Shareholder wealth effects of mergers and acquisitions in

Western Europe

AmsterdamBusinessSchool

Name Xander Jager

Student number 10660755

Program Economics & Business

Specialization Economics and Finance

Number of ECTS 12

Supervisor Mr.R.J.(Robin)Döttling

Target completion 31/1/2018

Abstract

This thesis investigates the short-term wealth effects of acquiring firm’s shareholders in Western

Europe from mergers and acquisitions announcements, over the period 2010 and 2017. I examine this

with the event study methodology described by MacKinlay (1997). I provide detailed information

about what mergers and acquisitions are, motives of M&A, merger waves, the method of payment and

bid characteristics. Also, I analyze the expected shareholder wealth effect through testing

shareholders’ Cumulative Average Abnormal Return (CAAR). Denmark, France and the Netherlands

experience a statistically significant negative CAAR in different event windows around the

announcement date. Furthermore, the results in this thesis suggest a statistically significant negative

CAAR of the total Western European sample over a 10-day, 5-day and 1-day window centered around

the event day. Additionally, I find that different methods of payment have a negative impact on the

share prices of acquirer firms.

Keywords: mergers and acquisitions; merger waves; method of payment; short-term wealth effects

JEL classification: G32, G34

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Statement of originality

This document is written by Student Xander Jager who declares to take full responsibility for the

contents of this document.

I declare that the text and the work presented in this document are original and that no sources other

than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the

work, not for the contents.

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TableofContents

1. INTRODUCTION ......................................................................................................................................... 4

2. LITERATURE REVIEW ............................................................................................................................. 6

2.1 WHAT IS M&A? ............................................................................................................................................. 6 2.2 MOTIVES OF MERGERS AND ACQUISITIONS ................................................................................................... 6 2.3 MERGER WAVES ............................................................................................................................................. 8 2.5 BID CHARACTERISTICS ................................................................................................................................. 10

3. DATA AND METHODOLOGY ................................................................................................................ 11

3.1 DATA ............................................................................................................................................................ 11 3.2 METHODOLOGY ............................................................................................................................................ 11

3.2.1 Event Study ........................................................................................................................................... 11

4. RESULTS .................................................................................................................................................... 15

4.1 EVENT STUDY RESULTS ................................................................................................................................ 15 4.2 IMPACT OF THE METHOD OF PAYMENT ......................................................................................................... 18

5. CONCLUSION ............................................................................................................................................ 20

6. DISCUSSION .............................................................................................................................................. 21

7. REFERENCES ............................................................................................................................................ 22

8. APPENDIX .................................................................................................................................................. 25

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1. Introduction Mergers and acquisitions (M&A) are a popular way of corporate development. In 2017, companies

announced over 50.000 transactions with a total value of more than 2.9 trillion EUR. The number of

deals in 2014 increased by 12.63% compared to 2013 and the total value of the transactions increased

by 107,16%. The acquisition of SABMiller by Anheuser-Busch InBev SA/NV, BG Group by Royal

Dutch Shell and Covidien by Medtronic are examples of sizable acquisitions from Western Europe in

the last few years with a deal value of 91.93, 64.4 and 31.56 billion euros, respectively (IMAA, 2017).

Figure 1: Number and Value of M&A in Western Europe. Source: IMAA

M&A profitability generated a small peak of research in the last 40 years. There is disagreement

among researchers about the announcement wealth effects of bidding firms. Walker (2000), Mitchell

and Stafford (2000), Akbulut and Matsusaka (2010) and Healy et al. (1992) find small negative

returns for bidding companies. On the other hand, researchers reveal small or zero positive abnormal

returns (Martynova and Renneboog, 2006; Eckbo and Thorburn, 2002; Macquira et al., 1998;

Schwert, 2000; Loderer and Martin, 1990). Bidders and targets shareholders combined earn positive

adjusted returns so that one should suggest that M&A does pay. However, much research illustrates

around a zero return to bidding companies. Synergies, efficiencies and value-creating growth seem

hard to realize, so managers should be careful with participating in M&A activity (Bruner, 2002).

The most research of mergers and acquisitions focus on the United States or M&A activity in one

country. The literature on domestic mergers and acquisitions is consistent. The target firm’s

shareholders receive a premium of 20-40% on average relative to the stock price before the

announcement (Goergen and Renneboog, 2004). Mulherin and Boone (2002) report abnormal

announcement returns of 21% in the USA in the 1990s. Besides, average target abnormal returns in

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the USA are 29% for 1963-1986, 24% for 1972-1987 and 27% for 1971-1982 (Jarrel and Poulsen,

1988; Servaes, 1991; Kaplan and Weisbach, 1992).

This thesis adds to this literature by examining the short-run effect of an M&A announcement in

Western Europe on stock prices. I provide further evidence on the creation of short-term shareholder

wealth effects expected by M&A activity. The research question is:

What is the short-term effect of an M&A announcement on abnormal returns for acquirer Western

European shareholders from 2010 till 2017?

I investigate the short-term returns for Western Europe mergers and acquisitions with the event study

methodology described by Mackinlay (1997). The event study has many applications. In finance

research, event studies practiced to a diversity of firm-specific and economy-wide events. To measure

the short-term shareholder value creation of M&A announcements, I use the methodology of the

market model. I apply the event study to a sample of 81 M&A announcements of Western European

acquiring companies from 2010 till 2017. Also, I investigate the impact of the method of payment on

stock prices.

I find a statistically negative CAAR for Denmark, France and the Netherlands in different event

windows around the M&A announcement date. The acquirer shareholders in Denmark, France and the

Netherlands lose money when a merger or acquisition occurs. Further, I reveal a statistically negative

CAAR of acquirer firm’s shareholder from Western Europe.

