[peace)final dissertation

7/31/2019 [Peace)Final Dissertation

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Value creation of thebanking M&A cases:

Event studies

Submitted by

Pyung-hwa Son

BSc Investment & Financial Risk Management

Supervisor: Dr Elena Kalotychou

1

st

April 2010

I certify that I have complied with the guidelines on plagiarism outlined in my

Course Handbook in the production of this dissertation and that it is my own,

unaided work

Signature:

______________________________________________________________


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Acknowledgements

I would like to give many thanks to Dr. Elena Kalotychou for her kind guidance and critical

suggestions throughout the completion of this dissertation.

Also, I would always like to thank my precious family and friends who encourage, support

and love me all the times during my life.

I love you all and you are appreciated.


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Table of Contents

-Acknowledgements....1

-Contents ....2

-List of tables and graphs.....4

-Abstract.....6

1. Introduction..8

2. Characteristics of M&A

.....10

2.1. Definition..10

2.2. Motivations10

2.2.1. Growth10

2.2.2. Synergy...11

2.2.3. Diversification12

2.2.4. Other motives.13

2.3. Classification of transaction type..13

2.3.1. Horizontal merger...14

2.3.2. Vertical merger...14

2.3.3. Conglomerate merger.14

2.4. Reasons for failure in M&A..15

3. Literature review..15

3.1. Return to the shareholders of acquiring companies..16

3.2. Return to the shareholders of target companies16

3.3. Types of payment..17


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4. Data and methodology18

4.1. Data descriptions...18

4.2. Event study18

4.3. Financial ratios..21

4.4. Efficient Market Hypothesis.21

5. Empirical case studies.22

5.1. General banking and finance industries22

5.1.1. Industry situation and rationale for M&A..22

5.1.2. Results and discussions in the acquiring companies..23

5.1.3. Results and discussions in the target companies28

5.2. Bank of America Corp. and FleetBoston Financial Corp.32

5.2.1. Company overview and rationale for M&A...32

5.2.2. Results and discussions..33

5.2.3. Profitability ratios analysis.36

6. Conclusion...38

-References...40

-Appendices .....43


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List of tables

Table 1: AAR and CAAR of the acquiring companies....23

Table 2: AAR and CAAR of the Domestic/Cross border deals...25

Table 3: AAR and CAAR of the Cash/Stock/Mix deals..26

Table 4: AAR and CAAR of the target companies..28

Table 5: AAR and CAAR of the Domestic/Cross border deals...29

Table 6: AAR and CAAR of the Cash/Stock/Mix deals..31

Table 7: AR and CAR of the Bank of America...33

Table 8: AR and CAR of the FleetBoston Financial Corp...34

Table 9: Profitability ratios of the Bank of America....36

Table 10: Profitability ratios of the peer companies................36


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List of graphs

Graph 1: AAR of the acquiring companies..24

Graph 2: CAAR of the acquiring companies...24

Graph 3: AAR of the Domestic and Cross border deals......25

Graph 4: CAAR of the Domestic and Cross border deals26

Graph 5: AAR of the Cash, Stock and Mix deals27

Graph 6: CAAR of the Cash, Stock and Mix deals..27

Graph 7: AAR of the target companies28

Graph 8: CAAR of the target companies.29

Graph 9: AAR of the Domestic and Cross border deals..30

Graph 10: CAAR of the Domestic and Cross border deals..30

Graph 11: AAR of the Cash, Stock and Mix deals......32

Graph 12: CAAR of the Cash, Stock and Mix deals....32

Graph 13: AR of the Bank of America.34

Graph 14: CAR of the Bank of America..34

Graph 15: AR of the FleetBoston Financial Corp....35

Graph 16: CAR of the FleetBoston Financial Corp.35

Graph 17: ROA of the Bank of America and Peer companies.....37

Graph 18: ROE of the Bank of America and Peer companies.....37

Graph 19: NIM of the Bank of America and Peer companies.........38


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Abstract

The objective of this dissertation is to examine that mergers in the banking industry sector

indeed do create extra values to shareholders in general.

Since few decades ago, M&A activities have increased dramatically, and accordingly,

investigation of abnormal returns to shareholders wealth for both the acquiring and target

companies are much more than issues now. Thus, this dissertation will analyze general

representative M&A cases in banking industry sector in order to find out the characteristics,

trend and behaviour of the recent M&A deals.

The pre and post-merger impact on corporate performances and stock prices will beinvestigated with Event study methodology which considered as a norm process when

evaluating the reaction of the firms to the merger announcement. More specifically, thirty

merger cases in banking industry sector will have short-term analysis by focusing on AAR

and CAAR especially in the event windows of (-2, +2) and (-40, +40) respectively, thus,

could identify market efficiency and reactions.

Therefore the case studies will be analyzed mainly based on three perspectives;

Abnormal Returns and simultaneous market reactions on the announcement date Cumulative Abnormal Returns and investment decision during event period Change in financial ratios over three years time period of pre and post-merger

So, taken as a whole, this dissertation will display; the fundamental characteristics,

motivations and reasons for failures in M&A, a review of the relevant literatures and

evidences found around this subject from previous studies, the sources of data and

methodologies that I used, which are event study, financial ratios analysis. Then, the general

thirty empirical merger case studies from banking industry sector will be followed with

analysis of industry situation, rationale for M&A and their pre and post-merger stock

performances under different categories which are types of payment and country of bid

occurred.

Afterwards, one specific case study will be conducted more deeply that is the deal between

Bank of America Corp. and FleetBoston Financial Corp. with the analysis of company


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overview, their rationale for M&A, pre and post-merger stock performances and the change

in financial ratios over time period of three years before and after.

In the last conclusion part, overall findings from the analysis will be discussed to match with

objectives of this dissertation, also limitation of this analysis and the rules of successful

M&A which can improve the quality of deals will be recommended with references and

appendices followed at the end.


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1. Introduction

Since first merger wave of 1897-1907 which was followed the economic recession of 1883,

merger activities have occurred in cyclical patterns. Majority of mergers during first merger

wave period, were horizontal merger and had the conventional monopoly behaviour. Up until

2000, there were four more merger waves which developed from simple forms of monopoly

to oligopoly and conglomerate in 20th century with more vertical mergers than horizontal

mergers. Afterwards, sixth merger wave started at economic recovery state, from deep

economic recession which was in 2002 and it had lasted until the end of 2006 with more

sophisticated ways of international takeover, Leveraged Buy Out, Management Buy Out and

many other forms in 21st century now. At the moment, a new merger wave may be forming

with relatively cheap stock prices of almost companies, which means, we are standing at the

beginning of new merger wave after experiencing of turmoil financial crisis which was at

2007 and 2008, just like we had a similar cyclical pattern in previous periods.

Banking industry always has been in the centre of merger moves, since due to the

characteristics of industry, it is vulnerable to the changes in economy, politics, regulation and

other competitive environment of the financial services industry. In result, consolidation in

banking industry has been growing dramatically because of tremendous risk exposure of

bankruptcy and veiled threats of takeover from other competitors. Rather than being pushed

to insolvency or go bankrupt, the best strategy for financially unstable banks regardless of

their size, is to be bought by other banks or finance conglomerates.

As we are in the midst of massive flows of M&A activities, majority of issues are focusing on

their post-performance and benefit that is, the deals really create additional values to

shareholders wealth. This is because, most research suggests that in the long run, M&A do

not outperform the market, nor create excessive values to shareholders. But, it is often

observable that companies tend to increase their expenditure of huge amounts of money in

provision of M&A, when economy is experiencing recession or they got in troubles. Also, in

most cases, it is revealed that shareholders of acquiring company gain zero returns or

negative returns, whilst those of target Company are experiencing positive returns. These

phenomenon are confirmed by several previous studies, for instance, Mulherin and Boone

[2000], who analyzed 281 M&A deals during 1990-1999 and found significant negative

returns to the acquiring companies, and Dodd [1980], who examined 151 M&A deals from1970 to 1977 and reported positive abnormal returns to the target companies on day (-1, 0).


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Therefore, this dissertation aims to have detailed analysis of M&A cases by conducting event

study and financial ratios analysis, in order to verify the hypothesis of Value creation of

M&A. The main findings can be summarized as follows.

First, the announcement of M&A generally has a significantly negative impact on the

acquiring companies, while has a significantly positive impact on the target companies. These

findings are supported by most of previous studies from Agrawal et al [1992], Mulherin and

Boone [2000], Sudarsanam et al [1996], Dodd and Ruback [1977] and Beitel et al [2002] so

on.

Second, companies which completed mergers with stock payment suffered from negative

returns, while companies which completed with cash payment gained significantly positive

returns and this result is also supported by majority of previous studies.

Third, after the completion of the M&A deals, the acquiring companies normally

underperform in the aspect of profitability. These poor performances in the post merger

period can be attributable to the mean reverting behaviour of stock returns over a long term

period.


