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“Mergers and Acquisitions in the financial sector”

Do mergers & acquisitions that have been completed in

the period 2001-2005 in the financial sector in Europe

create value for the acquiring firms?

Bachelor Thesis Finance

Name: Wouter Schreurs

ANR: 850024

Supervisor: N.R.D. Dwarkasing

Date: May 16th 2011

Program: International Business Administration

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Table of Contents

1. Introduction 3

2. Why do firms undertake M&A’s? 6

2.1 Introduction 6

2.2 Synergy benefits of M&A’s 6

2.3 Managers’ benefits of M&A’s 8

2.4 Why banks are special in M&A’s 9

2.5 Conclusion on motives for M&A’s 10

3. Do M&A’s create value? 12

3.1 Introduction 12

3.2 Overview of earlier research 12

3.3 Conclusion on previous research 15

4. Data Analysis 17

4.1 Methodology 17

4.2 Data 19

4.3 Results 20

5. Conclusion 23

5.1 Conclusion 23

5.2 Limitations 24

5.3 Future research 24

6. References 25

7. Appendix 27

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1: Introduction

The total number of transactions and the total deal value of mergers and acquisitions worldwide

have grown enormously in the last 25 years. In the year 1985 the total number of transactions

was about 3,500 with a total transaction value of $ 0.5 trillion. Since then these numbers have

been growing fast and a peak occurred in 2007 (before the financial crisis) with about 47,000

transactions with a total deal value of $ 5.8 trillion. The ten largest merger and acquisition deals

that have occurred in the period 1998-2007 have a total combined deal value of € 919 billion1

(not corrected for inflation) and the total deal value of mergers and acquisitions in only the

financial sector for 2008 was $ 161.6 billion.2 In comparison, the total Dutch government‟s

spending in 2010 was € 272.1 billion.3 So clearly large amounts of money go in to mergers and

acquisitions (M&A‟s), yet there are many academic papers that state that most of these mergers

and acquisitions are not successful in terms of creating value for the shareholders. So there is a

lot of money being spent on mergers and acquisitions although, according to various academic

papers, most of the time value is destroyed; Grubb & Lamb (2000) find that only 20% of all

M&A‟s that take place is successful in terms of recovering the cost made in the deal. However

there are many other studies that show opposite results and show that mergers and acquisitions

do create value for the acquiring firms. So the research question that is going to be answered in

this bachelor thesis is:

Do mergers & acquisitions that have been completed in the period 2001-2005 in the financial

sector in Europe create value for the acquiring firms?

An example of an unsuccessful acquisition is the takeover of ABN Amro by Royal Bank of

Scotland, Fortis and Banco Santander. This was the biggest banking takeover ever and the total

deal value was over $ 100 billion. But after this takeover the three acquiring firms had to raise

massive amounts of new capital, faced high write-downs and saw their stock prices plummeting.4

1 http://www.imaa-institute.org/statistics-mergers-acquisitions.html

2 http://www.reuters.com/article/2010/04/08/us-financial-ma-outlook-idUSTRE63738P20100408

3 http://www.rijksbegroting.nl/2010/voorbereiding/miljoenennota,kst132844_1.html

4 http://www.marketwatch.com/story/the-curse-of-the-abn-amro-acquisition

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On the other hand, a successful acquisition in 2005 was the takeover of Android by Google.

Google bought this company for $ 50 million5 and the mobile operating system Android is now

market leader in the smartphone market with a market share of 31.2 % in the US.6 Besides that,

Google forecasts that Android will generate $ 10 billion in revenues annually.7

According to Stefanowski (2007) a merger is: “The combination of two companies/legal entities

into one. This normally occurs in situations where two companies of similar size and

characteristics agree to combine efforts” and control of the new merged firm is distributed

relatively equally between the two merging firms.

An acquisition is according to Stefanowski (2007): “The 100 percent purchase by one company

of another. The target company is normally absorbed by the acquirer and no longer exists as a

separate entity after the deal closes” and here the control is for the largest part in the hands of the

acquiring firm.

The difference between a merger and an acquisition is that in a merger two similar companies in

terms of size and other characteristics merge in to one company, while in an acquisition there is

one (larger) company that is leading which absorbs the target company and this leading firm has

more control than the firm that is taken over. But the principle of both a merger and an

acquisition are similar: two companies combine to form one company.

This chapter has been an introduction to mergers and acquisitions with definitions, some facts

and numbers and the following description of how the structure of this bachelor thesis will be.

The second chapter will be a literature review on why firms undertake mergers and acquisitions

in which different reasons (other reasons than creating shareholder value) for M&A‟s will be

highlighted based on previous academic literature. Chapter two will also describe why M&A‟s

for banks are special compared to other industries.

The third chapter will also be a literature review which will summarize various papers that find

that mergers and acquisitions do create value and on the other hand papers that find that M&A‟s

5 http://www.techspot.com/news/40905-google-android-acquisition-was-best-deal-ever.html

6 http://theflickcast.com/2011/03/10/android-mobile-os-now-number-one-in-u-s-market-share/

7 http://www.fiercemobilecontent.com/story/googles-schmidt-forecasts-annual-android-revenues-top-10b/2010-07-29

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destroy value (for the acquiring firm) and see what the overall view on M&A‟s in the financial

sector is.

The forth chapter will be the data analysis part in which data will be analyzed to see whether

mergers and acquisitions have created value in the period 2001-2005 by calculating the

cumulative average abnormal returns for different event windows.

In the fifth and final chapter a conclusion is given, the limitations of this study are highlighted

and possibilities for future research are given.