Also, all-cash bids, all-equity bids and the combination of cash, debt and stock bids in the

sample generate a negative price correction.

Finally, I claim that managerial hubris and the agency motive restrict the bidding firm’s

shareholders to experience significant positive abnormal returns in the seventh merger wave.

I organized this thesis as follows: section 2 shows the literature about mergers and acquisitions.

Section 3 describes the research methodology, variables and data sources. Section 4 provides the

results of the event study and the impact of the method of payment. Section 5 summarizes the main

conclusions from this study.

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2. Literature review

2.1 What is M&A?

Mergers and acquisitions (M&A) are often referred as the market for corporate control. There is

typically a buyer, the “acquirer” or “bidder”, and a seller, the “target”, when one firm acquires

another.

The target company can merge with the acquirer company. Also, a corporation, firm or group

of individuals can acquire the target firm. These are the two primary mechanisms by which control

and ownership of a public corporation can change. The acquiring firm absorbs the target firm and

goes further on as one company with an acquisition. In the case of a merger, the acquirer and target

acknowledge going further as one new firm rather than two different companies separately owned.

The transaction with a merger or an acquisition is the same, because the acquirer must buy the shares

of the target firm. When an acquisition occurs, it is not necessary that the acquirer purchases the full

hundred percent shares of the target. There are also examples of acquisitions which involve a minority

of shares.

Mergers and acquisitions that take place in the same industry refer to horizontal mergers and

vertical mergers are M&As of firms producing different services or goods for a specific finished

product. Further, M&As between business unrelated to each other are called conglomerate mergers

(Berk and DeMarzo, 2011).

2.2 Motives of Mergers and Acquisitions Mukherjee et al. (2004) provide insights on the motives for acquisitions based on a survey among 75

CFOs in the United States during 1990-2001. The results show that the essential motive is synergy

(37.3%), the second motivation is diversification (29.3%) and lastly achieve a specific organizational

form as part of an ongoing restructuring program (10.7%). Other reasons that responding CFOs gave

for their M&As are: acquire a company below its replacement cost, use excess free cash and reduce

the tax of the combined company due to tax losses of the acquired company.

Acquirers justify their takeovers with many potential synergy reasons from mergers and

acquisitions while the forecasted benefits are often not realized. The majority of research presents that

there are three major reasons for takeovers: synergy motive, managerial hubris and the agency

problem. I illustrate these reasons now:

1. Synergy motive

The first motive for M&A is synergies, the primary motive for a merger. Synergy is a justification that

acquirers give for the premium they pay for a target. An acquirer could add economic value after the

acquisition and an individual investor could not have done this. Berk and DeMarzo (2007) describe

the most often reasons of acquirers to justify their takeovers: vertical integration, expertise, efficiency

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gains, monopoly gains, tax savings from operating losses, economies of scale and scope,

diversification and earnings growth.

The synergy motive assumes that managers of acquirers and targets maximize shareholder

value and that they only participate in M&A activity if it results in gains to both of their shareholders.

Thus, when synergy motives takeovers the measured benefits to both acquirer and target shareholders

should be positive.

If the target can resist the acquirer or there is a race among possible acquirers for the specific

target, then the target has some bargaining power. The target gain will increase with the total gain.

Also, the wealth gains to the target shareholders correlate positively with the acquirer shareholders

and the total wealth gain (Goergen and Renneboog, 2002).

2. Managerial hubris

The second, unsuccessful, explanation of a merger or acquisition shows Richard Roll. Roll (1986)

brings forward that managerial hubris is the main reason that leads to a high number of value-

destroying mergers and acquisitions. Managers are likely overconfident in their abilities in general.

Research points out that it takes repeated losses for a manager to change his belief that he is above-

average at some actions (Berk and DeMarzo, 2007). The hubris hypothesis is an explanation of

corporate takeovers, which supports that CEOs that are overconfident seek mergers with a low chance

of creating value. The reason behind this comes from CEOs that believe their ability to manage is big

enough to succeed.

Next, Roll (1986) points out that hubris on individual decision makers in acquirer firms can

explain why bids made even when a valuation above the current market price represents a positive

valuation error. Acquirer firms that are infected by hubris pay too much for their target companies.

Goergen and Renneboog (2004) also show that one-third of the large European takeovers in the 1990s

experience managerial hubris. Other evidence of managerial hubris comes from Malmendier et al.

(2005). They conclude that overconfident managers, who choose to retain from shares in their firms,

make less profitable and diversifying takeovers.

3. Agency problem

The agency problem is the third M&A motive. Managers and shareholders are in possession of a

conflict of interest about payout policies when a firm has a substantial amount of free cash flow.

Managers may be tempted to use free cash flow to increase the size of the company, this is known as

‘empire building’. They use free cash flows for increasing the size of the firm instead of returning

these to the shareholders (Jensen, 1986). Further, managers have the incentive to run a more

prominent company, because of the extra salary and prestige it brings to run such an organization. The

private benefits are increasing for managers in correlation with the firm size (Goergen and

8

Renneboog, 2004).

Conyon and Murphy (2002) show an example from the United Kingdom that size is the

primary explanation of managerial salaries, bonuses and allocation of share options instead of

performance. Moreover, Harford and Li (2007) show that in 75% of the mergers where the acquiring

shareholders lose money, the acquiring CEOs are financially better off. Furthermore, Harford (1999)

indicates that the abnormal return of cash-rich acquiring companies becomes negative as a reaction to

takeover announcements and this is decreasing with the amount of free cash flow held by the

acquiring company. This negative abnormal return points out that acquiring firms with a substantial

amount of free cash flow destroy value by overbidding. As a consequence, cash-rich acquiring

companies that undertake value-decreasing acquisitions have a higher chance of being taken over in

the following years (Lang et al., 1991).