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2. Characteristics of M&A

2.1. Definition

In general, the term merger is used when two companies are combined in which one company

survives and keeps going business while the other merged company no longer exists. It is

different from a consolidation, which introduce entire new company as a result of a

combination of two or more companies. However, the terms merger and consolidation are

sometimes used interchangeably and the term merger is more widely applied to combination

of companies regardless of their size.

And an acquisition means one company takes over some parts or entire of the other company

hence, the latter company may not exist as a separate entity or just continue their business

under the same name but with all controls given entirely by the acquiring company.

Therefore, a merger can be described as the combination of two companies into one, where

an acquisition as an act of purchases one company by another. Due to their similar

characteristics, literature represents these terms together as Mergers and Acquisitions.

2.2. Motivations

There are several reasons and motives why companies might engage in M&A. No matter how

important the motive is, the motivations should be given, as boards of directors are conscious

of these procedural matters. Below are main motives that inspire the M&A deals.

2.2.1. Growth

One of the most fundamental motives for M&A is growth. Growth through M&A may have

much quicker process when compared to the speed of their internal growth. Although there

are still uncertainties in the growth of both cases, it becomes less risky through M&A way. If

there are any opportunities in other region or business area, a company needs to clarify the

new market condition first, and then adjust to the new different environment such as language

and culture barriers. [Patrick A. Gaughan, 2002, p111-112]

By acquiring a target company that have the resources and other kinds of management that

they needed, the acquiring company may respond rapidly to violent circumstances and take

more market share. Of course there exists the premium paid for these advantages they get,


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which is the price of the target company, however, eventually will lead to better, quicker

growing company after acquired.

2.2.2. Synergy

Synergy is also considered as most widely used reason for explaining large premiums paid in

most M&A deals, and is the additional value that is generated by combining two companies,

creating opportunities that would not have been available to these companies operating

independently.

This can be expressed simply as:

VA+T = VA + VT

Where VA+T is the value of the combined company and, VA and VT are the values of acquiring

and target company before merged. It is only worth to take the deal, when VA+T is greater or

at least equal to the sum ofVA and VT .

There are two main types of synergy which are operating synergy and financial synergy.

Firstly, operating synergy normally comes from revenue enhancements and cost reductions.

Revenue enhancing operating synergy is defined as a newly strengthened product or service

that is formed by the mix of two different attributes of the merger partners which also,

generates short and long term revenue growth. [Mark N. Clemente and David S. Greenspan,

1998, p46]

Revenue enhancing operating synergy may have many potential sources of which from a

sharing of marketing opportunities. With their existing and new sales distribution channel,

they can sell a larger amount of products and services, thereby enabling the company to

increase its revenues quickly. Revenue enhancing operating synergy is also attainable from

merging with a major company which has popular brand name, by lending its reputation to

the product line of a merger partner. However, they are redeemed much more difficult to

achieve than cost reduction synergies. [Patrick A. Gaughan, 2002, p113-123]

Thus, many of merger manager tend to focus on latter one, and these cost reduction synergies

are normally followed by economies of scale which means reduction in per unit costs that

result from an increase in the size of scale of a companys operations. The economies of scale


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that arose from the merger, hence, allows the combined company to become more cost

efficient and profitable and is often observable from horizontal mergers which have same

businesses. This is also, closely related to the benefits of the economies of scope refers to the

ability of a company to utilize one set of inputs to produce a broader range of products and

services. These operating synergies may affect growth, margin and even value of the

companies involved in M&A. With such reasoning, horizontal and vertical mergers normally

perform better than conglomerate merger, since they are more likely to achieve economies of

scale, economies of scope and are more likely to have complementary resources that they do

not have.

Secondly, financial synergy means reduction in the costs of capital to the acquiring company

after two or more companies are combined and the payoff can take the form of higher cash

flows or lower cost of capital. Financial synergies include lots of benefits such as:

Their debt capacity may increase, since the combined company will have more stable and

predictable earnings and cash flows with less volatility, which in turn, let them to borrow

more amounts with lower interest rates. Also, by acquiring the target company which has

been experiencing net operating losses, above advantages may create tax benefits to the

acquiring company which will save in taxes and increase its value. Besides, when large

companies acquire smaller companies, or when publicly traded firms acquire private

businesses, the financial synergy may come from the projects that undertaken with the excess

cash or cash slack which generated from merger. [Aswath Damodaran, 2006, p542-543]

2.2.3. Diversification

Diversification basically means expanding outside a companys existing industry categories.

By expanding into other industries which are more profitable and less correlated and merging

with company which has imperfectly correlated earnings, the company will have much less

volatile earnings stream, thus could lower their risks involved.

However, only shareholders of the acquiring company can benefit from the diversification in

a less costly way by simply holding well diversified portfolio which is adjusted for their own

preferences. In this case, shareholders do not need to pay the premiums required for mergers,

thus, it is obviously less costly than M&A. Also, the management department of the

acquiring company may go through hard times, since they normally do not have thenecessary skills and abilities to understand and operate entirely new different industry.


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Although diversification is classified as one of the most controversial and dubious reason for

M&A, since it is easier and cheaper only for the shareholders than for the company itself, but

it is also most fundamental motive for the M&A deals as well. [Brealey and Myers, 1996,

p934]

2.2.4. Other motives

Apart from above main motives, there are still plenty of reasons why companies pursue

M&A deals. One may be the improved management. An acquiring company may want to pay

premiums for a target company because of their anticipated gains when they applies their

superior management skills to the target companys resources, since they may believe that

they could gain higher returns than market expected from the target company.

Acquiring companies believe that M&A may accelerate the research and development

process, thus, they could improve their future growth remarkably when compared to their

peer companies. Another motive is, to improve distribution channel through M&A, especially

for the companies that do not have direct access to consumers. These companies have strong

eager for developing direct channels to ensure that their products and services can reach the

ultimate consumer in an efficient manner. And market power has become critical reason for

M&A lately, since achieving a huge market share in competitive business environment is

directly related to their strong brand value and market power which will lead to higher sales

and earnings.

The motives and reasons behind M&A are many and diverse, even though some are sensible

and others are quite dubious. But key point is that all the companies should focus their main

objective of M&A on maximizing shareholders wealth.

2.3. Classification of transaction type

Throughout the years, mergers are often categorized as horizontal, vertical or conglomerate

mergers. However, in the banking industry, the most common types of mergers were

horizontal and vertical mergers, since the companies involved in these types are relatively

easy to take advantage of economies of scale, thus could maximize shareholders wealth.

These three types are explained below.


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2.3.1. Horizontal mergers

Horizontal mergers occur between two direct competitors within the same industry. The

businesses of two merged companies are very closely related, thus, the primary aim of the

merger is to gain sufficient market shares to control the market and obtain operating

synergies through economies of scale. These benefits can be gained by sharing central

management parts such as finance, research and development and marketing so on.

Once two companies are combined, the company will have strong market power and this is

why horizontal mergers are often found in highly concentrated markets which have high

entry barriers and most of the recent mergers belong to this type. However, horizontal

mergers might be regulated by antitrust law, since it has a possibility of creating a monopoly

with its enhanced market power which makes inefficient non-competitive market.

2.3.2. Vertical mergers

Vertical mergers take place between companies at different stages of production operation,

which means the combination of companies that have a buyer-seller relationship. The main

benefits are reduction in costs which incurred from research, transportation and marketing so

on. This reduction in costs from supply expenses that are generated within value chain is

called economies of vertical integration. Hence, some companies are expanding back to the

source of raw materials or forward to the ultimate consumers, in order to get control over the

whole production process.

2.3.3. Conglomerate mergers

Conglomerate mergers are mergers between companies which have unrelated businesses

which means, two companies involved are neither competitors nor a buyer-seller relationship.

The main objective of this kind of merger is to get benefits from a more diversified business

structure which spread out risks, since acquiring company may believe that they can create

additional values from target companys resources with their superior management skills.

This is why the conglomerate mergers were popular at the earlier third merger wave which

was in the 1960-1970. However, the conglomerate mergers type has become less popular

during last decades, since it was only beneficial to the shareholders of an acquiring company

and a conglomerate is often valued at a discount to the sum of its parts which is known as

conglomerate discount.


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2.4. Reasons for failure in M&A

Although, it may look so good of having M&A for many reasons, most research showed that

more than half percent of the M&A deals could not generate any additional values to the

shareholders. Here are some common reasons for failure in M&A deals.

The failure mainly may attributable to the inefficiency of acquiring companys post-merger

management plan and implementation. Simply, they are not prepared for unexpected

procedures which can occur after completion of the deals. What happens in post-merger

period is much more important than just M&A deal itself. When M&A deal is completed, one

of the most difficult steps for the acquiring company is to understand different culture,

environment and personnel. As these are accustomed to the existing behaviour, it is

extremely important to set a detailed integration plan which can cover all the differences in

their operating systems. Also, if the premium paid to the target company was too much to

handle for an acquiring company, there may be less chance that the combined company will

perform effectively with insufficient capital on the behalf of shareholders view. Then, it ruins

the main objective of maximization of shareholders wealth even though the M&A deals

were successful, and this is called winners curse problem.