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2 Why do firms undertake M&A’s?

2.1 Introduction The focus of this bachelor thesis is mainly on the shareholder value creation aspect of mergers

and acquisitions as the main research question studies whether mergers and acquisitions create

value for the acquiring firm in terms of share price increase. However, besides a higher share

price and thus a higher return for the firms‟ shareholders there are some other reasons why firms

undertake mergers and acquisitions. The main reason why firms undertake a merger or an

acquisition however still remains value creation, but not just for the shareholders. The two

companies that will become one should be worth more than if they stayed separate, so the sum of

the two combined parts should be larger than the two parts on their own. This is called synergy

and will be explained further in the following section. After that other motives of why the

management of a firm undertakes a merger or an acquisition are highlighted that do not only

include one of the above mentioned motives, but have to do with the fact that managers can

personally profit from working for a larger company in terms of their compensation. In the fourth

part of this chapter it will be examined why mergers and acquisitions in the financial sector, and

particularly in banking, are special. If a bank becomes large enough it obtains a too big to fail

status and this comes with several advantages that will be discussed in section 2.4. Also in

section 2.4 the impact of competition regulation in the banking sector is briefly discussed.

Finally an overview is given of what is discussed here in chapter 2 which will summarize why

firms undertake mergers and acquisitions.

2.2 Synergy benefits of M&A’s According to Sirower (1997) the definition of synergy is the following: “Synergy is an increase

of competitive power and the resulting cash flows are larger than the expected cash flows of the

individual companies”. A merger of two companies is only successful, according to Sirower

(1997), when the synergy is larger than the cost of the merger and the premium paid. A

distinction can be made between horizontal and vertical mergers and the resulting efficiency

gains differ among the two. A horizontal merger of two companies is that two relatively similar

companies become one, so for instance two banks (ING & Fortis) merge. This gives the

combined firm several advantages like economies of scale (for instance if there are two bank

offices in one town, one office can be closed), larger financial possibilities and possibly the

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replacement of inefficient management. The replacement of inefficient management is supported

by the market discipline hypothesis that implies that firms with poor corporate government have

lower market values and are taken over by higher valued bidders. This market discipline

hypothesis is supported by the finding of Jensen and Ruback (1983) who find that acquisitions

can help to protect shareholders from bad management. Agrawal and Walking (1994) also find a

similar result that CEO‟s are often fired or see their salaries reduced after being taken over.

For vertical mergers the synergy advantages are more in terms of cutting out the middle man so

margins can increase because the firm owns a larger part of the supply chain (Sirower, 1997).

Rime and Stiroh (2003) examine efficiency improvements in Swiss banks that have merged or

that acquired another bank, and they find evidence for small and medium size banks that those

indeed profit from synergies in term of economies of scale. They used a sample of 289 Swiss

banks and looked at mergers and acquisitions in the period 1996 until 1999 and compared

variable profit and costs functions of banks of different sizes. Swiss banks gain in efficiency up

until size category 8 (out of 10). If they become larger than scale 8 their efficiency goes down.

However there are some limitations to this research since Switzerland is a relatively small

country and this research may not be representative for other European countries, but it is at least

a first indication of synergy benefits in bank M&A‟s.

In the paper of Devos, Kadapakkam and Krishnamurthy (2008) it is examined where synergy

gains from a merger actually come from, since there is little similar research in that particular

area. Previous work does show where the gains come from (taxes, market power and efficiency),

but does not address the relative importance of the synergy gains. Devos et al. (2008) investigate

a sample of 264 large mergers and find that the average gains are 10.03 % of the combined

equity value of the two firms. From this percentage 1.64 percent point can be dedicated to tax

gains that arise from the merged firm and operating synergies account for 8.38 percent point of

the total synergy gains.

A relatively similar research has been executed by Houston, James and Ryngaert (2001) but they

focus only on the banking sector instead of all sectors in the economy as done by Devos et al.

(2008). Houston et al. (2001) try to find out where merger gains in the banking sector come from

and look at 41 large (> $ 400 million) mergers between 1985 and 1996. They find that cost

savings are highly correlated to geographical overlap of the two merging banks, and also they

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show that merged banks slightly improve their efficiency and return on assets (ROA) compared

to the pre-merger figures.

As shown by the papers that are discussed in this section it appears that there are indeed synergy

advantages that companies can achieve by undertaking a merger or an acquisition. Also for the

financial sector in specific synergy benefits can be achieved in terms of cost savings and

operating improvements.

2.3 Managers’ benefits of M&A’s As described in the introduction of this chapter the benefits for managers of firms that undertake

a merger or an acquisition will be highlighted in this section. The first benefit for managers is

that when their company takes over another company, the size of the merged companies will

increase. When management tries to increase the size of the firm via M&A activity, despite the

fact that it does not necessarily creates value for the firms‟ shareholders, this is known as empire

building (Bösecke, 2009). By empire building managers try to maximize their own utility

(Trautwein, 1990). Anderson, Becher and Campbell (2004) show in their paper that CEO

compensation (salary and bonus) is positively related to the size of a firm. Since the size of a

firm always increases with a merger, even though the acquisition or merger in itself does not

create value for the shareholders, the CEO (and management) often benefit personally from the

takeover. Anderson et al. (2004) use a sample of 337 banks from the period 1990 until 1997 to

find that CEO compensation increases on average with 12.0 % while the abnormal return for the

acquiring firm is on average – 1.12 %. However the combined returns of the acquirer and the

target are positive so it does appear that in general large banking mergers and acquisitions create

value, but not for the acquiring firm.