Managers are aware of destroying shareholder wealth under the agency problem, but they are better

off from doing so. The agency problem is different from the hubris hypothesis, because the

overconfident CEOs think they are doing an excellent job for their shareholders. Though, they are

overestimating their capabilities.

In summary, while synergy is the reason for the majority of the takeovers, there is substantial

evidence that agency problems and managerial hubris motivate acquisitions. However, agency

problems, not managerial hubris, seems to be the primary motive in takeovers with total negative

gains (Berkovitch and Narayanan, 1993). The findings of this thesis can suggest whether the bidding

firm’s shareholders experience negative or positive benefits due the synergy motive, managerial

hubris, the agency motive or all.

2.3 Merger wavesMerger waves are periods with increased M&A activity followed by a smaller amount of transactions.

Merger waves characterize the takeover market. During economic expansion, merger activity is higher

than during contractions and correlates with bull markets (Berk and DeMarzo, 2007). For this reason,

merger activity is higher in periods of economic expansion than during a financial crisis. M&As are

increasing significantly since the economy is improving the last years after leaving the financial crisis

behind. The financial crisis started in 2008 after the collapse of Lehman Brothers (Von Hagen et al.,

2011).

Merger waves can originate from market timing or clustering of industry shocks for which

mergers facilitate changes to the new environment. Economic, regulatory and technological shocks

drive industry merger waves. If the shock leads to a wave of mergers, this is due to whether there is

sufficient overall capital liquidity present to accommodate the necessary transactions. The economic

motivation for merger activity is the simultaneous peak in divisional acquisitions for cash (Harford,

2005).

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The first European merger wave aimed at creating monopolies and took place between 1880

and 1904. Anti-trust regulation forbade monopolies and this formed the second merger wave (1919-

1929) which increased vertical integration (Goergen and Renneboog, 2002). The third merger wave

started in the 1950s and reached its peak in the 1960s. This wave is known as the conglomerate wave,

because firms became large conglomerates and bidding companies acquired firms in an unrelated

business. Hostile takeovers characterized the fourth wave and junk bond financing recognized this

period (Lipton, 2006). The fifth wave was the era of the mega-deal from 1993 to 2002. It ended with

the bursting of the Millenium Bubble, also known as the Dotcom bubble. Only three years later the

sixth wave started and was encouraged by globalization.

Moeller et al. (2005) examined the experience of acquirer shareholders in the fifth merger

wave. They found that acquisition announcements in the 1990s were profitable in the aggregate for

acquirer firm’s shareholders until 1997. But, the losses from the shareholders of acquiring companies

from 1998 through 2001 destroyed all the gains made earlier. Hence, acquisition announcements in

the fifth merger wave were costly for acquiring firm shareholders.

In this thesis, the focus is on the most recent merger wave: the seventh merger wave. There is not

much research done in this period, because the wave is still busy. In 2014, optimism was returning to

the market and the largest volume of transactions occurred since 2007. The environment of M&A

after the financial crisis, characterized by risk aversion and a focus on natural growth by firms, has

disappeared.

2.4 Method of payment

An acquiring company has to choose between three methods of payment in M&A transactions: an all-

stock bid, all-cash bid or a combination of cash, debt and stock. The choice an acquiring company

makes is a meaningful signal of the quality of the target firm. The price that an acquirer offers for a

target firm is the initial value of the target before the acquisition and increased by an acquisition

premium.

Jensen (1986) shows evidence that managers use free cash flow for ‘empire building’ as

mentioned before. Financing with cash has a positive effect on managers to using resources more

efficiently. Cash or debt, chosen as a payment method, will also generate more benefits than with

stock financing.

Furthermore, Myers and Majluf (1984) conclude with the pecking order theory that managers

with superior information first will choose to finance their investment with internally generated cash,

then debt and as third option equity. When an acquirer company issues debt, the stock price will not

fall. If equity is issued to finance an investment, the stock price will drop and this is not favorable for

acquirer stockholders. Asymmetric information between the acquirer’s management and outside

investors can influence the choice of payment.

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The method of payment in a takeover bid affects the share price of a target firm. All-cash

offers and combined cash, equity and loan notes bids have higher abnormal returns than all-equity

bids. If the real value of bidding firm’s shares is worth more than the current price, bidding managers

will issue equity, because they believe that their firm’s shares are overpriced. Managers issuing equity

corresponds with the theory that they release new shares when the stock market is booming (Goergen

and Renneboog, 2004; Martynova and Renneboog, 2006). Acquiring firms that finance their

investment with stocks are overvalued and they use cash to fund their investment when they think

their shares are undervalued (Shleifer and Vishny, 2003).

In the results, I investigate how the market responds to the announcement of M&A transactions for

acquiring firms by the method of payment used in the transaction. I expect a positive price correction

for all-cash bids, because the market interprets the financing choice as a signal about the firm’s over-

or undervaluation. I predict a negative price correction for all-equity bids and bids with equity

involved. The share price of the bidding firm should increase with an all-cash bid and decrease with

an all-equity bid.

2.5 Bid characteristics

An important factor that defines a transaction is the approach of an acquirer. Either the acquiring

company makes an offer to the Board of Directors of the target company. Or the acquirer ignores the

Board and makes the offer directly to the target shareholders; this is a hostile takeover. The approach

of an acquirer company is important, because the type of takeover tactic has a sizable impact on the

short-term wealth effects for the target firm shareholders.

Acquirer shareholders can have negative returns with a hostile takeover since they would

have to pay a higher premium and target shareholders obtain higher returns due to competitive bids

leading to better offer prices. The impact on short-term wealth effects for target shareholders during a

hostile takeover is substantially higher (announcement effect of 12.6% on day 0) than for mergers and

friendly acquisitions (8% and 22% on day 0).

