bidders, we also see that stockholders react with an increase in volatilities and the number of shares traded when bidding for a German legal origin target. Hence, for French legal origin investors, a mega deal announcement embodies sufficient information to decide on its portfolio, but it only can be seen as enhancing the frame of analysis for volatility and volume traded.

 

We would like to deepen our analysis by considering more variables, particularly target characteristics that could also determine investor reactions. However, the size of our sample does not allow such an analysis; otherwise, by increasing the number of observations through establishing our cut off at a lower transaction value may not reflect purely the stockholders’ reaction to a mega transaction.

References

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Brown, S.J. and Warner, W.B. (1985). Using daily stock return: the case of event studies.  Journal of Financial Economics, vol 14 (1), 3-31.

 

Campa, J. M. and Hernando, I. (2004). Shareholder Value Creation in European M&As. European Financial Management. Vol. 10(1), 47-81.

 

Campa, J. M. and Hernando, I. (2006). M&A Performance in the European Financial Industry. Journal of Banking and Finance, Vol. 30(12), 3367-3392.

 

Corrado, C.J. (1989). A nonparametric test for abnormal security-price performance in event studies. Journal of Financial Economics, Vol. 23(2), 385-395.

 

Corrado, C.J. and Zivney, T.L. (1992). The specification and power of the sign test in event study hypothesis tests using daily stock returns. Journal of Financial and Quantitative Analysis, Vol. 27, 465-478.

 

Craninckx, K. and Huyghebaert, N. (2011) Can Stock Markets Predit M&A Failure? A Study of European Transactions in the Fifth Takeover Wave. European Financial Management, Vol. 17 (1), 9-45.

 

Djankov, S., La Porta, R., Lopez-de-Silanes, F., Shleifer, A. (2003). Courts. The Quartely Journal of Economics, vol 118 (2), 453-517.

 

Faccio, M., McConnell, J. J. and Stolin, D. (2006). Returns to Acquirers of Listed and Unlisted Targets. Journal of Financial and Quantitative Analysis, vol 41 (1), 197-220.

 

Goergen, M., Renneboog, L. (2004). Shareholder wealth effects of European domestic and cross-border takeover bids. European Financial Management, vol (10),  9-45.

 

Healy, P.M., Palepu, K.G. and Ruback, R.S. (1992) Does Corporate Performance improve after mergers? Journal of Financial Economics, vol. 31, 135-155.

 

Kim, O. and Verrecchia, R. E. (1991). Trading Volume and Price Reactions to Public Announcements. Journal of Accounting Research, vol. 29 (2), 302-321.

 

 

 

Martynova, M. and Renneboog, L. (2006). Mergers and Acquisitions in Europe in: Renneboog, L. (ed.), Advances in Corporate Finance and Asset Pricing, 15-76. Elsevier, Amsterdam.

 

Martynova, M. and Renneboog, L. (2008). A century of corporate takeovers: What have we learned and where do we stand?. Journal of Banking & Finance. vol. 32, 2148-2177.

 

Martynova, M. and Renneboog, L. (2011) The Performance of the European Market for Corporate Control: Evidence from the Fith Takeover Wave. European Financial Management, vol. 17 (2), 208-259.

 

Menendez, S. (2005). Market valuation of the analysts’ recommendations: the Spanish stock market. Applied Financial Economics, vol. 15, 509-518.

 

Rosen, R. J. (2006). Merger Momentum and Investor Sentiment: The Stock Market Reaction to Merger Announcements. Journal of Business. vol. 79 (2), 987-1017.

 

 

 

APPENDIX 1: ACQUIRERS AND TARGETS

 

 

Acquirers

Acquirer Country

 

 

Legal Origin

Anheuser-Busch Inbev

 

Nokia

Belgium

 

Finland

French

 

Scandinavian

Air Liquide Axa

BNP Paribas Carrefour

France Telecom

France France France France

France

French French French French

French

Gaz de France L’Oreal

Saint Gobain

 

Sanofi

France France France

France

French French French

French

Schneider Electric Societe Generale Unibail

Vinci

France France France

France

French French French

French

Vivendi Allianz

Bayer Schering

 

Daimler

France Germany Germany

Germany

French German German

German

Deutsche Bank Deutsche Borse Deutsche Telekom

E.ON

Germany Germany Germany

Germany

German German German

German

Munich Re RWE

SAP

 

Siemens

Germany Germany Germany

Germany

German German German

German

CRH

Assicurazioni Generali Enel

Ireland

Italy Italy

English French

French

 

ENI

 

Intesa Sanpaolo

Italy

 

Italy

French

 

French

Telecom Italia Unicredit ArcelorMittal

ING

Italy Italy Luxembourg

Netherlands

French French French

French

Koninklijke Philips Electronics Banco Bilbao Vizcaya Argentaria Banco Santander Central Hispano

Iberdrola

Netherlands

Spain Spain Spain

French French French

French

Repsol YPF

 

Telefonica

Spain

 

Spain

French

 

French

 

 

 

Targets                                                                                 Target Country   Legal Origin

 

City Sued Shopping Center                                                     Austria     German Atacadao Distribuicao Comercio e Industria Limitada                                       Brazil            French

TIM Celular                                                                                        Brazil            French

Telefonica Movil Chile                                                                       Chile            French

 

China Citic Bank                                                                                China          Socialist

 

Maurel et Prom’s assets in Congo                                                     Congo            French

 

AGF Assurances                                                                               France            French

 

Autoroutes du Sud de la France                                                        France            French