Similar findings have been observed by Bliss and Rosen (2001) who also find a positive

relationship between mergers and CEO compensation in their sample of 32 banks for the period

1985 until 1995. This relationship comes mainly from the increased size of the bank, through

which compensation increases. In their analysis they split up their sample in two groups: high-

merger and low-merger. In the high-merger group they place companies that undertook the most

mergers and acquisitions, and vice versa. The „High Group‟ shows a 19.7 % larger increase in

aggregate (over 9 years) total compensation.

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Hadlock, Houston and Ryngaert (1999) compare a sample of 84 banks that are successfully taken

over to 84 banks that have not been acquired and compare among others ownership structure

between the two datasets. They find that a higher level of ownership reduces the probability that

a bank is acquired. Hadlock et al. (1999) indicate this as when management owns a large block

of shares they want a fair value for it in a takeover, and this can be interpreted that when

management has less shares they care less about getting a good price.

Since managers with little ownership care less about the price that is offered for their company in

a takeover, it appears that managers (sometimes) use M&A‟s (empire building) for their own

benefit, rather than creating value for the shareholder. In a merger or an acquisition the firm size

increases, and firm size is directly related to CEO compensation as can be seen in the above

paragraphs.

2.4 Why banks are special in M&A’s Besides value creation for shareholders, synergy benefits and increase of management

compensation there is another important reason for why firms undertake takeovers. This reason

is mainly valid for the banking industry, because this industry is vital for the economy by

providing liquidity to other businesses and that is why governments bail out banks when it is

needed during an economic crisis (for instance: credit crisis 2007) when they are „Too Big to

Fail‟ (TBTF). The implicit guarantee given by governments reduces financing cost of very large

banks (Kane, 2000) and stimulates smaller banks to undertake M&A‟s to grow large enough in

order to achieve the TBTF status.

O‟Hara and Shaw (1990) perform an event study in which they compare TBTF banks to banks

that do not have this status using an event window of eleven days (-5 , 5) where 0 is an article in

the Wall Street Journal (WSJ) that lists these TBTF banks. They find „positive wealth effects‟

related to the TBTF group and after the article in the WSJ was published share prices of the

TBTF banks increased on average with + 1.31 % while the other banks that were not on the list

on average decreased with – 0.16 %. Lazarus and Saunders (1997) use the same WSJ bank list of

eleven banks but reduce this list to nine banks in their analysis and find that the cost of capital of

banks indeed is reduced by the implicit government guarantees about deposit insurance.

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It is clear that it can be a big advantage for banks to achieve the „Too Big to Fail‟ status. This

status brings several advantages that come from the implicit government deposit guarantees that

any TBTF bank will be bailed out in a crisis or other similar circumstance. This reduces the

financing costs and when an article with a list of TBTF banks was published share prices of the

TBTF banks increased significantly compared to not-TBTF banks. The TBTF status is thus one

of the reasons why banks undertake mergers and acquisitions, and is one of the „special‟ features

of the banking industry.

A study of Carletti, Hartmann and Onega (2007) also investigates why banks are special, but

looks at a legislative point of view of competition policy. In their study they examine the

cumulative abnormal returns of banks versus non-financial institutions when legislation changes

in competition policy are announced for the period 1987 until 2004. In their dataset of 19

industrial countries they find that the stock prices of banks react positively on the announcement

of stricter competition policy, while share prices of other firms react negatively to strengthening

of competition policy. An explanation for the positive interpretation of stricter competition rules

in banking that Carletti et al. (2007) find are obtained by regressing the cumulative abnormal

returns (CAR‟s) on several variables. They find that the opaqueness in bank mergers explains

this effect since bank mergers are subject to reviews by supervisory authorities.

A study on bank merger regulation by Köhler (2009) finds that the number of cross-border bank

mergers within Europe is still smaller than the amount of domestic bank mergers. According to

Köhler there are several reasons for this. One of these reasons is the difference in regulation

between countries which reduces synergy benefits since banks have to comply with different

regulations after a cross-border merger. Also cross-border bank mergers can be restricted by

market entry barriers such as ownership limits for foreign investors which often restrict or

prohibit bank mergers or acquisitions. These entry barriers and efficiency barriers are according

to Köhler the main reasons why there is a limited number of cross-border M&A deals in the

European banking sector.

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2.5 Conclusion on reasons for M&A’s As discussed in this chapter firms can have several reasons to undertake a merger or an

acquisition. The most common reason is value creation for shareholders. In chapter 3 this reason

will be examined in more detail. A second reason for firms to undertake M&A activities are

synergy benefits that arise in a merger or an acquisition, such as cost reductions, economies of

scale and improved efficiencies which lead to improved operating performance. Another reason

why managers choose to undertake a merger or an acquisition is that they can benefit personally

from this. If their firm increases in size, CEO compensation also tends to increase significantly.

And the last reason for mergers and acquisitions discussed in this chapter, which is valid

especially for the banking sector, is for banks to obtain the Too Big to Fail status. This TBTF

status mainly holds for the banking industry where governments give implicit guarantees that

they will not let the largest banks go bankrupt, thus reducing their cost of capital and increasing

their value. Also stricter competition policy combined with supervisory review for bank mergers

have positive effects on the stock prices of banks, but due to regulation differences and

restrictions between countries within Europe the number of cross-border M&A‟s is relatively

low.

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3 Do M&A’s create value?