Hence, the market is expecting that opposition against a bid lead to a change of the offer and

eventually to a higher premium. The study of Goergen and Renneboog (2004) confirm this: the

announcement of a merger or friendly acquisition causes a positive abnormal gain of 2.5% whereas a

hostile acquisition produces a negative abnormal return of 2.5%.

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3. Data and Methodology In this chapter, first I show how I collect the data for this research and which criteria I set. Then I

discuss the event study of MacKinlay (1997).

3.1 Data In this section, I present the used data sample. The sample includes Western European M&A deals

completed between 01/01/2010 and 01/01/2017. Data of Western European mergers and acquisitions

are from the Zephyr database. Zephyr contains information about 1.2 million transactions and rumors.

The selection criteria for M&A announcements are:

1. Mergers and acquisitions announced between 1 January 2010 and 1 January 2017

(completed-confirmed)

2. The acquirer and target has to originate from Western Europe1

3. Percentage of the final stake is hundred percent

4. The acquirer and target are listed or delisted companies

I collect a sample of 97 M&A announcements and I add an overview of the sample in the appendix as

Appendix 1. However, I exclude 16 announcements due to lack of available information. As a result,

the sample consists of 81 M&A announcements. From the sample, I use the daily return on stock

price. The daily gains of the sample are from the database: DataStream. DataStream is a global

macroeconomic and financial data platform covering stock market indices, currencies, equities and

more.

3.2 Methodology

3.2.1 Event Study

I investigate the stock price reactions of bidding firms to measure the announcement effect of M&A.

Based on the efficient market hypothesis, stock prices fully reflect available information about a

company and its future (Fama, 1970). Event studies, survey data, accounting studies and case studies

are the four primary methods to determine the effect of mergers and acquisitions.

I use an event study to measure the effect of an M&A announcement on the abnormal returns

of the stock. Event studies have a long history. The first published study is the work of James Dolley

(1933). James Dolley examines in his work the price effect of stock splits, studying nominal price

changes at the time of the division (MacKinlay, 1997). An event study measures the impact of an

event on the stock price of a firm with financial data over a time window. Based on the papers of

MacKinlay (1997) and Brown and Waner (1985) the methodology for this study is determined.

1 Zephyr classified Western European countries as: Andorra, Austria, Belgium, Cyprus, Denmark, Finland, France, Germany, Gibraltar, Greece, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Spain, Sweden, Switzerland, Turkey and the United Kingdom.

12

First, I identify the event day; the day a Western European company announces the merger or

acquisition. The event day is the first day that the market is informed about the new information.

Then I should define the event window, the period during which effects of the event are

possible detected. The event window must be long enough to cover the whole event, but unnecessary

days must be excluded that can negatively affect the power of the test. In a perfectly efficient market

it would be sufficient to restrain the event window only to include the event day, but in practice, the

event window is expanded due to possible information leakage of the event days before it. The impact

of the event on the price of the stock is reflected in the days after the event day. I use an event window

of 21 days and note this as [-10, +10]. The event window consists of ten days before the M&A

announcement and ten days after. Also, I analyze other event windows: [-5, +5], [-2, +2] and [-1, +1]

based on the articles of Brown and Warner (1980,1985). 𝐿" = 𝑇" − 𝑇' is the length of the event

window.

After defining the event window, I determine the estimation period. During the estimation

window, no event takes place. Estimating the estimation period is necessary, because I need to decide

how the returns of the stock should be under normal circumstances if no event had taken place. The

estimation period and the event window must not overlap to obtain unbiased estimates. The estimation

period, 𝐿' = 𝑇' − 𝑇(, is determined at 180 days before the start of the event window: 𝐿' =

−170 − −10 . I choose for an estimation period of 170 days.

Figure 2: Event study timeline. Source: MacKinlay (1997)

Normal returns would be the returns on the stock if no event took place. Chatterjee (1986) noted that

monthly data to estimate regression parameters give two fundamental problems: the long estimation

period is relatively sure to pick up non-stationarity in the regression parameters and the Cumulative

Abnormal Returns are probably affected by events which are not related to the merger. For that

reason, I use daily returns.

An estimation of the impact on the event requires a measure of the abnormal return. The abnormal

return for firm i and event date τ is:

𝐴𝑅/,1 = 𝑅/,1 − 𝐸 𝑅/,1 𝑋𝜏)

13

where 𝐴𝑅/,1, 𝑅/,1and𝐸 𝑅/,1 𝑋𝜏)are the abnormal, actual and normal returns for a given security 𝑖and

dayτ.

The market model is a commonly used method for creating the normal return. Also, the constant mean

return model is a method to generate the normal return. In short-term event studies, simple approaches

like the constant mean return model and the market model work adequately (Brown and Waner,

1985). In this thesis, the model used to test the existence of abnormal returns in the event period is the

market model.

The market model, a statistical model, demonstrates the returns of any given security to the

return of the market portfolio. A primary assumption of the market model is the joint normality of

asset returns. The market model for any security i is:

𝑅/,1 = 𝛼/ + 𝛽/𝑅>1 + 𝜀/1

𝐸(𝜀/1 = 0)𝑣𝑎𝑟 𝜀/1 = 𝜎EFG" ,

where 𝛼/, 𝛽/ and 𝜎EFG" are the parameters of the model and 𝜀/1 is the zero-mean disturbance term. 𝑅/,1

and 𝑅>1 are the period-t returns on security i and the market portfolio.

For the market portfolio, a broad-based stock index is used such as the AEX, S&P 500 and the CRSP

Value Weighted Index. Here, I use the Stoxx Europe 600 Index because all firms of the sample are

European companies.