In most of the M&A deals, managers of acquiring companies have a tendency tounderestimate the costs associated with unexpected events which might occur after the

completion of the deal. And they are over-optimistic about future revenues and benefits,

which makes an M&A deal over-valued and this is why acquiring companies pay a higher

premium than the market expectation. Therefore, acquiring companies should carefully look

whether the M&A deals have an indeed reasonable rationale to proceed or not, otherwise, the

deal might worsen the companys situation rather than create additional values.

3. Literature review

There were many researches carried out in order to investigate the profitability of M&A deals

and these were mainly conducted by event study methodology which compares the change in

the stock price and market reaction for the acquiring and target companies before and after

the merger announcement. Before move on to the empirical analysis part, below are the

previous studies and findings of event study of M&A deals.


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3.1. Return to the shareholders of acquiring companies

Although the evidences are mixed such like Jensen and Ruback [1983] said that gains to the

acquiring companies from mergers are mixed due to difficulties in the measure of post-

merger returns, but most studies verify that returns of acquiring companies are negative in

general.

Agrawal et al [1992] analyzed data range of 1955-1987 and revealed that shareholders of

acquiring companies experience significantly negative returns over five years after the

merger. However, Loughran and Vijh [1997] amended this view by insisting that the model

used by them was inaccurate, and reported that only companies who completed mergers

experience negative returns whereas companies who completed tender offers gain

significantly positive abnormal returns.

Mulherin and Boone [2000] also found significantly negative returns of 0.37% to acquiring

companies after examined 281 M&A deals from 1990 to 1999. This is supported by Datta

and Puia [1995] who researched 112 cross border M&A deals during 1978-1990 and revealed

that cross border M&A deals, on average, bring the negative returns to acquiring companies,

thus, destroying values for shareholders. Sudarsanam et al [1996] who analyzed 429 UK

acquiring companies during 1980-1990, again, found statistically significant negative returns

which has range between -1.26% and -4.04%.

In contrast, Franks et al [1977] analyzed 74 M&A deals in UK between 1955 and 1972 and

found significantly positive abnormal returns to acquiring companies. Moreover, Cakici et al

[1996] analyzed 195 cross border M&A deals during 1983-1992 over the event window of (-

10, +10) and found positive abnormal returns to acquiring companies, and, same results werefound by Conn and Connell [1990] who reported positive abnormal returns to UK and US

acquiring companies during 1971-1980.

3.2. Return to the shareholders of target companies

In general, shareholders of target companies enjoy significantly positive returns, despite

variations in their different conditions of M&A deals, and most of studies support this result.

For instance, Jensen and Ruback [1983] summarized 13 studies of M&A deals during 1977-


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1983 and found evidences of positive returns to the target companies. These returns to be

higher in tender offers than complete mergers, which prove that the premium paid is lower in

friendly mergers.

Dodd and Ruback [1977] also found that shareholders of target companies gain large positive

abnormal returns regardless of type and outcome of the M&A deals by analyzing stock

returns of one month post-merger period after the first announcement. And Dodd [1980]

again, examined 151 M&A deals during 1970-1977 and gained large significantly positive

abnormal returns to the target companies on the day and the day before the announcement.

Moreover, Dennis and McConnell [1986] analyzed 76 target companies during 1962-1980 in

the event period of (-1, 0), and found significantly positive return of 8.56% and similarly in

the same event period of (-1, 0), Beitel et al [2002] gained positive return of 10.48% by

analyzing 98 target companies from 1985 to 2000. Even in the cross border M&A deals, Eun

et al [1996] verified that target companies still experienced significantly positive gains.

3.3. Types of payment

The exchange term in M&A deals has three types which are cash, stock or mixture of the two

and the choice between them is depending on the market condition, tax and financial

strategies so on. Depends on the types of payment, the returns to the shareholders of

acquiring companies vary. The common result came out of previous studies is, companies

which completed stock mergers experienced negative returns while companies which

completed mergers with cash gained significant positive returns and this evidence is

supported by Loughran and Vijh [1997].

Asquith et al [1987] and Travlos [1987] also found similar evidences that deals accomplished

with stock payment suffer from significantly negative returns on announcement day, while

returns to the shareholders of cash deals are zero or slightly positive. This is due to the tax

effects, which in general, capital gains are taxed instantly in cash deals, while capital gains

taxes are deferred until the stocks received are sold in stock deals. Also, this might be due to

the managers perception of the companys stock price. Myers and Majluf [1984] suggested

that companies tend to choose stock deals when the stock is over-valued and on the other


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hand, may pay with cash if the stock is under-valued. The shareholders may recognize the

stocks are over-priced, when the company chooses stock payment.

Thus, most of previous studies clearly suggest that shareholders benefit most from the M&A

cash deal, while they gain smaller returns from other types of payment which are stock or

mixture of them.

4. Data and methodology

4.1. Data descriptions

This dissertation aims to have an analysis of M&A cases in banking industry, therefore, allthe daily data including stock prices, benchmark indices (FTSE All World Index and S&P

500), mergers information and financial ratios of thirty companies are collected from

Bloomberg and all the tables and graphs are my own work from MS excel. For the

benchmark index, FTSE All World Index is selected, since it is most widely used and

includes more than 2700 stocks from 49 different countries, also, it counts for 90-95%

capitalization of each of the markets in US$ terms.

In order to catch the trends of the recent M&A, this dissertation only included M&A deals

announced between January of 2000 and December of 2009. Further, all the deals are friendly

completed and divided into balanced number of subsets, which are 9 cash deals, 12 stock

deals and 9 mixed deals, so as to conduct a fair comparison. Also, 8 cross border deals are

included in order to compare the domestic deals with international deals, thus, could find out

different stock price movement and market reaction.

There are two fundamental methods to measure the performance of M&A deals, which are

event study and financial ratios analysis, and these are explained below.

4.2. Event study

This method is originated from Fama et al [1969], which examines the abnormal returns to

the shareholders in the period close to the announcement date.

For the estimation, the market return model method is used, since it is the most common

method when conducts empirical research on M&A. This model assumes that there is a linear


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relationship between the return on the each stock and that of the market and the equation is

given as,

Rit = i + iRmt + it

Where;

Rit is the return on stock i at time t,

Rmt is the return on FTSE All World Index at time t,

i is the average return of stock i in the period not explained by the market,

i

is the sensitivity of stock i to the market,

it is the residuals

From above equation, the daily returns for each company is calculated as,

Rit =Pit Pit1

Pit1

Where Pit is the price of stock i at time t.

The and coefficients are estimated through the above regression, and this calculation

should include a period which is not involved in the event period, thus, the abnormal returns

are calculated over the estimation period of (-240, -41). After obtaining the and

coefficients estimates, expected returns for each stock can be calculated as,

ERit = i + iRmt

Then, the abnormal returns of stock i under the market return model method are simply the

difference between actual returns and expected returns at time t.

ARit = Rit E(R)it

To investigate the total returns to each company over the event windows, cumulative

abnormal returns (CAR) are calculated as,

CARit,T

=

AR

it

T

t=t


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Hence, CARit,T can be interpreted as the cumulative extra earnings for stock i between time

t and T. The stock returns for each company are quite noisy and fluctuate, however this

problem can be resolved when large number of companies are averaged together. This is

called average abnormal returns (AAR) and AAR for the N number of companies at time tare calculated as,

AARt =1

NARit

N

i=1

The AAR then can be summed together to cover the whole event windows, which represents

the cumulative average abnormal returns (CAAR).

CAAR(t,T) = AARtT

t=t

After obtaining the AAR and CAAR, hypothesis test is conducted with null hypothesis of

AAR or CAAR equals to zero. By conducting the hypothesis test, the creation of significantly

positive or negative return can be verified. Although under financial circumstances, the

distribution of stock returns tends to have fat tails and is skewed, here, normal distribution is

assumed since we have got enough number of companies to ease the complexity.

Test-statistics for AAR and CAAR are given by,

AARt =AARt

AAR 241,41

CAAR(t,T) =CAAR(t,T)

AAR (241,41) number of cumulative days

Where AAR 241,41 is the standard deviation for the AAR for the estimation period of

(-241, -41).

The confidence level of 95%, which is same as 5% significance level, is used to judge the

significance of null hypothesis. Hence, if the absolute value of the test-statistics is greater

than1.96, the null hypothesis of zero abnormal return is rejected which implies there existsignificant abnormal returns either positive or negative.


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4.3. Financial ratios

It measures the overall financial results of the companies, which include income statement,

balance sheet and other financial statements. In order to judge the success of the M&A deals,

it is vital to oversee performance change in ratios, and this dissertation mainly focuses on

profitability ratios since it is directly related to the shareholders wealth.