3.1 Introduction A lot has been written about the possible shareholder value creation of mergers and acquisition

in general, but there is also a large amount of academic literature about the financial sector (and

banking) in specific. In this chapter an overview of several of these papers will be presented and

a distinction will be made between M&A‟s in general and financial M&A‟s.

There are several ways through which value creation can be measured but in the literature the

two main categories are value creation based on change in operating income and value creation

based on changes in share prices. In the data analysis part of this bachelor thesis value creation

will be examined using share price data as a measure, so also in this chapter only papers that use

change in share price as a performance measure will be discussed. According to the Efficient

Market Hypothesis (EMH) financial markets are informationally efficient. This means that when

new information about a company comes out this is immediately priced in the share price. So

when an M&A deal is announced this should be observable in stock prices immediately so the

event windows can be relatively short.

The final distinction that is made in literature is the time period over which the abnormal returns

are calculated. In various papers there is a difference between short term performance (less than

one year) and long term performance (more than one year), and this distinction will also be made

in this chapter. The most important of the two is short term since this is also what will be

examined in the data analysis part of chapter 4.

3.2 Overview of earlier research A study of Gross and Lindtstad (2005) that examines several industries in Europe and the United

States makes the distinction between horizontal and vertical mergers and acquisitions. In the

financial sector they find an average cumulative abnormal return (CAAR) for bidding firms of +

1.74 % for the period January 1th 1998 until August 31th 2001 (62 observations) and the event

study window is four days (-2 , 1). When distinguishing between horizontal and vertical M&A‟s

they find a negative return of - 2.08 % for horizontal M&A‟s and for the vertical M&A‟s the find

a positive return of + 2.12 %. They explain that the negative returns for horizontal M&A‟s are

caused by imprudent management decisions.

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Mulherin and Boone (2000) examine wealth effects of mergers and acquisitions for bidding

firms and target firms and examine the period 1990 until 1999 which gives them a sample of 376

targets and for 281 of these observations data about the bidder is also available. They use an

event window of three days (-1 , 1) and Mulherin and Boone find an average abnormal return

(AAR) for the target firms of + 21.20 % and a negative return for the bidder of – 0.37 %. This

small negative AAR for bidding firms is “interpreted as reflecting a competitive market for

corporate control”.

Mitchell and Stafford (2000) examine the long term performance of acquiring firms and use a

sample of 366 US firms in order to come to an average negative abnormal return of – 5.04 % in

the three years after the event date and the negative returns are mainly caused by stock issues to

pay for the acquisitions. The period over which the data is collected is from 1958 until 1993. A

comparable study is that of Lougran and Vijh (1997) who study 947 acquisitions during the

period 1970 until 1989 and they find an abnormal return for acquiring firms of – 6.5 % for the

period of 5 years. Again when making the distinction between paying in stock or cash they find

that returns when paying in stock are lower.

In the study of Paul Asquith (1983) he examines mergers of NYSE firms during the period July

1962 until December 1976 and Asquith makes the distinction between successful and

unsuccessful bids. Since only mergers and acquisitions that actually took place are interesting

only the successful bids will be considered. Asquith finds an average positive significant excess

return for target firms of + 15.5 % and - 0.10 % for acquiring firms for the period one day before

the press date until one day after the announcement (-1 , 1).

Jensen and Ruback (1983) examine thirteen studies that are similar to the above one of Asquith

and use those previous findings to say something about the abnormal returns of targets and

acquirers. The period over which these previous figures have been found vary between 1 and 2

months so these are short term results. For the acquiring firm they find a positive average return

of + 3.80 % and for the target firms Jensen and Ruback also find a positive average return of

+ 15.90 % when taking the weighted average of the thirteen studies.

Agrawal, Jaffe and Mankleder (1992) looked at post-merger performance of firms on the NYSE

and AMEX indices over the period 1955 until 1987 and use a sample of 937 mergers and 227

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acquisitions. They show a statistically significant negative cumulative average abnormal return

of -10.26 % for the acquiring firms in the five years after the merger was completed. Agrawal et

al. (1992) propose that the negative returns might have to do with mean reversion but do not find

significant evidence.

Kane (2000) studies the returns of acquiring and target firms in the banking sector and only takes

into consideration the fifteen largest US bank deals per year for the period 1991 until 1998 and

thus has a sample size of 120 M&A‟s. Kane finds an average excess return for target firms of +

11.14 % and for the acquiring firms he finds a negative average excess return of – 1.50 % and

combined this is + 0.83 % while using an event window of 3 days (-1 , 1).

Beitel, Schiereck and Wahrenburg (2004) study 98 large (above $ 100 million) European

banking bids during the period 1985 until 2000 and use an event window of 41 days (- 20 , 20)

and find a positive cumulative average return for targets of + 16.00 % and for acquiring firms

they find a (not significant) negative average cumulative return of – 0.20 %. The two firms

combined Beitel et al. find a positive return of + 1.29 % over the event window period.

Campa and Hernando (2006) investigate the performance of mergers of European firms in the

financial industry for the period 1998 until 2002. When looking at an event window of three days

around the announcement (-1 , 1) they find an average negative return for the acquiring firm of –

0.87 % and an average positive return of + 3.24 % for the target. When taking a longer event

window up until more than one year after the announcement (-1 , 360) they show a negative

return for the acquirer of - 3.37 %. To further investigate the negative returns for acquiring firms

Campa et al. (2006) split up the sample in cross-border vs. national deals and small vs. large

deals. Only the small deals show a larger negative return, but large deals are also still slightly

negative.