 

Aventis                                                                                              France            French

 

Cofiroute                                                                                           France            French

 

Industrial Turbines Business of Alstom                                            France            French

 

Pinault Bois et Materiaux                                                                  France              French

Office Properties in Paris and Brussels                                            Belgium            French

Bayerische Hypo-und Vereinsbank                                                Germany          German

DaimlerChrysler Luft- und Raumfahrt Holding                             Germany          German

Gabriel Sedlmayr Spaten-Franziskaner-Brau                                Germany          German

Messer Griesheim GmbH’s gas operations                                   Germany          German

 

Norisbank                                                                                      Germany          German

 

Saar Ferngas            

 

Schering

Germany

 

Germany

German

 

German

STADTWERKE LEIPZIG

 

Ghana Telecom

MOL Foldgaztaralo Rt MOL Storage 2S Banca

Germany

 

Ghana Hungary

Italy

German English Socialist

French

Assicurazioni Generali Banca Nazionale del Lavoro CAAM SGR

Capitalia

Italy Italy Italy

Italy

French French French

French

Monte dei Paschi di Siena’s (MPS’s) bankassurance

 

and pension operations

 

 

Italy

 

 

French

Olimpia

 

Riunione Adriatica di Sicurta

Italy

 

Italy

French

 

French

Telecom Italia Mobile Toro Assicurazioni Unicredito Italiano

Wind Telecomunicazioni

Italy

Italy

French French French

French

Arcelor

 

Quilmes Industrial

Grupo Financiero BBVA Bancomer S A de C V Euronext

Luxembourg Luxembourg

Mexico

 

Netherlands

French French French

French

Orange Nederland Rodamco

Zentiva

 

TeleRing

Netherlands Netherlands Netherlands

Norway

French French French

Scandinavian

Polska Telefonia Cyfrowa

 

SECIL Companhia Geral de Cal e Cimento Electrica Muntenia Sud

OGK-4

 

RESO-Garantiya

Poland Portugal Romania Russia

Russia

Socialist French Socialist Socialist

Socialist

Severneftegazprom

 

United Financial Group

Russia

 

Russia

Socialist

 

Socialist

 

Orange Slovensko

 

Slovenske Elektrarne

Slovakia

 

Slovakia

Socialist

 

Socialist

Compania Espanola de Petroleos Endesa

Terra Lycos

 

Terra Networks

Spain

Spain

French French French

French

Wind Farms in Spain and Italy Dahl International

Winterthur Swiss Insurance

 

TMB Bank

Spain/Italy Sweden Switzerland

Thailand

French Scandinavian

German

 

English

Tupras Turkiye Petrol Rafinerileri Avent Holdings

Body Shop International

 

BPB

Turkey

UK

French English English

English

Burren Energy Caledonia Oil and Gas Four Seasons Healthcare

London Stock Exchange

UK

UK

English English English

English

O2

 

BMG Music Publishing Group Drive Financial

Energy East Corp

UK  US

US

English English English

English

Excelerate Energy

GMAC Commercial Mortgage GSM Network of Cingular Laredo National Bancshares

US

US

English English English

English

Lumileds Lighting MONY Group NAVTEQ Corp OutlookSoft

Pelco

US

US

English English English English

English

Retek

 

Shenzi Deep Water Oil Field

US

 

US

English

 

English

 

Sovereign Bancorp

 

Ashland Global Holdings

US

 

US

English

 

English

128 Commercial properties Midland

Non-Listed capital risk assets

NA NA

NA

NA NA

NA

 

 

 

 

APPENDIX 2: ABNORMAL RETURN AND VOLUME CALCULATIONS

Abnormal return

 

The return of security i over period t is defined as:

 

Rit = E(Rit | Xt)it + ARit              [1]

 

where, Rit , E(Rit|Xt)it and ARit are  the  actual, normal, and abnormal returns, respectively, and Xt is the conditioning information set for the normal return model.

 

We compute expected or normal returns by using the market model, thus we assume that normal return is given by a linear relationship between the stock and the market return.

𝐸(𝑅$% |𝑋%)$% = 𝑎$ +

𝑏$                                                                                                                                                                 𝑅.%                                                                                                                                                                                  [2]

 

Where:

𝑅.%  =

𝑙1 234567588 9: ;75<= >?4=@7 ABC@8 D   G                                                             [3]

234567588 9: ;75<= >?4=@7 ABC@8 DEF

 

 

We estimate the security normal returns through a pre-event period of 151 days starting on day -170 to day -20 been day 0 the M&A announcement date.

Average abnormal returns (AARs) has been obtain averaging abnormal returns of each event. Thus, AARs is calculated as:

 

 

Cumulative average abnormal return (CAAR) has been calculated by adding the average daily abnormal return for different time intervals (a, b), within the event window [-2, +2].

Absolute Abnormal Return

 

Absolute abnormal returns has been obtain applying the absolute value of each abnormal return. Then, we proceed averaging them, thus AAAR is given by:

Cumulative average absolute abnormal return (CAAAR) is obtained by adding average daily absolute abnormal returns across different time intervals (a, b), within the event window [-2, +2].

 

Abnormal Volume

 

Following Menendez (2005), we define abnormal trading volumes for stock i on day t as:

Once abnormal daily volumes have been computed for each firm, the average abnormal trading volume (AAV) on day t is calculated as:

The cumulative average abnormal volume (CAAV) is obtained by adding average daily abnormal volumes across different time intervals (a, b), within the event window [-2,+2].

 

 

 

                         

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