Profitability ratios measure the whole operating performance of the companies and can be

measured by some representative ratios such as return on assets (ROA), return on common

equity (ROE) and net interest margin (NIM). Briefly, ROA is the returns earned from the

assets financed by companies, thus, it indicates how efficiently companies are operated with

given assets and resources. ROE measures how much profits a company generates with the

funds that shareholders have invested. More importantly, NIM shows average interest margin

that the companies are receiving from borrowing and lending funds, thus, it is a critical ratio

especially for banks. These profitability ratios can be calculated as,

Return on Assets =Net Income

Total Assets

Return on Equity =Net Income

Shareholders Equity

Net Interest Margin =Total Interest Income Total Interest Expenses

Total Earning Assets

4.4. Efficient Market Hypothesis

The Efficient Market Hypothesis (EMH) is a statement about how an assets price should

react to sudden new information. This is a critical theory for the assessment of value creation

of the M&A deals, since a fluctuation of the stock prices are fairly dependent upon the

market reaction and both are quite closely related.

Fama [1970] suggested that a market is efficient, when prices fully and instantaneously

reflect available information. If so, investors can only earn an average return depending on

their risk aversion, since they use the same information as the rest of the market.


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There are three types of EMH which are weak form, semi-strong form and strong form

efficiency. Under weak form efficiency, prices should reflect all the past information such as

prices, earnings and interest rate so on, thus, technical analysis becomes useless in this case.

The semi-strong form efficiency implies that past and publicly available information should

be incorporated in the current prices such as earning forecasts, financial statement and price

to book ratio so on, in this case, fundamental analysis is not applicable. Hence, under semi-

strong form efficiency, investors can only increase average return if they take on more risk,

except some market anomalies such as January effect and size anomaly.

Lastly, strong form efficiency refers to that all the information mentioned above, which are

past, public and even private information should be included into the current price. Hence,

even inside traders and active portfolio managers are not able to beat the market under strong

form efficiency.

The Efficient Market Hypothesis is important to know in this dissertation, since only if the

stock price reflects the entire public announcement, can we use the abnormal returns as a

measure of the M&A deals. And event study is basically conducted under the assumption of

semi-strong or strong form efficiency.

5. Empirical case studies

5.1. General banking and finance industries

5.1.1. Industry situation and rationale for M&A

Originally, banking industries had been protected from unwanted takeovers, since regulatory

policies imposed strict restrictions than other industries in terms of market entrance and

competition due to the characteristics of industries. However, during the 1980-1990s, there

were a lot of changes in the environments and regulations of the banking and financial

services which made restrictions were lifted and in result, they were challenged from

increasing number of not only banks but also non-bank competitors.

Afterwards, the banking industries have been in the midst of a huge merger waves which

contributed to a mass reduction in the number of independent banks. These competitive

environments and financial pressure have pushed majority of banks, even the most profitable

banks in the industry, to have a belief and enthusiasm for M&A rather than independent


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internal growth. The general motive and rationale for M&A which explained on section 2,

also applies to the banking mergers, however, here are additional reasons for M&A in the

banking point of view.

First of all, main rationale behind M&A in the banking industries is costs savings. This

reduction in costs can be maximized when the two companies have overlapped operations,

thus, during the M&A process, their overlapped departments, branches and inefficient

management will be eliminated and may operate efficiently after all. Also, by combining

different areas of businesses such as banking and insurance, they can create positive

synergies which come from different assets and resources; Bancassurance is a good

example of this.

With retained earnings which gained from reduction in costs, banks can also diversify their

operations in more effective way, for instance, by moving costly functions to the other parts

of the world where economies of scale can be achieved, thus, could lower the operational

risks involved and volatility of earnings. Another critical motive for M&A in banking

industries is size matters. The profitability of banks is hugely dependent upon the size and

quality of their businesses and services, which make the banks to reach the ultimate clients

with their sound capital base and worldwide market access. Lastly, the introduction of

important information systems have created the economies of scale and over-capacity in

banking operations, thus, contributed to the boost of M&A activities in order to improve the

profitability and efficiency in the banking industries. [Radecki et al, 1997]

Therefore, through successful M&A activities, banks and financial services companies can

keep up the fierce competition with other competitors under turmoil financial environment

and ultimately could survive.

5.1.2. Results and discussions in the acquiring companies

Table 1: AAR and CAAR of the acquiring companies

Acquirer AARt T-TEST CAARt T-TEST

-2 0.0543% 0.19548 0.4941% 0.28482

-1 -0.1721% -0.6196 0.3220% 0.18327

Day 0 -2.8260% -10.172 -2.5040% -1.4076

1 -0.8455% -3.0435 -3.3495% -1.8604

2 -0.0067% -0.0242 -3.3562% -1.8423


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According to the Table 1, the market showed significantly negative reactions on the

announcement day and day 1. On average, all the thirty acquiring companies experienced

negative returns of 2.826% on day 0, and negative returns of 0.8455% on day 1 respectively.

This phenomenon tells us that market showed a delayed reaction to the announcement and

this violates the notion of semi-strong form efficiency, since investors could have made

abnormal returns by trading on public information.

Graph 1: AAR of the acquiring companies

Graph 2: CAAR of the acquiring companies

Graphs 1 and 2 depict AAR and CAAR of the thirty acquiring companies for the event period

of (-40, +40). It is obviously observable that market showed significantly negative reaction

on the announcement date. And this is exactly matched with previous findings from

Sudarsanam et al [1996], who analyzed 429 UK acquiring companies and found statisticallysignificant negative returns which has range between -1.26% and -4.04%.


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Table 2: AAR and CAAR of the Domestic/Cross border deals

From Table 2, it can be seen that twenty two domestic deals out of thirty deals are showing

the same results with table 1 results, which violates semi-strong form efficiency and showed

delayed reaction on day 1. However, eight cross border deals had significantly negative

reaction only on the announcement date, which is consistent with semi-strong form efficiency,

since the price adjusted quickly to the new information.

Graph 3: AAR of the Domestic and Cross border deals

Domestic AARt T-TEST CAARt T-TEST

-2 0.2885% 0.98485 1.7733% 0.96934

-1 -0.1064% -0.3633 1.6669% 0.89971Day 0 -3.0996% -10.581 -1.4326% -0.7638

1 -0.9480% -3.2361 -2.3806% -1.254

2 0.3048% 1.0404 -2.0759% -1.0806

Cross border AARt T-TEST CAARt T-TEST

-2 -0.5897% -0.9028 -3.0237% -0.7412

-1 -0.3528% -0.5401 -3.3765% -0.8173

Day 0 -2.0736% -3.1744 -5.4501% -1.303

1 -0.5637% -0.863 -6.0138% -1.4206

2 -0.8633% -1.3216 -6.8771% -1.6055


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Graph 4: CAAR of the Domestic and Cross border deals

Graphs 3 and 4 indicate that both domestic and cross border deals are also consistent with the

previous findings that have negative reaction on the announcement date and are confirmed by

Datta and Puia [1995], who revealed that cross border M&A deals, on average, bring the

negative returns to acquiring companies, thus, destroying values for shareholders.

Table 3: AAR and CAAR of the Cash/Stock/Mix deals

Cash AARt T-TEST CAARt T-TEST

-2 -0.9665% -1.7596 -2.2887% -0.6672

-1 -0.4066% -0.7404 -2.6953% -0.7759

Day 0 -0.7775% -1.4155 -3.4728% -0.9874

1 -0.5483% -0.9983 -4.0211% -1.1297

2 -1.0002% -1.821 -5.0213% -1.3941

Stock AARt T-TEST CAARt T-TEST

-2 0.5539% 1.16752 3.0779% 1.03887

-1 0.1555% 0.32777 3.2334% 1.07763

Day 0 -3.8669% -8.1508 -0.6335% -0.20851 -1.0602% -2.2347 -1.6937% -0.5509

2 0.4298% 0.90603 -1.2639% -0.4063

Mix AARt T-TEST CAARt T-TEST

-2 0.4090% 1.10154 -0.1681% -0.0725

-1 -0.3744% -1.0085 -0.5425% -0.231

Day 0 -3.4865% -9.3905 -4.0291% -1.6948

1 -0.8565% -2.3067 -4.8855% -2.0304

2 0.4047% 1.09001 -4.4808% -1.8404


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Above Table 3 tells us the results under different types of payment which are cash, stock and

combination of the two. From nine cash deals out of thirty deals, it showed insignificant

results during event window of (-2, +2), which confirms the null hypothesis of zero abnormal

returns. In the stock and mix deals, both showed significant negative returns on the

announcement day and the following day, which indicate the slow reaction of the market.