Ekkayokkaya, Holmes and Paudyal (2009) look at 963 mergers and acquisitions in the financial

sector during the period 1990 until 2004 within the Euro area and find that, for an event window

of three days (-1 , 1), on average the bidding firms‟ share price increases with + 0.121 % and for

the target firms this is on average + 0.029 %.

Cybo-Ottone and Murgia (2000) also study European banking mergers and acquisitions that

occurred between 1988 and 1997. During this period 54 deals happened and again when using a

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three day event window (-1 , 1) the average abnormal return for the acquiring firms is + 0.99 %

and for the target the average abnormal return is + 12.93 %.

Houston and Ryngaert (1994) examine stock prices of mergers and acquisitions of 153 US banks

during the period 1985 until 1991. In their analysis they find a five-day average abnormal return

(event window: [-4 , 0]) for acquiring firms of – 2.32 % and for the target firm the abnormal

return is on average + 14.39 %. These two combined show a slightly positive abnormal return of

+ 0.38 %. A possible explanation for the negative returns of bidders they give is that when the

acquisition is paid in stock this is a signal to the market that the current stock price is overvalued.

3.3 Conclusion on previous research There are many more papers that can be discussed in section 3.2 but the papers mentioned give a

good indication of the general findings that previous research on abnormal returns in mergers

and acquisition have found. When examining the short term abnormal returns of the acquiring

firms in a deal on average the return is + 0.13 % and for the long term this is – 6.29 %. When

looking at the target returns in mergers and acquisitions, on average a much higher abnormal

return of + 13.39 % is obtained. When looking at the returns of M&A‟s in the financial sector

compared to M&A‟s in general no significant differences can be seen. In Table 1 on the

following page an overview of the returns that are described in the papers discussed in section

3.2 is given.

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Table 1: Overview of returns found in academic studies

Author (Year) Bidder Short Bidder Long Target Window Finance?

Gross & Lindstad (2005) +1.74 % - - (-2 , 1) Yes Mulherin & Boone (2000) -0.37 % - +21.20 % (-1 , 1) No Michell & Stafford (2000) - -5.04 % - 3 years No Lougran & Vijh (1997) - -6.50 % - 5 years No Asquith (1983) -0.10 % - +15.50 % (-1 , 1) No Jensen & Ruback (1983) +3.80 % - +15.90 % n.a. No Agrawal et al. (1992) - -10.26 % - 5 years No Kane (2000) -1.50 % - +11.14 % (-1 , 1) Yes Beitel et al. (2004) -0.20 % - +16.00 % (-20 , 20) Yes Campa & Hernando (2006) -0.87 % - +3.24 % (-1 , 1) Yes Campa & Hernando (2006) - -3.37 % - (-1 , 360) Yes Ekkayokkaya et al. (2009) +0.12 % - +0.029 % (-1 , 1) Yes Cybo-Ottone & Murgia (2000) +0.99 % - +12.93 % (-1 , 1) Yes Houston & Ryngaert (1994) -2.32 % - +14.39 % (-4 , 0) Yes Average +0.13 % -6.29 % +13.39 %

In the first column the name(s) of the author(s) is (are) given and between brackets is the year the paper was published. In the

second column the short term (<1 year event window) return in percent is given for the bidding firm and in the third column

the long term (>1 year event window) returns are given. In the fourth column the target returns are given, followed by the

event window period in column five. In the last column six it is indicated whether the research is about financial firms in specific

(indicated by ‘Yes’) or about M&A’s in general (indicated by ‘No’).

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4: Data Analysis

4.1 Methodology

The stock performance measure that will be used in this event study to analyze the stock return

data is the abnormal return measure as described by the Tilburg University Lecture Notes from

de Jong (2007). The abnormal return is the difference between the expected return and the

actual return for stock j over time period t and this measure is based on the capital asset

pricing model (CAPM). The abnormal return can be written as the following formula:

The can be observed from daily stock data obtained from the Datastream database for the

event study windows T = [- 30 , + 30] , [- 20 , + 20] , [- 10 , + 10] , [- 5 , + 5] , [- 3 , + 3] and

[- 1 , + 1] where t = {0} is the announcement date of the merger or acquisition. The expected

return can be calculated by multiplying times the market return minus the risk free

rate and adding which leads to the following formula:

The firms‟ beta ( ) is the exposure to the market and can be calculated by the following

formula:

In order to calculate the expected returns a time span for the clean period has to be set over

which the above ingredients for beta can be calculated. As suggested by Beitel et al. (2004) a

clean period of 252 trading days (one full year) prior to the event window (-282 , -31) will be

used for this.

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The average of all the computed abnormal returns can be calculated by the following formula:

∑

To test if the AAR‟s are statistically different from zero the following test statistic is used:

√

√

∑

When is < -1.96 or > 1.96 the abnormal returns are statistically different from 0 at 5%

confidence. The critical value for a 1% confidence level is 2.36 and for a 10% confidence level is

the critical value is 1.67.

After the AAR‟s are calculated the cumulative abnormal returns (CAR) can be calculated and the

average of these per event window is called CAAR. Also for the CAAR‟s the significance level

can be calculated using the same critical values as with the AAR described above:

∑

√

√

∑

Figure 1: Event Window Time Line (in case of event window = [ -30 , 30 ])

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4.2 Data

The data that is needed to calculate the abnormal returns for acquiring firms in mergers and

acquisitions will be extracted from the SDC Platinum database. This SDC International Merger

and Acquisition database provides a list of all Mergers and Acquisitions that meet the following

criteria:

Announcement date between 01/01/2001 – 31/12/2005

Target firm US SIC code: 60, 61, 62, 63, 64, 65 & 67 (all financial firms)

Acquirer firm US SIC code: 60, 61, 62, 63, 64, 65 & 67 (all financial firms)

Acquirer and Target are Public

Acquirer and Target are located in Western-Europe

Deal status is „Completed‟ or „Unconditional‟

Percentage of share owned after transaction is > 50 %

This provides a list of 125 mergers and acquisitions, and when filtering the data further by

eliminating firms that do not have a Datastream Code (DC) the sample is reduced to 94 deals.