The market model parameters use ordinary least squares (OLS) as a measurement procedure under

common conditions. For an estimation window of observations, the OLS estimators of the market

model parameters are:

𝛽H =(𝑅/I − 𝜇/)(𝑅>I − 𝜇>)

KLIMKNO'

(𝑅>I − 𝜇>)"KLIMKNO'

𝛼/ = 𝜇/ − 𝛽/𝜇>

𝜎EF" =

1𝐿' − 2

(𝑅/I − 𝛼/ − 𝛽/𝑅>1)"KL

IMKNO'

where 𝜇/ ='QL

𝑅/IKLIMKNO' and 𝜇> = '

QL𝑅>I

KLIMKNO' . 𝑅/I and 𝑅>I are the returns is event period 𝜏

for security i and the market.

14

Further, I explain the use of the ordinary least squares estimators to measure abnormal returns and to

develop their statistical properties. First, I present the statistical properties of abnormal returns

followed by the aggregation of abnormal returns.

The abnormal returns are measured and analyzed with the parameter estimates of the market

model. 𝐴𝑅/,1, 𝜏 = 𝑇' + 1, … . . , 𝑇", is the sample of 𝐿" abnormal returns for firm i in the event

window. The abnormal sample returns by using the market model to measure the normal return are:

𝐴𝑅/,1 = 𝑅/,1 − 𝛼/ − 𝛽/𝑅>1

When the length of the estimation window, 𝐿', becomes large the variance of the abnormal return will

be 𝜎EF" .

Second, I consider the aggregation of the abnormal returns. Cumulative abnormal return (CAR) is

needed to modify the multiple period event windows. The CAR of one of the Western European

countries from 𝑡'to𝑡" is:

𝐶𝐴𝑅 𝜏', 𝜏" = 𝐴𝑅/I

IW

IMIL

The variance of CAR is:

𝜎/" 𝜏', 𝜏" = (𝜏'−𝜏" + 1)𝜎EF"

I analyze the Cumulative Average Abnormal returns to study the different abnormal returns for all

Western European countries. The CAAR is:

𝐶𝐴𝐴𝑅 𝜏', 𝜏" =1𝑁

𝐶𝐴𝑅/(𝜏', 𝜏")Y

/M'

𝑣𝑎𝑟 𝐶𝐴𝐴𝑅 𝜏', 𝜏" = 1𝑁" 𝜎/" 𝜏', 𝜏"

Y

/M'

where N is the number of M&A announcements for each Western European country.

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Finally, I test CAAR for significance. The hypothesis for each Western European country (i) is:

𝐻(:𝐶𝐴𝐴𝑅/ = 0

𝐻':𝐶𝐴𝐴𝑅/ ≠ 0

𝐻( can be tested using:

𝜃' =𝐶𝐴𝐴𝑅 𝜏', 𝜏"

𝑣𝑎𝑟 𝐶𝐴𝐴𝑅 𝜏', 𝜏"'/" ~𝑁(0,1)

4. Results In this chapter, I present the empirical findings from the event and analyze the numbers and their

significance. Also, I answer the central research question of this thesis by rejecting or accepting the

hypothesis made in the last chapter. Furthermore, I discuss the impact of the method of payment on

stock prices.

4.1 Event study resultsAfter applying the event study methodology by MacKinlay (1997), I calculated the Cumulative

Average Abnormal Returns (CAAR) for all Western Europe countries with different event windows.

In this research, I used the Erasmus Event Study Tool and made further calculations with Microsoft

Excel. I report the CAARs of the acquiring countries for the period 2010-2017 and their significance

in Table 1 below. Figure 3 illustrates a plot for the whole sample.

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Table 1: CAARs of Western European countries for event windows [-10,10], [-5,5], [-2,2] and [-1,1]. ***, ** and *

denote significance at the 1%, 5% and 10% levels, respectively.

Country Number of

observations

CAAR [-10,10] CAAR [-5,5] CAAR [-2,2] CAAR[-

1,1]

Austria 1 -0.0177

-

-0.0207

-

-0.0221

-

-0.0131

-

Germany 6 -0.0329

(-1,0288)

-0.0154

(-0,7319)

0.0031

(0,1711)

-0.0048

(-0,2936)

Denmark 5 -0.0315

(-0,8534)

-0.0526*

(-1,8585)

-0.0351

(-1,13170)

-0.0234

(-0,9789)

Spain 3 0.0431

(-0,0237)

0.0538

(1,4005)

0.0623

(1,3305)

0.0567

(1,2033)

Falkland

Islands (GB)

1 -0.0237

-

-0.0527

-

-0.0274

-

-0.0270

-

France 24 -0.0248**

(-1,7973)

-0.0189*

(-1,4723)

-0.0113

(-1,1908)

-0.0076

(-0,9858)

United

Kingdom

16 -0,0450

(-0,3915)

-0,0388

(-0,3747)

-0,0303

(-0,4157)

-0,0254

(-0,4233)

Greece 2 -0,4925

(-0,7200)

-0.0796

(-0,3012)

0.1089

(0,7420)

0.0120

(0,1473)

Ireland 1 0.0121

-

0.0095

-

-0.0251

-

-0.0217

-

Italy 6 0.0397

(1,0722)

0.0470

(2,1651)

0.0205

(0,8725)

0.0135

(0,5543)

Netherlands 5 -0.1267**

(-2,4978)

-0.0716

(-0,6927)

0.0188

(0,1999)

-0.0384

(-0,9207)

Norway 1 -0.0032 0.0330 -0.0320 -0.0288

Switzerland 10 -0.0419

(-1,1603)

-0.0202

(-1,0187)

-0.0140

(-0,6835)

-0.0043

(-0,2475)

Western

Europe

81 -0.0416***

(-3,3417)

-0.0214**

(-2,3083)

-0.0066

(-0,8808)

-0.0097**

(-1,8230)

17

Figure 3: CARs of Western European countries for event window: [-10,10]

As a result, Table 1 shows that I reject the null hypothesis, the Cumulative Average Abnormal

Returns is zero, for Denmark, France and the Netherlands at 10% significance level. Investors owning

shares in acquirer firms from France and Denmark for a period starting five days prior the event day

and selling their shares after five days of the event day would receive a significant negative return of

2% and 5%, respectively. Also, I reject the null hypothesis that there is no effect of the CAAR at 5

percent significance level for France and the Netherlands over a 10-day event window centered

around the event day. The statistically significant CAAR amounts to -2% for France. The price

reactions for the bidding firm’s shareholders in the Netherlands are large: Table 1 shows a significant

negative CAAR of 13%. These results indicate that the announcement of a merger or acquisition

generates a loss for the acquirer shareholders in Denmark, France and the Netherlands.