Graph 5: AAR of the Cash, Stock and Mix deals

Graph 6: CAAR of the Cash, Stock and Mix deals

As it can be seen from Graphs 5 and 6, the cash deals have performed better than rest of the

deals in the aspects of AAR and CAAR on the announcement date and over the event period

of (-40, +40). These critical results are consistent with most of previous studies, which state

that shareholders benefit most from the M&A cash deal, while they gain smaller returns fromother types of payment which are stock or combination of them.


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5.1.3. Results and discussions in the target companies

Table 4: AAR and CAAR of the target companies

Table 4 shows that the market had significantly positive reactions on the day before the

announcement date and the announcement date. All the target companies experienced huge

positive returns of 17.2966% on the announcement date and positive returns of 1.7644% on

the previous day on average. The significantly positive abnormal returns on the day before

announcement date, suggest that the information was leaked beforehand. However, if those

leaked information were not public knowledge until the announcement date, then this result is

consistent with semi-strong form efficiency. But, strong form efficiency seems to have been

violated, since the abnormal returns were also significantly positive on the announcement

date. If the market were strong form efficient, adjustments should have occurred only on the

previous day.

Graph 7: AAR of the target companies

Target AARt T-TEST CAARt T-TEST-2 0.3718% 0.91524 3.3236% 1.31023

-1 1.7644% 4.34372 5.0879% 1.98055

Day 0 17.2966% 42.583 22.3845% 8.6066

1 0.6788% 1.67111 23.0633% 8.76138

2 0.0423% 0.10419 23.1056% 8.67479


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Graph 8: CAAR of the target companies

Graphs 7 and 8 demonstrate AAR and CAAR of the thirty target companies for the event

period of (-40, +40). It is clear that the market experienced significantly positive returns on

the announcement date and this result is exactly supported by Dodd [1980], who examined

151 M&A deals during 1970-1977 and found large significantly positive abnormal returns to

the target companies on the day and the day before the announcement.

Table 5: AAR and CAAR of the Domestic/Cross border deals

Once again, we have found same results from both domestic and cross border deals those

significantly positive returns on the day before the announcement date and the announcement

date. But interestingly, the market reacted positively on the following day of the

announcement date in domestic deals and this is because, the leaked information were not

public knowledge until the announcement date and showed delayed reaction even after.

Domestic AARt T-TEST CAARt T-TEST

-2 0.5617% 1.83516 3.5688% 1.86721

-1 0.9340% 3.05164 4.5028% 2.32623

Day 0 15.0860% 49.2917 19.5889% 9.99576

1 1.2144% 3.96783 20.8032% 10.4883

2 0.3549% 1.1595 21.1581% 10.5424

Cross border AARt T-TEST CAARt T-TEST

-2 -0.6568% -0.5741 2.1427% 0.29989

-1 4.0479% 3.53798 6.1906% 0.85552

Day 0 23.3755% 20.4309 29.5661% 4.03578

1 -0.7941% -0.6941 28.7720% 3.88035

2 -0.8172% -0.7143 27.9548% 3.72604


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Graph 9: AAR of the Domestic and Cross border deals

Graph 10: CAAR of the Domestic and Cross border deals

From Graphs 9 and 10, it is obvious that the market in both deals has reacted in a

significantly positive way on the announcement date and cross border deals have

outperformed the domestic deals.


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Table 6: AAR and CAAR of the Cash/Stock/Mix deals

The cash deals have recorded highest positive returns of 23.8398% compared to other deals

and the same information leakage were happened, thus, is consistent with the semi-strong

form efficiency only if the information was not public domain until the announcement date.

In stock deals, they showed clear semi-strong form efficiency with significantly positive

returns only on the announcement date. And lastly, the mix deals have experienced both

information leakage and delayed market reaction. These results are consistent with the

findings from Dodd and Ruback [1977], who suggested that shareholders of target companies

gain large positive abnormal returns regardless of different types of payment and outcome of

the M&A deals.

Cash AARt T-TEST CAARt T-TEST-2 -0.6589% -0.6671 3.7262% 0.6041

-1 2.9858% 3.02298 6.7120% 1.07448

Day 0 23.8398% 24.1366 30.5518% 4.8308

1 -0.8446% -0.8551 29.7073% 4.641

2 -0.7418% -0.7511 28.9655% 4.47218

Stock AARt T-TEST CAARt T-TEST

-2 0.9398% 1.86495 4.6256% 1.46977

-1 0.6156% 1.22153 5.2412% 1.64443

Day 0 14.7137% 29.1971 19.9548% 6.18407

1 0.0162% 0.0322 19.9711% 6.11497

2 0.1674% 0.33212 20.1384% 6.0941

Mix AARt T-TEST CAARt T-TEST

-2 0.4171% 0.83209 0.9570% 0.30575

-1 2.0746% 4.13914 3.0316% 0.95636

Day 0 14.1972% 28.3255 17.2288% 5.36833

1 3.0855% 6.15607 20.3143% 6.25393

2 0.6597% 1.31625 20.9740% 6.38151


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Graph 11: AAR of the Cash, Stock and Mix deals

Graph 12: CAAR of the Cash, Stock and Mix deals

Same results with the acquiring companies were found that cash deals outperformed the rest

of the deals and this is supported by majority of previous studies that shareholders gain most

significantly positive returns from mergers with cash payment.

5.2. Bank of America Corp. and FleetBoston Financial Corp.

5.2.1. Company overview and rationale for M&A

The Bank of America was originally formed by a $60 billion merger with NationsBank in1998. Afterwards, Bank of America became the third major bank in US and announced


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merger agreement with FleetBoston which was the seventh major bank in US on 27th of

October, 2003 which had worth over $47 billion at that time. The deal was completed on 1st

of April, 2004 with a stock payment type, in result, FleetBoston shareholders received 0.5553

of the Bank of America common share for each share of the Boston bank and became the

second largest bank in the world behind the Citigroup. The combined bank had the largest

retail banking network in the US with 5,700 branches across 29 states.

The main reason behind the acquisition of FleetBoston was to achieve an increase in market

share by expanding into the New England and Northeast region. Since the majority market

shares of Bank of America were invested only in the West, Midwest and South of the US,

they needed to acquire the New England and Northeast region of FleetBostons.

The Bank of America paid 42% of market premiums, thus, in order to offset these huge

expenses, another aim of the acquisition for the Bank of America was to achieve a reduction

in costs through economies of scale. However, the objective of reduction in costs seemed

difficult to be achieved at that time, since both banks had different main lines of businesses

and no overlapping branches or operations. Therefore, it was an essential task for the Bank of

America to assimilate FleetBostons different operations and systems, and get rid of

unnecessary costs in order to achieve economies of scale.

5.2.2. Results and discussions

Table 7: AR and CAR of the Bank of America

From Table 7, the market shows significantly negative returns of 10.3318% and 2.2698% on

the announcement date and the following day. The significantly negative returns on day 1

represent that the reaction of the slow learning market was delayed. Afterwards, the opposite

signal of significantly positive returns on day 2 indicates the markets correction movement

of its over-reaction which was on the announcement date and day 1.

ARt T-TEST CARt T-TEST

-2 0.6248% 0.90789 0.8914% 0.20742

-1 0.4649% 0.67559 1.3563% 0.31163

Day 0 -10.3318% -15.014 -8.9755% -2.0369

1 -2.2698% -3.2983 -11.2453% -2.52152 1.7890% 2.59968 -9.4563% -2.0955


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Graph 13: AR of the Bank of America

Graph 14: CAR of the Bank of America

It is clearly observable from Graphs 13 and 14 that the market experienced huge negative

returns on the announcement date. This common phenomenon is supported by Mulherin and

Boone [2000], who found significant negative returns of -0.37% to acquiring companies after

examined 281 M&A deals from 1990 to 1999.

Table 8: AR and CAR of the FleetBoston Financial Corp

ARt T-TEST CARt T-TEST

-2 -0.2361% -0.2125 2.2576% 0.32538

-1 -0.2933% -0.264 1.9644% 0.27955

Day 0 22.9554% 20.6611 24.9197% 3.50283

1 -2.8765% -2.589 22.0432% 3.06139

2 1.6776% 1.50989 23.7208% 3.25584


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Table 8 indicates that there was a huge significantly positive return of 22.9554% on the

announcement date and a negative return of 2.8765% on the following day. Thus, this

opposite direction of movement can be regarded as a correction of the over-reaction which

was on the announcement date.

Graph 15: AR of the FleetBoston Financial Corp

Graph 16: CAR of the FleetBoston Financial Corp

The significantly positive reaction of the market on the announcement date can be easily

observed in the Graphs 15 and 16. Jensen and Ruback [1983] support this view with

evidences of positive returns to the target companies at the announcement date.


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5.2.3. Profitability ratios analysis

In order to measure the pre and post merger performances, it is an essential to analyze the

financial statement of the Bank of America. There are lots of financial ratios can be analyzed,

however, this dissertation is focused on the profitability ratios such as Return on Assets,

Return on Equity and Net interest Margin, which are the main interests of shareholders.