From these 94 deals only 77 have stock data available so the final sample size used to calculate

the abnormal returns is 77. The full list of these deals is provided in Appendix 1.

For these 77 deals the following data are needed in order to calculate the abnormal returns: stock

prices of acquiring firms for period (-282 , 30), stock data of the market index ( ) and the risk

free rate ( ).

is the return of the market index, and since we only take European financial deals into

consideration the Stoxx Europe 600 Financials index will be used as a . This index only

consist out of financial services firms, banks, insurance and real estate firms so it is a relatively

good benchmark for the dataset that only contains financial firms.

For the Euro Euro-Currency (ICAP/TR) 1-month bond rate will be taken at time t which

gives the risk free rate that can be used.

All data will be obtained from the Datastream database and will be used to calculate the

abnormal returns by first calculating the returns of the market and the stock using the natural

20

logarithm: LN ( Pt+1 / Pt ). Then the normal returns are calculated and these are subtracted from

the actual returns which will give the abnormal returns and the AAR‟s and CAAR‟s are

calculated for the various event windows.

4.3 Results

First the average abnormal returns per t are calculated for t = -30 until t = 30 and these can be

found in Table 2 below. It is also indicated whether the AAR values are statistically significant

different from 0. For all values of t the average abnormal returns are negative but only a few are

statistically significantly different from 0.

Table 2: Average Abnormal Returns

T AARt G T AARt G T AARt G

-30 -0,005218675 -1,08 -9 -0,013149021 -2,52*** 12 -0,002417660 -0,29 -29 -0,007396978 -1,47 -8 -0,007957866 -2,05** 13 -0,008610231 -1,97** -28 -0,004466159 -0,80 -7 -0,003852090 -0,81 14 -0,003597730 -0,72 -27 -0,005371252 -0,90 -6 -0,003868811 -0,74 15 -0,005362853 -0,88 -26 -0,010087290 -2,38*** -5 -0,009420238 -2,03** 16 -0,006178739 -1,27 -25 -0,005603300 -0,96 -4 -0,002758523 -0,56 17 -0,006894232 -1,33 -24 -0,005719409 -0,98 -3 -0,014179559 -2,84*** 18 -0,007485627 -1,71* -23 -0,007218997 -1,60 -2 -0,006857297 -1,41 19 -0,001218618 -0,20 -22 -0,004335087 -0,84 -1 -0,011683925 -2,48*** 20 -0,008471734 -1,37 -21 -0,006495857 -1,42 0 -0,010561791 -2,21** 21 -0,015210703 -3,22*** -20 -0,002126487 -0,41 1 -0,011719765 -2,20** 22 -0,006355768 -1,36 -19 -0,010337171 -2,47*** 2 -0,005839613 -1,17 23 -0,008495188 -1,74* -18 -0,005103942 -0,84 3 -0,011596502 -2,63*** 24 -0,007459863 -1,87* -17 -0,008704481 -1,79* 4 -0,007576078 -1,32 25 -0,009282742 -1,92* -16 -0,012116337 -2,22** 5 -0,002363726 -0,55 26 -0,009085776 -1,77* -15 -0,006260312 -1,01 6 -0,003742952 -0,75 27 -0,011731095 -2,45*** -14 -0,012150928 -2,41*** 7 -0,003149703 -0,66 28 -0,008268277 -1,49 -13 -0,004296103 -0,87 8 -0,003551021 -0,72 29 -0,007327438 -1,72* -12 -0,004774409 -1,00 9 -0,002853637 -0,53 30 -0,001797536 -0,37 -11 -0,006392672 -1,13 10 -0,002905375 -0,59 -10 -0,003769694 -0,74 11 -0,006877147 -1,49

In columns 1, 4 and 7 the dates relative to the announcement are given as T. In columns 2, 5 and 8 the AAR values per T are

given, and in columns 3, 6 and 9 the G-value are given. It is also indicated if the AAR’s are statistically significant:

*** = 1% significance, ** = 5% significance and * = 10% significance.

21

The cumulative average abnormal returns for acquiring firms for mergers and acquisitions in the

financial sector are calculated for 6 different event windows. The results can be found in Table 3

below. For the event window [-30 , 30] a negative cumulative average abnormal return (CAAR)

of - 41.97 % is found. When reducing the event window to [-20 , 20] the CAAR is again

negative: - 27.27 %. For the event window [-10 , 10] a negative CAAR is found of - 14.34 %.

When taking an ever shorter event window more negative CAAR‟s are found. For [-5 , 5] the

CAAR is – 9.46 %, for [-3 , 3] the CAAR is – 7.24 % and for [-1 , 1] the CAAR is – 3.40 %.

For all event windows the CAAR‟s are negative, and this leads to a negative abnormal return of

– 17.28 % when taking the average of the CAAR‟s of all six event windows that are calculated.

This indicates that in mergers and acquisitions in the financial sector for the period 2001 – 2005

the cumulative average abnormal returns for the acquiring firms are negative.