However, the CAAR of the residual countries and different event windows is not proven

significant at 1%,5% or 10%. Thus, I cannot reject H( for the remaining countries. There is no effect

of the Cumulative Abnormal Average Return at every significance level. Thus, shareholders of

acquiring firms in the residual countries do not lose or gain.

Also, there is a significant decrease in Western European acquirer share prices over 10-day, 5-day and

1-day window centered around the event day: -4% at 1% significance level, and -2% and -1% at 5%

significance level. Thus, M&A announcements destroyed the wealth of bidding firm’s shareholders in

Western Europe. The results are in line with the literature from Walker, (2002); Mitchell and Stafford,

(2000); Akbulut and Matsusaka, (2010); Healy et al., (1992). Though, the result is not proven

significant for the event window two days before and after the event day.

Additionally, Figure 3 demonstrates a positive abnormal return of 4% for all Western

-0,8

-0,6

-0,4

-0,2

0

0,2

0,4

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10

CumulativeAb

norm

alReturn

DaysAustria Germany Denmark Spain

FalklandIslands France UnitedKingdom Greece

Ireland Italy Netherlands Norway

Switzerland WesternEurope

18

European companies on the event day. Therefore, the announcement of a takeover bid gives positive

abnormal returns for the acquirer shareholders in Western Europe.

4.2 Impact of the method of payment Furthermore, I examine the impact of the method of payment in an acquisition. The method of

payment affects the quality of the target firm. The managers of a bidding firm prefer to finance the

acquisition with cash when they believe that the actual value of their firm’s stocks is overvalued.

The acquisition of TSB Banking Group PLC by Banco de Sabadell SA is an entirely cash

financed offer in our sample. In contrast, the acquisition of Delhaize Group SA by Koninklijke Ahold

NV is an all-equity bid.

Figure 4: Cumulative Abnormal Return of Koninklijke Ahold NV for event window: [-10,10]

Figure 5: Cumulative Abnormal Return of Banco de Sabadell SA for event window: [-10,10]

-0,04

-0,03

-0,02

-0,01

0

0,01

0,02

-10 -8 -6 -4 -2 0 2 4 6 8 10

CumulativeAb

norm

alReturn

Days

KONINKLIJKEAHOLDNV

KONINKLIJKEAHOLDNV

-0,08

-0,06

-0,04

-0,02

0

0,02

0,04

0,06

-10 -8 -6 -4 -2 0 2 4 6 8 10

CumulativeAb

norm

alReturn

Days

BANCODESABADELLSA

BANCODESABADELLSA

19

Figure 4 and 5 above support my expectations mentioned in the literature review: the CAAR of Banco

de Sabadell SA in a twenty-one event window, ten days before the announced date and ten days after,

increases with 6% and the CAAR of Koninklijke Ahold NV in the same event window, decreases

with 11%. The all-equity bid from Koninklijke Ahold NV generates a negative price correction and

the share price of Banco de Sabadell SA increases with an all-cash bid.

These acquisitions could argue the different CAARs of Spain (4%) and the Netherlands

(-13%). The positive (negative) price reaction to bids participating in cash (equity) confirms that the

market believes that cash (equity) payments send a signal that the bidding firm is undervalued

(overvalued).

Figure 6: Cumulative Abnormal Return with different methods of payment for event window [-10,10]

Figure 6 shows how the market responds to the announcement of M&A transactions for acquiring

firms by the method of payment used in the transaction: all-cash bid, all-equity bid and a combination

of cash, debt and stock bid. The sample consists of 20 all-equity bids, 21 all-cash bids and 24 bids

with a combination of cash, debt and stock. From the residuary transactions, the deal method of

payment is unknown.

The CAAR of the all-equity bids in the sample is -8.67% and the CAAR of the combination

of cash, debt and stock bid is -2.52%. Thus, the market thinks that payments with equity give a signal

that the bidding firm is overvalued. This corresponds to the prediction I made earlier. A negative price

correction takes place for all-equity bids and bids with equity involved. However, the CAAR of the

all-cash bids is -2.27% and this is not in line with the expectations. The share price of the bidding firm

should increase with an all-cash bid.

-0,03

-0,025

-0,02

-0,015

-0,01

-0,005

0

0,005

0,01

0,015

-10 -8 -6 -4 -2 0 2 4 6 8 10

CumulativeAb

norm

alReturn

Methodofpayment

All-equitybid

All-cashbid

Combinationofcash,debtandstockbid

20

5. Conclusion In this study, the main purpose was investigating the short-term shareholder wealth effect that arises

from mergers and acquisitions. This thesis concentrates on 81 M&A announcements from Western

Europe in the period from 2010 till 2017. The focus lay on the wealth effect of shareholders from the

bidding firm. To investigate this wealth effect, I implemented the event study described by

MacKinlay (1997).