These profitability ratios are summarized in below Table 9 and 10.

Table 9: Profitability ratios of the Bank of America

Table 10: Profitability ratios of the peer companies

During the pre and post merger periods, the Bank of America maintained relatively good

performances in the aspects of profitability, although these ratios had been down trended.

They have managed well above the averages of the peer companies; however, Return on

Shareholders Equity has decreased sharply after merger on October in 2003 which was

lower than the average of the peer companies. This is not good news to the shareholders,since this is the ratio that shareholders are most concerned. These results are not exactly, but

Profitability ratios 2000 2001 2002 2003 2004 2005 2006

Return on Assets 1.18% 1.07% 1.44% 1.57% 1.52% 1.37% 1.53%Return on Equity 16.34% 14.14% 18.73% 22.01% 18.84% 16.35% 18.07%

Net Interest Margin 3.51% 4.00% 4.20% 3.95% 3.81% 3.15% 3.13%

Pre-merger Post-merger

Profitability ratios 2000 2001 2002 2003 2004 2005 2006

HSBC Holdings 1.09 0.75 0.86 0.98 1.12 1.08 0.93

Citigroup 1.58 1.43 1.41 1.51 1.24 1.65 1.27

Goldman Sachs 1.14 0.77 0.63 0.79 0.97 0.91 1.22

JPMorgan Chase&Co 0.81 0.23 0.22 0.87 0.46 0.72 1.13

Wells Fargo&Co 1.56 1.18 1.65 1.68 1.72 1.69 1.76

Average 1.24% 0.87% 0.95% 1.17% 1.10% 1.21% 1.26%

HSBC Holdings 17.08 11.11 12.71 13.9 16.15 16.93 15.64

Citigroup 22.18 19.44 18.41 19.52 16.56 22.33 18.66

Goldman Sachs 23 13.29 11.36 14.79 19.49 21.85 31.89

JPMorgan Chase&Co 15.17 4.02 3.96 15.43 5.87 7.98 12.96

Wells Fargo&Co 16.09 12.77 18.92 19.15 19.38 19.61 19.77

Average 18.70% 12.13% 13.07% 16.56% 15.49% 17.74% 19.78%

HSBC Holdings 2.61 2.55 2.49 3.32 3.12 2.58 2.38

Citigroup 3.9 3.95 4.09 3.85 3.45 2.95 2.58

Goldman Sachs 0.38 0.45 0.76 0.87 0.68 0.52 0.47JPMorgan Chase&Co 1.81 2.06 2.11 2.23 2.23 2.07 2.04

Wells Fargo&Co 5.28 5.36 5.44 5.22 4.9 4.72 4.88

Average 2.80% 2.87% 2.98% 3.10% 2.88% 2.57% 2.47%

Net Interest Margin

Post-mergerPre-merger

Return on Assets

Return on Equity


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partially consistent with the findings from Mueller [1980], who examined 287 merger cases

during 1962-1972 and found that returns to the acquiring companies were less profitable than

comparable companies in post merger period, although results were not significant. These

discussions can be verified by below graphs.

Graph 17: ROA of the Bank of America and Peer companies

Graph 18: ROE of the Bank of America and Peer companies


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Graph 19: NIM of the Bank of America and Peer companies

6. Conclusion

After since the 1980-1990s, when there were lots of changes in the regulations and

restrictions on the banking and financial services industries, they were challenged from

increasing number of fierce competitors and left in the midst of a huge merger waves. Inresult, all the issues of shareholders were focused on their wealth gains from M&A deals.

Thus, this dissertation examined the main objective ofvalue creation of the recent banking

M&A cases to the shareholders by conducting standard process of event study and financial

ratios analysis. All the findings from this dissertation can be summarized as follows.

From the analysis of the general thirty merger cases, different results came out for the

acquiring companies and the target companies. The acquiring companies realized

significantly negative returns of 2.8260% on the announcement date and negative returns of

0.8455% on the following day which indicates the delayed reaction of the market. In contrast,

the target companies gained significantly positive returns of 17.2966% on the announcement

date and 1.7644% on the day before announcement date which represents the information

was leaked beforehand. The assumption of the event study methodology is that the market is

efficient; however, the results from this dissertation were mostly not consistent with the semi-

strong form market efficiency since the market showed the phenomenon of information

leakage and delayed reaction before or after the announcement date.


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Also, event study was conducted under different categories in order to analyze in a various

way. Cross border deals reacted more positively than domestic deals to the both acquiring

companies and target companies on the announcement date and afterwards. Under the

categories of different types of payment, the cash deals significantly outperformed in a

positive way to the both acquiring companies and target companies, while shareholders

gained less or worse returns from the deals with other types of payment which were the stock

and the combination of cash and stock. All of the above findings are consistent with the

recent trends of the M&A deals, and supported by most of common previous studies.

From the Bank of America and FleetBoston case study, interestingly, slight different results

were found. The shareholders of Bank of America experienced significantly negative returns

of 10.3318% and 2.2698% on the announcement date and the following day respectively,

however, there was a significantly positive reaction on day 2 which can be regarded as a

correction movement of an over-reaction which was on the previous day. The similar market

reactions were also found on FleetBoston case. The profitability ratios of Bank of America,

including ROA, ROE and NIM, showed downward trend in post-merger period especially

with ROE, which had a sharp decrease after the M&A. Even though the profitability ratios

were still above the average of the peer companies, sharp decrease of the ROE in post-merger

period was not really good news for the shareholders of Bank of America.

There are some limitations in this dissertation which involved in the sample M&A deals

selected. The samples included only thirty banks and financial services companies regardless

of their main businesses; thus, it might contain sampling error which comes from the lack of

data and might provide biased results. Since this dissertation included friendly completed

merger deals only, it may give a wider picture of analysis, if we extend the research to the

other types of mergers as well. In the Bank of America and FleetBoston case study, this

dissertation only focused on the profitability ratios analysis, thus, it would provide more

accurate measure of post-performances if further financial ratios were analyzed.

Therefore, M&A can create additional values not only to the target shareholders, but also to

the shareholders of acquiring companies, when the deal is implemented with careful intention

and in-depth analysis. Lastly, I hope this dissertation gives an insight of the value creation of

the M&A cases to investors and banks, so that they could make better investment decisions.


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of synergy and ownership structure, The Journal of Business Finance and Accounting 23,

pp.673-698.

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returns, The Journal of finance 42, pp.943-964.

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43

Appendices

List of companies and announcement date

Announcement date Acquirer (Country) Target (Country)

2005-05-09 Barclays, UK ABSA Group, South Africa

2006-08-01 HBOS, UK McCarthy&Stone, UK

2000-11-20 Banco Santander SA, Spain Banco do Estado de Sao Paulo, Brazil

2000-03-14 Dexia SA, Belgium Financial Security Assurance Holdings, US

2000-05-15 UniCredit SpA, Italy Pioneer Grooup, US

2007-11-19 Credit Agricole SA, France Bankinter SA, Spain

2000-10-10 Deutsche Bank AG, Germany National Discount Brokers Group, US

2007-07-09 Marshall&Ilsley Corp, US First Indiana Corp, US

2003-12-02 Hibernia Corp, US Coastal Bancorp, US

2008-05-13 Westpac Banking Corp, Australia St George Bank, Australia

2006-12-04 Bank of New York Mellon Corp, US Mellon Financial Corp, US

2006-05-25 Regions Financial Corp, US AmSouth Bancorp, US

2000-07-22 UniCredit Bank AG, Germany Bank Austria Creditanstalt AG, Austria

2007-02-05 State Street Corp, US Investors Financial Services Corp, US

2003-01-21 BB&T Corp, US First Virginia Banks, US

2007-05-01 National City Corp, US MAF Bancorp, US

2001-01-26 Royal Bank of Canada, Canada RBC Bancorporation USA, US

2000-03-20 National Commerce Financial Corp, US CCB Financial Corp, US

2006-09-21 First Busey Corp, US Main Street Trust, US

2004-11-16 Community Banks, US Pennrock Financial Services Corp, US

2007-07-26 StellarOne Corp, US FNB Corp, US

2006-12-20 Huntington Bancshares, US Sky Financial Group, US

2006-05-02 MB Financial, US First Oak Brook Bancshares, US

2006-10-09 PNC Financial Services Group, US Mercantile Bankshares Corp, US

2006-05-07 Wachovia Corp, US Golden West Financial Corp, US

2006-06-05 Sterling Financial Corp, US FirstBank NW Corp, US

2007-06-27 People's United Financial, US Chittenden Corp, US

2004-05-09 SunTrust Banks, US National Commerce Financial Corp, US

2005-07-26 Fulton Financial Corp, US Columbia Bancorp, US

2000-05-17 M&T Bank Corp, US Keystone Financial, US


45/48

44

AAR and CAAR of the acquiring companies for (-40, +40)