When looking at the statistical significance the abnormal returns for the event windows [-3 , 3]

and [-1 , 1] are significant on a 1% significance level. The event window [-5 , 5] is significant on

a 5% significance level. Also the average of all event windows is statically significant on a 5%

significance level. The abnormal returns with event windows [-30 , 30], [-20 , 20] and [-10 , 10]

are not significant on a 5% significance level but [-30 , 30] and [-10 , 10] are on a 10%

significance level.

Table 3: Cumulative Average Abnormal Returns

Event Window Days CAAR G-value

[ -30 , 30 ] 61 -0,419661990 -1,69* [ -20 , 20 ] 41 -0,272734601 -1,60 [ -10 , 10 ] 21 -0,143357187 -1,68* [ -5 , 5 ] 11 -0,094557016 -2,11** [ -3 , 3 ] 7 -0,072438452 -2,54*** [ -1 , 1 ] 3 -0,033965481 -2,67*** Average 24 -0,172785788 -2,05**

In the first column the event window is given, followed by the number of days in the event window in column two. In the third

column the cumulative average abnormal returns are given. The last column contains the values for the test statistic G. The

bottom row of this table shows the average values for the different variables. It is also indicated if the G-values are statistically

different from 0: *** = 1% significance, ** = 5% significance and * = 10% significance.

22

The results found show a negative average return for the acquiring firms, but there are some

limitations to these results. Not all results are statistically significant, probably due to the small

sample size. Another problem that the data has is that the announcement date is obtained directly

from the SDC Platinum database so the official announcement dates are used. But by using these

dates possible rumors or pre-announcements are not taken in to consideration. Yet these events

can influence the stock price quite heavily as shown by the example below.

When looking at the acquisition of Eurocity Properties PLC by Panther Securities PLC (deal

number 38) the announcement date that is obtained from the database is 08/11/2002, but when

looking at the stock price graph of the acquirer firm it appears that there has been a leakage of

the takeover news. In Figure 2 it can be seen that before the announcement date the stock price

increases quite significantly, and this is confirmed when looking at the deal information in the

Zephyr database. In the deal information it is

stated that on 06/11/2002 the board of Eurocity

Properties announced that they were in an

advanced stage of discussion for a takeover, so

this influenced the stock price before the official

takeover date.

Figure 2: Stock Price Deal 38

23

5: Conclusion

5.1 Conclusion This bachelor thesis examines whether mergers and acquisitions within the financial sector in

Europe during the period 2001-2005 have created value for shareholders of the acquiring firms in

terms of share price increases. To examine this main question a sample of 77 firms is used to

calculate the abnormal returns for various short term event windows and a negative cumulative

average abnormal return of – 17.28% is found. The abnormal returns are consistently negative

for all six different event windows.

Previous literature about the abnormal returns for acquiring firms in mergers and acquisitions

find dispersed results. Some find positive CAAR‟s and other find negative CAAR‟s. The average

from the papers discussed in this bachelor thesis is a slightly positive CAAR of + 0.13%.

The sample of 77 European financial merger and acquisition deals finds the following returns

for the various event windows: [-30 , 30] = - 41.97%, [-20 , 20] = - 27.27%, [-10 , 10] =

- 14.34%, [-5 , 5] = – 9.46%, [-3 3] = – 7.24% and [-1 , 1] = – 3.40%. The average of the

CAAR‟s shows a negative return of - 17.28% which is quite lower than the average of

+ 0.13% that is found in literature. For the different event windows only [-3 , 3] and [-1 , 1] are

statistically significant on a 1% level, [-5 , 5] is significant on a 5% level and [-10 , 10] and

[-30 , 30] are on a 10% level.

Since returns are negative for acquiring firms, there should be other reasons for financial firms to

undertake mergers or acquisitions. These reasons are also investigated in this thesis and the most

important ones for M&A‟s in the financial sector in particular are synergy benefits, managerial

compensation increases and obtaining a „Too Big to Fail‟ status.

So concluding on the main research question, mergers and acquisitions that have been

undertaken by European financial firms within the financial industry during the period 2001-

2005 have not created value for the shareholders in terms of an increase in share price.

24

5.2 Limitations There are some limitations to this research, starting with the fact that not all results are statically

significant. This is probably caused by the limited data set of 77 transactions which is a serious

limitation of this study. Also only short events are considered so nothing can be said about the

long term performance of the acquiring firms which is at least as important for shareholders as

the short term. Another limitation is that this study only considers deals within the financial

sector and so cannot be generalized to mergers and acquisitions in general. And also the time

period 2001-2005 include a severe recession so may not be representative for other periods.

Another limitation of the data part of this bachelor thesis is the fact that only the announcement

dates that are obtained from the SDC Platinum database are used. As shown with an example in

the section 4.3 there can be possible leakages or pre-announcements that influence stock prices

before the official announcement of the deal.

5.3 Future research The above mentioned limitations are also possibilities for future research. First of all, by

increasing the time horizon in which the deals are selected the number of deals will increase, and

consequently the significance of the data will also increase. And with a wider time period a

recession does not has as much influence as it will have on the data in this bachelor thesis.

Another possibility for future research is to not only focus on the financial sector, but take all

deals for all industries in a certain time period and divide deals in several industry groups so they

can be compared and the results can be generalized to mergers and acquisitions in general. And

finally all deals can be checked for possible leakages or announcements before the official

announcement date to make sure that stock prices are not influenced by other events.