This thesis demonstrates that for the total sample of 81 M&A announcements in Western Europe the

Cumulative Average Abnormal Returns are statistically significantly below zero over a 10-day, 5-day

and 1-day window centered around the event day. A CAAR below zero means that the shareholders of

acquiring firms lose when the company is involved in mergers and acquisitions activity. As well, it is

statistically significant that an M&A announcement destroys wealth for acquiring shareholders in

Denmark, France and the Netherlands.

The period of this research lies between 2010 and 2017; this is different from the fifth merger

wave. However, the results are similar, acquisition announcements in the fifth merger wave were also

costly for acquiring firm shareholders (Moeller et al., 2005).

The negative benefits imply that managerial hubris and the agency motive restrict the bidding

firm’s shareholders to experience significant positive abnormal returns for the period between 2010

and 2017, which is considered to be the seventh merger wave.

Further, the method of payment gives an import signal of the quality of the target firm. In the results,

a negative price correction takes place for all-equity bids and bids with a combination of cash, debt

and stock. The negative price correction is in line with the predictions. Nevertheless, the share price of

the bidding firms is expected to increase with all-cash bids and in this thesis, this is not the case. A

negative price correction takes place for all-cash bids.

In summary, this thesis contributed to the existing research due to further evidence on the creation of

short-term shareholder wealth effects expected by M&A activity. More importantly, for Western

European bidding shareholders. I fulfilled a gap in the existing empirical research.

21

6. Discussion There are some limitations to this study; the first one is the size of the sample. The sample consists

only of 81 announcements which are a severe limitation of this research. Therefore, not all results are

statistically significant. The reason for the limited number of announcements comes from the criteria I

set for collecting the data out of Zephyr. Focus on continental Europe instead of Western Europe

could be a suggestion. Also, only completed deals were a criterion for the sample. Including

transactions with less than 100% acquisitions can be interesting as well.

Second, in this thesis, I only use the announcements dates from Zephyr. Possible leakages or

pre-announcements from firms could have influenced the stock prices before the official

announcement date of the deal.

Lastly, I focus specifically on the short-term wealth effects and not on the long-term

announcement effects. Event windows that span years around the announcement date would be an

interesting future topic to examine long-term performance of firms. Long-term performance of firms

could give interesting evidence about the gains of mergers and acquisitions for the whole company on

the long-term, which is just as important for the shareholders.