T AA Rt T-TEST CA ARt T-TEST

-40 -0.000501627 -0.1805656 -0.0005016 -0.1805656

-39 0.004927558 1.77372201 0.00442593 1.12653171

-38 0.002254713 0.81160582 0.00668064 1.38839012

-37 -0.001357692 -0.4887143 0.00532295 0.95802395

-36 0.000699617 0.25183395 0.00602257 0.96950624-35 0.001783686 0.6420552 0.00780626 1.147152

-34 -0.000144727 -0.052096 0.00766153 1.04236595

-33 0.004389653 1.58009813 0.01205118 1.53369312

-32 0.001013312 0.36475153 0.01306449 1.56756358

-31 -0.002847607 -1.0250238 0.01021689 1.16298041

-30 -0.004495358 -1.6181477 0.00572153 0.62096844

-29 0.00145484 0.52368391 0.00717637 0.74570654

-28 -0.004803447 -1.7290471 0.00237292 0.2369003

-27 0.004009769 1.44335513 0.00638269 0.61403572

-26 0.003224401 1.16065423 0.00960709 0.8928945

-25 0.000480982 0.17313406 0.01008807 0.9078249

-24 -0.003596161 -1.2944729 0.00649191 0.56676373

-23 -0.001633576 -0.5880214 0.00485834 0.41219736

-22 -0.003991973 -1.4369493 0.00086636 0.07154468

-21 -0.001770734 -0.6373927 -0.0009044 -0.0727922

-20 0.001393906 0.50175009 0.00048954 0.03845293

-19 0.001636229 0.58897664 0.00212577 0.16313908

-18 -0.000359375 -0.1293604 0.00176639 0.13257966

-17 -0.001642338 -0.5911756 0.00012405 0.00911497

-16 0.002236608 0.80508868 0.00236066 0.16994855

-15 -0.003523466 -1.2683057 -0.0011628 -0.082087

-14 0.003779613 1.36050826 0.00261681 0.18127746

-13 0.002907439 1.0465607 0.00552425 0.37579231

-12 0.002455038 0.88371483 0.00797928 0.53335802

-11 -0.001762081 -0.6342783 0.0062172 0.40859054

-10 -0.001741159 -0.626747 0.00447604 0.28937926

-9 0.001557914 0.56078613 0.00603396 0.38395574

-8 -0.004103646 -1.4771469 0.00193031 0.1209552

-7 -0.000538957 -0.1940029 0.00139136 0.08589195

-6 -0.004509199 -1.6231298 -0.0031178 -0.189703

-5 -0.002930091 -1.0547148 -0.0060479 -0.3628355

-4 0.005324828 1.91672347 -0.0007231 -0.0427913

-3 0.005121404 1.84349884 0.0043983 0.2568305

-2 0.000543066 0.19548181 0.00494136 0.28481856

-1 -0.001721256 -0.6195828 0.00322011 0.18327115

0 -0.028259681 -10.172346 -0.0250396 -1.4076312

1 -0.008455158 -3.0435158 -0.0334947 -1.8603974

2 -6.71168E-05 -0.0241593 -0.0335618 -1.8423219

3 0.003409487 1.22727769 -0.0301524 -1.636247

4 0.002084938 0.75049347 -0.0280674 -1.5060874

5 -0.000975272 -0.3510586 -0.0290427 -1.5413877

6 -0.000292146 -0.1051607 -0.0293348 -1.5402411

7 0.00299704 1.07881341 -0.0263378 -1.3683991

8 0.001281581 0.46131758 -0.0250562 -1.2884614

9 -0.000786165 -0.2829879 -0.0258424 -1.3155322

10 0.004240392 1.52637005 -0.021602 -1.0888364

11 -0.001243413 -0.4475785 -0.0228454 -1.140384

12 0.001092902 0.39340057 -0.0217525 -1.0755367

13 -0.004880823 -1.7568995 -0.0266333 -1.3046152

14 -0.004431746 -1.59525 -0.0310651 -1.5078042

15 0.00017653 0.06354353 -0.0308885 -1.4857896

16 0.001034842 0.37250129 -0.0298537 -1.4233597

17 0.003312466 1.19235418 -0.0265412 -1.2544722

18 -0.001712912 -0.6165791 -0.0282542 -1.3240675

19 -0.004225915 -1.5211589 -0.0324801 -1.509368

20 -0.000321233 -0.1156308 -0.0328013 -1.51175

21 -0.003284384 -1.182246 -0.0360857 -1.6496543

22 0.003047475 1.0969681 -0.0330382 -1.4983044

23 -0.004867669 -1.7521646 -0.0379059 -1.7055734

24 0.0018053 0.64983503 -0.0361006 -1.6118007

25 -0.000176711 -0.063609 -0.0362773 -1.6073732

26 -0.006028262 -2.1699313 -0.0423056 -1.860432

27 -0.001402589 -0.5048756 -0.0437081 -1.9079269

28 -0.00045789 -0.1648219 -0.044166 -1.9138931

29 0.002892277 1.04110321 -0.0412738 -1.7757376

30 0.002297942 0.8271664 -0.0389758 -1.6650215

31 -0.00024129 -0.0868545 -0.0392171 -1.6636543

32 -0.000774734 -0.2788731 -0.0399918 -1.6848598

33 -0.00441631 -1.5896936 -0.0444081 -1.858235

34 0.001635073 0.58856023 -0.0427731 -1.7778441

35 0.005470861 1.96928923 -0.0373022 -1.5402161

36 -0.00015978 -0.0575142 -0.037462 -1.5367363

37 0.003974263 1.4305745 -0.0334877 -1.364873

38 0.000341858 0.12305509 -0.0331459 -1.3423623

39 -0.005901759 -2.1243951 -0.0390476 -1.5714607

40 -0.001298991 -0.4675845 -0.0403466 -1.6136841


46/48

45

AAR and CAAR of the target companies for (-40, +40)

T AA Rt T-TEST CA ARt T-TEST

-40 0.005471969 1.34716247 0.00547197 1.34716247

-39 0.00174024 0.42843545 0.00721221 1.25553733

-38 -0.002372271 -0.5840373 0.00483994 0.68794785

-37 0.003155413 0.77684163 0.00799535 0.98420113

-36 0.002449084 0.60294822 0.01044443 1.14994289

-35 0.00136327 0.33562811 0.01180771 1.18676904

-34 -0.002836276 -0.6982724 0.00897143 0.83481247

-33 0.000295118 0.07265599 0.00926655 0.80658333

-32 0.00783357 1.92857286 0.01710012 1.40331168

-31 0.004064731 1.00070981 0.02116485 1.64775058

-30 0.000154962 0.03815061 0.02131981 1.58257137

-29 0.001932777 0.47583674 0.02325259 1.65255897

-28 -0.004992307 -1.2290729 0.01826028 1.2468438

-27 0.00049756 0.12249585 0.01875784 1.23422715

-26 0.001201829 0.29588226 0.01995967 1.26877318

-25 -7.39413E-05 -0.0182039 0.01988573 1.22393338

-24 -0.004063042 -1.000294 0.01582268 0.94478287

-23 -0.001247148 -0.3070396 0.01457554 0.84579399

-22 -0.006525713 -1.6065871 0.00804982 0.45465906

-21 0.003608576 0.88840731 0.0116584 0.64180075

-20 -0.005378816 -1.3242288 0.00627958 0.33736298

-19 0.005161225 1.27065935 0.01144081 0.60051196

-18 0.00227459 0.55998906 0.0137154 0.70407807

-17 -0.003332268 -0.8203822 0.01038313 0.5217939

-16 -0.005742679 -1.4138093 0.00464045 0.22848966-15 0.001365313 0.336131 0.00600576 0.28997325