25

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Appendix

Appendix 1: List of Deals Deal Number Announced Acquiror Name Target Name

1 03-16-01 EFG Eurobank Ergasias SA Telesis Investment Bank

2 04-01-01 Allianz AG Dresdner Bank AG

3 04-01-01 Munich Re Ergo Versicherungsgruppe AG

4 04-09-01 Dunedin Enterprise Investment Group Trust PLC

5 04-11-01 Svenska Handelsbanken AB Midtbank A/S

6 04-25-01 Eurafrance Azeo(Eurafrance)

7 05-16-01 Allianz AG Berner Versicherung AG

8 05-22-01 Dexia SA Kempen & Co NV

9 05-31-01 Baader Wertpapierhandelsbank KST Wertpapierhandels AG

10 06-15-01 Assicurazioni Generali SpA INA

11 07-20-01 Baloise-Holding AG Mercator & Noordstar(Baloise)

12 08-14-01 Royal Bank of Scotland Group Euro Sales Finance PLC

13 08-24-01 NewMedia Spark PLC Spuetz AG

14 09-27-01 Fortis (B) Fortis(NL)NV

15 10-05-01 Severis & Athienitis Finl Svcs Winvest Securities

16 10-18-01 Billam PLC World Life Sciences PLC

17 10-26-01 Befimmo SA Cibix NV

18 10-31-01 Bank of Piraeus SA Hellenic Indl Development Bank

19 11-14-01 Banca Popolare di Verona Banca Popolare di Novara Scarl

20 11-27-01 E-Capital Investments Plc Avanti Partners Plc

21 12-07-01 WCM Beteiligungs RSE Grundbesitz und

22 12-14-01 Unicredito Italiano SpA Rolo Banca 1473(Credito Itali)

23 12-17-01 IDI IPBM SA

24 02-18-02 Sydbank A/S Egnsbank Fyn

25 04-04-02 Allianz AG Dresdner Bank AG

26 04-29-02 BNP Paribas SA ConSors Discount Broker AG

27 05-11-02 Risanamento Napoli SpA Bonaparte SpA

28 05-30-02 Evolution Group PLC Beeson Gregory PLC

29 05-30-02 Fondiaria Assicurazioni SpA SAI

30 07-01-02 Mountcashel PLC Corporate Synergy Holdings PLC

31 07-16-02 Unicredito Italiano SpA Onbanca(Banca Popolare)

32 07-17-02 DAB Bank AG Self Trade

33 08-07-02 Gecina SA Simco SA

34 09-09-02 Hammerson PLC Grantchester Holdings PLC

35 09-23-02 Swiss Life Holding AG Schweizerische Lebensversicher

36 10-14-02 Deutsche Effecten und Wechsel Optic-Optical Tech Inv AG

28

37 11-06-02 EFG Eurobank Ergasias SA Ergoinvest SA

38 11-08-02 Panther Securities PLC Eurocity Properties PLC

39 11-13-02 Banca Monte dei Paschi di Banca Agricola Mantovana

40 11-13-02 Banca Monte dei Paschi di Banca Toscana

41 01-09-03 Banco Popular Espanol SA BNC

42 03-18-03 Den Norske Bank Holding ASA Gjensidige NOR ASA

43 06-05-03 Alpha Bank AE Alpha Investments SA

44 06-13-03 LjungbergGruppen AB Fastighets AB Celtica

45 06-23-03 Bank of Piraeus SA Hellenic Indl Development Bank

46 06-27-03 Alpine Select AG EIC Electricity SA

47 07-02-03 Credit Agricole SA Credit Lyonnais SA

48 07-29-03 Metrovacesa SA Bami SA Inmobiliaria

49 09-04-03 BNP Paribas SA COBEPA

50 10-01-03 IVG Immobilien AG Polar Kiinteistot Oyj

51 10-06-03 RBS First Active PLC

52 11-19-03 PSP Swiss Property AG REG Real Estate Group

53 12-19-03 Banco de Sabadell SA Banco Atlantico SA

54 12-22-03 UNIQA Versicherungen AG Mannheimer AG

55 01-19-04 Societe Generale SA General Hellenic Bank

56 02-16-04 Eurazeo SA Rue Imperiale de Lyons SA

57 04-20-04 Natexis Banques Populaires Coface

58 04-26-04 Investment AB Oresund Custos AB

59 07-23-04 Santander Central Hispano SA Abbey National PLC

60 09-02-04 Altarea SA Imaffine SA

61 09-30-04 BNP Paribas SA Union de Credit pour Batiment

62 10-14-04 Nordea Bank AB Turun Arvokiinteistot Oyj

63 12-05-04 Swiss Prime Site AG Maag Holding AG

64 12-23-04 KBC Bank & Insurance Almanij NV

65 01-28-05 Chrysalis VCT PLC Chrysalis A VCT PLC

66 03-01-05 Eurazeo SA Ateliers de Constrs du Nord

67 03-14-05 Metrovacesa SA Gecina SA

68 04-19-05 AXA-UAP SA Finaxa SA

69 05-13-05 Old Mutual PLC Foersaekrings AB Skandia

70 05-23-05 The British Land Co PLC Pillar Property PLC

71 05-30-05 Unicredito Italiano SpA Bayerische Hypo- und Vereins

72 06-12-05 Unicredito Italiano SpA Bank Austria Creditanstalt AG

73 07-29-05 National Bank of Greece SA National Real Estate SA

74 09-11-05 Allianz AG RAS

75 09-14-05 Allianz AG AGF

76 11-15-05 Commerzbank AG Eurohypo AG

77 12-01-05 Prudential PLC Egg PLC