22

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25

8. Appendix Appendix1:SampleM&Aannouncements.Source:Zephyr

DealNumber Acquirername Acquirer

country

code

AcquirerISIN

number

Announceddate

90. 1909166258 UBMREALITATENENTWICKLUNG

AG

AT AT0000815402 2014-10-29

8. 1601410550 COCA-COLAHBCAG CH CH0198251305 2012-10-11

40. 1909489321 DEUTSCHEPOSTAG DE DE0005552004 2016-09-28

57. 1909422043 EVOTECAG DE DE0005664809 2016-10-26

7. 1909067843 VOLKSWAGENAG DE DE0007664039 2014-02-21

91. 1909255076 VOLKSWAGENAG DE DE0007664039 2015-07-03

49. 1909116343 ERGOVERSICHERUNGSGRUPPE

AG

DE DE0008418526 2014-08-14

89. 1909102696 MUTARESAG DE DE000A0SMSH2 2015-04-29

28. 1909260193 TELECOLUMBUSAG DE DE000TCAG172 2015-07-16

10. 1909119261 TUIAG DE DE000TUAG000 2014-09-15

75. 1601242849 VESTJYSKBANKA/S DK DK0010304500 2012-03-27

42. 1909154587 NORDJYSKEBANKA/S DK DK0060034353 2014-12-18

69. 1909016292 SVENDBORGSPAREKASSEA/S DK DK0060520377 2013-11-06

35. 1601443062 ROYALUNIBREWA/S DK DK0060634707 2013-07-11

68. 1601478991 SPAREKASSENSJÆLLAND DK DK0060670776 2013-06-24

52. 1909200306 WILLIAMDEMANTHOLDINGA/S DK DK0060738599 2015-09-30

51. 1909089744 AMADEUSITHOLDINGSA ES ES0109067019 2014-04-03

14. 1909209484 BANCODESABADELLSA ES ES0113860A34 2015-03-20

87. 1601492405 BARGELDSICAVSA ES ES0114219035 2013-06-21

92. 1909392916 FINECOEUROCARTERASICAVSA ES ES0138202033 2015-12-28

85. 1601386414 INVERMAYSICAVSA ES ES0155887039 2012-06-26

73. 1601075552 RENTA4SERVICIOSDE

INVERSIÓNSA

ES ES0173358039 2011-02-07

15. 120266 INTERNATIONALCONSOLIDATED

AIRLINESGROUPSA

ES ES0177542018 2010-04-08

56. 1909026575 FALKLANDOIL&GASLTD GB FK00B030JM18 2013-10-03

41. 1601461067 FONCIEREDEPARISSIICSA FR FR0000034431 2013-07-30

43. 1909297663 MAUREL&PROMSA FR FR0000051070 2015-10-16

31. 1909106492 ATOSSE FR FR0000051732 2014-05-26

81. 1909182646 BOISSETLAFAMILLEDESGRANDS

VINSSAS

FR FR0000060766 2015-07-07

78. 1601376491 FONCIEREDESREGIONSSA FR FR0000064578 2012-08-03

55. 1601376805 AIRLIQUIDESA FR FR0000120073 2012-09-04

26

13. 1601282800 CARREFOURSA FR FR0000120172 2011-07-01

97. 1909277294 CARREFOURSA FR FR0000120172 2016-01-01

33. 1909165597 IMERYSSA FR FR0000120859 2014-11-05

47. 1601265888 EURAZEOSA FR FR0000121121 2011-04-26

5. 1909129040 KLEPIERRESA FR FR0000121964 2014-10-27

63. 1601442578 KLEPIERRESA FR FR0000121964 2013-01-31

2. 529205 UNIBAIL-RODAMCOSE FR FR0000124711 2007-05-21

37. 1601277973 CAPGEMINISA FR FR0000125338 2011-07-29

21. 1601354921 CASINOGUICHARD-PERRACHON

SA

FR FR0000125585 2012-07-27

34. 1909441158 VIVENDISA FR FR0000127771 2016-05-19

96. 1909248479 SOCIETEGENERALESA FR FR0000130809 2015-06-18

11. 1909017091 ORANGESA FR FR0000133308 2014-09-15

62. 1601187879 DAMARTEXSA FR FR0000185423 2010-05-12

86. 1601439593 NETGEMSA FR FR0004154060 2013-02-06

70. 1601411751 EXELINDUSTRIESSA FR FR0004527638 2012-10-16

53. 1909094365 BIOALLIANCEPHARMASA FR FR0010095596 2014-04-16

17. 1601261570 ELECTRICITEDEFRANCESA FR FR0010242511 2011-04-08

23. 1909430553 FNACSA FR FR0011476928 2016-04-25

80. 1601287964 BIOMERIEUXSA FR FR0013280286 2011-07-22

6. 1909170808 AVIVAPLC GB GB0002162385 2014-12-02

36. 1909448363 RPCGROUPPLC GB GB0007197378 2016-06-09

83. 1601305562 SOUTHSTAFFORDSHIREPLC GB GB0034321611 2011-10-04

54. 1909213872 NCCGROUPPLC GB GB00B01QGK86 2015-03-24

1. 1909218355 ROYALDUTCHSHELLPLC GB GB00B03MM408 2015-04-08

79. 1909247899 1SPATIALPLC GB GB00B09LQS34 2015-06-18

74. 1601056363 DEBENHAMSPLC GB GB00B126KH97 2009-11-12

65. 1909168573 INTERNATIONALPERSONAL

FINANCEPLC

GB GB00B1YKG049 2014-12-19

32. 1909098515 OPHIRENERGYPLC GB GB00B24CT194 2014-11-24

61. 1601227480 DAISYGROUPPLC GB GB00B61G9L20 2010-11-10

26. 1909204074 JUSTRETIREMENTGROUPPLC GB GB00BCRX1J15 2015-08-11

44. 1909225891 CIRCASSIAPHARMACEUTICALS

PLC

GB GB00BJVD3B28 2015-05-15

60. 1909168593 PARAGONOFFSHOREPLC GB GB00BMTS0J78 2014-12-19

76. 1909204311 VOLUTIONGROUPPLC GB GB00BN3ZZ526 2015-11-11

20. 1601072848 VIRGINMONEYHOLDINGS(UK)

LTD

GB GB00BQ8P0644 2011-11-17

16. 1909155157 NEWSTERISLTD GB GB00BVVBC028 2014-10-13

12. 1909203985 LIVANOVAPLC GB GB00BYMT0J19 2015-03-24

59. 1601468297 JOHNSONMATTHEYPLC GB GB00BZ4BQC70 2012-10-22

27

46. 1601407695 ALPHABANKAE GR GRS015003007 2012-10-17

30. 1909000009 EUROBANKERGASIASSA GR GRS323003012 2013-07-15

9. 1909162340 PERRIGOCOMPANYPLC IE IE00BGH1M568 2014-11-06

66. 1909504502 DOBANKSPA IT IT0001044996 2016-07-14

48. 1601396658 HERASPA IT IT0001250932 2013-01-02

25. 1601222116 PRYSMIANSPA IT IT0004176001 2011-01-05

72. 1601342021 KMEGROUPSPA IT IT0004552359 2012-05-09

94. 1601431743 FONDIARIA-SAISPA IT IT0004827447 2012-12-20

95. 1601431764 FONDIARIA-SAISPA IT IT0004827447 2012-12-20

88. 1601492745 INDUSTRIALSTARSofITALYSPA IT IT0004938707 2015-01-26

18. 1909266393 DELPHIAUTOMOTIVEPLC GB JE00B783TY65 2015-07-30

27. 1601061248 KONINKLIJKEBOSKALIS

WESTMINSTERNV

NL NL0000852580 2010-02-24

71. 1909035317 FORNIXBIOSCIENCESNV NL NL0010627865 2013-12-06

82. 1601201346 GRANDVISIONNV NL NL0010937066 2010-07-06

4. 1909401312 MYLANNV NL NL0011031208 2016-02-10

3. 1909231252 KONINKLIJKEAHOLDNV NL NL0011794037 2015-06-24

64. 1909432671 R&SRETAILGROUPNV NL NL0012047849 2016-09-15

67. 1601401978 AKERSEAFOODSHOLDINGAS NO NO0003052615 2012-09-11

77. 1601443885 AUSTEVOLLSEAFOODASA NO NO0010073489 2013-03-05

58. 1909111291 ACANDOAB SE SE0000105116 2014-06-09

22. 1909063234 SSABAB SE SE0000171100 2014-01-22

19. 1909412445 CASTELLUMAB SE SE0000379190 2016-04-13

84. 1601372682 PARTNERTECHAB SE SE0000394165 2012-05-23

38. 1909239709 SWECOAB SE SE0000489098 2015-06-01

29. 1601314133 SANDVIKAB SE SE0000667891 2011-11-07

45. 1909298716 CATENAAB SE SE0001664707 2015-10-20

39. 1601412627 AFAB SE SE0005999836 2012-10-18

24. 1601212361 PANDOXAB SE SE0007100359 2010-10-21

50. 1909437545 KAROPHARMAAB SE SE0007464888 2016-11-01

93. 1909517350 ADDLIFEAB SE SE0007982814 2016-12-07