-14 0.005635462 1.38741324 0.01164123 0.55156052

-13 0.006010918 1.47984796 0.01765214 0.82128665

-12 0.003347855 0.82421962 0.021 0.96005606

-11 0.002248928 0.5536712 0.02324893 1.04500558

-10 -0.003068526 -0.7554506 0.0201804 0.89232955

-9 -0.004640373 -1.1424289 0.01554003 0.67632143

-8 -0.002286158 -0.562837 0.01325387 0.56801796

-7 0.000500575 0.1232383 0.01375445 0.58073761

-6 0.001417771 0.34904579 0.01517222 0.63138074

-5 -0.001217032 -0.2996253 0.01395518 0.57261226

-4 0.002231782 0.54944985 0.01618697 0.65515025

-3 0.01333114 3.28203797 0.02951811 1.17888924

-2 0.003717582 0.91524408 0.03323569 1.31023348

-1 0.017643546 4.34372382 0.05087923 1.98055494

0 0.172965694 42.5830045 0.22384493 8.60660074

1 0.006787782 1.67110678 0.23063271 8.76138133

2 0.000423189 0.10418642 0.2310559 8.67479379

3 0.000876435 0.21577259 0.23193234 8.60817897

4 0.00694686 1.71027083 0.2388792 8.76694731

5 0.001317725 0.32441506 0.24019692 8.71896319

6 0.000452151 0.11131663 0.24064907 8.64194676

7 0.002588994 0.63739301 0.24323806 8.64345244

8 0.001203678 0.29633745 0.24444174 8.59713322

9 0.001113275 0.27408085 0.24555502 8.54948856

10 0.004250539 1.04645436 0.24980556 8.61178802

11 -0.001850282 -0.4555271 0.24795527 8.46541015

12 -0.002311067 -0.5689694 0.24564421 8.30701353

13 -0.003687065 -0.9077308 0.24195714 8.10621078

14 -0.005920239 -1.4575234 0.2360369 7.8356475

15 -0.004248902 -1.0460514 0.231788 7.62558671

16 -0.000339122 -0.0834895 0.23144888 7.54734116

17 -0.000804299 -0.198013 0.23064458 7.4559946

18 -0.000110983 -0.0273233 0.2305336 7.38898099

19 -0.007156006 -1.7617611 0.22337759 7.09970504

20 0.000695368 0.17119508 0.22407296 7.06318954

21 -0.000364631 -0.0897697 0.22370833 6.9945960222 -0.003693957 -0.9094276 0.22001437 6.82428419

23 -0.003505919 -0.8631339 0.21650845 6.66286783

24 0.004561937 1.12311856 0.22107039 6.75072206

25 -0.003253757 -0.8010533 0.21781663 6.60078217

26 -0.002325555 -0.5725363 0.21549108 6.48139098

27 -0.000658719 -0.1621722 0.21483236 6.41389091

28 0.014982888 3.68868754 0.22981525 6.81130961

29 -0.000431552 -0.1062451 0.2293837 6.74978366

30 -0.001999839 -0.4923471 0.22738386 6.64365057

31 -0.000348827 -0.0858789 0.22703503 6.58723186

32 0.001508716 0.37143592 0.22854375 6.58543154

33 -0.001605064 -0.395156 0.22693868 6.49484808

34 -0.000530569 -0.1306226 0.22640811 6.4363208

35 0.00615008 1.51410892 0.23255819 6.56751657

36 -0.000624944 -0.153857 0.23193325 6.50719736

37 0.000118962 0.02928754 0.23205221 6.46866616

38 0.000654681 0.1611781 0.23270689 6.4457288

39 -0.001097789 -0.2702683 0.2316091 6.37509939

40 -0.002276848 -0.5605448 0.22933226 6.27334196


47/48

46

AR and CAR of the Bank of America for (-40, +40)

T ARt T-TEST CA Rt T-TEST

- 40 0. 0075858 1.102328 0. 0075858 1. 102328

-39 -0.0095406 -1.3863857 -0.0019548 -0.2008591

-38 -0.0217437 -3.159664 -0.0236984 -1.9882336

-37 -0.0241939 -3.5157219 -0.0478924 -3.4797218

-36 0.0039076 0.5678253 -0.0439848 -2.8584186-35 0.0022839 0.3318784 -0.0417009 -2.4738784

-34 -0.0047051 -0.6837206 -0.0464061 -2.5487884

-33 -0.0065588 -0.953091 -0.0529649 -2.7211418

-32 0.0049654 0.7215468 -0.0479995 -2.3250015

-31 0.0009808 0.1425211 -0.0470187 -2.160621

-30 0.0183072 2.6602938 -0.0287115 -1.2579625

-29 -0.0038582 -0.5606463 -0.0325697 -1.366252

-28 0.0067151 0.9758062 -0.0258545 -1.0420126

-27 0.010751 1.5622682 -0.0151036 -0.5865747

-26 -0.003516 -0.5109273 -0.0186196 -0.6986058

-25 0.0027702 0.4025477 -0.0158494 -0.5757853

-24 0.0004144 0.0602186 -0.015435 -0.5439886

-23 0.0074496 1.0825281 -0.0079854 -0.2735076

-22 0.0060736 0.882585 -0.0019118 -0.0637338

-21 0.0089081 1.2944783 0.0069963 0.2273341

-20 -0.009402 -1.3662382 -0.0024056 -0.0762823

-19 -9.872E-05 -0.0143449 -0.0025043 -0.0775867

-18 -0.0037542 -0.5455414 -0.0062585 -0.1896346

-17 -0.0022815 -0.3315286 -0.00854 -0.2533148

-16 -0.0035561 -0.5167467 -0.0120961 -0.3515461

-15 0.0074218 1.0784917 -0.0046743 -0.1332097

-14 -0.0054414 -0.7907175 -0.0101157 -0.2828933

-13 0.0040152 0.5834604 -0.0061005 -0.167532

-12 -0.0001334 -0.0193825 -0.0062339 -0.1682174

-11 0.0058673 0.8526065 -0.0003666 -0.0097261

-10 0.0015391 0.2236524 0.0011725 0.0306012

-9 0.005755 0. 8362901 0. 0069275 0.1779559

-8 -0.0034212 -0.4971485 0.0035063 0.0886964

-7 -0.0044694 -0.6494624 -0.000963 -0.0239996

-6 0.0054794 0.7962354 0.0045164 0.1109341

-5 -0.0080981 -1.1767724 -0.0035817 -0.0867462

-4 -0.0061167 -0.8888466 -0.0096985 -0.2316914

-3 0.0123646 1.7967521 0.0026661 0.0628491

-2 0.0062478 0.9078931 0.0089139 0.2074174

-1 0.0046491 0.6755868 0.0135631 0.3116279

0 -0.1033181 -15.013592 -0.089755 -2.0369251

1 -0.0226976 -3.2982894 -0.1124527 -2.521467

2 0. 01789 2. 5996759 -0.0945626 -2.0955283

3 0.0012476 0.1813006 -0.093315 -2.0442465

4 0.0107482 1.5618606 -0.0825668 -1.7885766

5 0.0019187 0.2788088 -0.0806482 -1.7279206

6 -0.001628 -0.2365645 -0.0822761 -1.7439461

7 0.0096283 1.3991225 -0.0726479 -1.5237385

8 0.0032039 0.4655726 -0.069444 -1.4415996

9 -0.0054145 -0.7868034 -0.0748585 -1.5383816

10 -0.0025111 -0.3648973 -0.0773696 -1.5743206

11 -0.0011413 -0.1658534 -0.0785109 -1.5821091

12 -0.0058276 -0.8468261 -0.0843384 -1.683433

13 -0.0054069 -0.7857053 -0.0897454 -1.7746938

14 -0.0030496 -0.4431455 -0.092795 -1.8182399

15 0.003078 0.4472734 -0.089717 -1.7421631

16 -0.0009896 -0.1438 -0.0907066 -1.7458601

17 -0.0012527 -0.1820413 -0.0919593 -1.7546473

18 0.0018064 0.2624975 -0.0901529 -1.7055396

19 0.0031662 0.4600982 -0.0869867 -1.6318687

20 -0.0063809 -0.9272379 -0.0933676 -1.7371581

21 0.0003196 0.046436 -0.093048 -1.7171944

22 0.0017401 0.2528548 -0.091308 -1.6716547

23 -0.0005818 -0.0845468 -0.0918898 -1.6691118

24 0.0025563 0.3714717 -0.0893335 -1.6101473

25 0.0058835 0.8549621 -0.0834499 -1.4926641

26 -0.013913 -2.0217571 -0.0973629 -1.7284799

27 -0.0037586 -0.5461763 -0.1011215 -1.781957

28 0.001256 0.1825189 -0.0998655 -1.7470245

29 0.0054741 0.795465 -0.0943914 -1.6394246

30 -0.0009009 -0.1309151 -0.0952923 -1.6433751

31 0.0030269 0.4398475 -0.0922654 -1.5800864

32 -0.005853 -0.8505286 -0.0981184 -1.6687734

33 -0.0030563 -0.4441237 -0.1011747 -1.7090879

34 0.0121328 1.7630619 -0.089042 -1.4940749

35 0.0082163 1.1939478 -0.0808257 -1.3472577

36 0.0036076 0.5242337 -0.0772181 -1.2787387

37 0.003012 0.4376909 -0.074206 -1.2209565

38 0.0014091 0.2047605 -0.072797 -1.1901669

39 -0.0027594 -0.4009769 -0.0755563 -1.2275356

40 0.0005638 0.0819353 -0.0749925 -1.2108307


48/48

AR and CAR of the FleetBoston Financial Corp. for (-40, +40)

T ARt T-TEST CA Rt T-TEST

-40 -0.0074656 -0.6719408 -0.0074656 -0.6719408

-39 -0.0119621 -1.0766551 -0.0194277 -1.2364441

-38 -0.0076323 -0.6869505 -0.02706 -1.4061634

-37 0.0028469 0.2562387 -0.0242131 -1.0896539

-36 -0.0007996 -0.0719714 -0.0250127 -1.0068026-35 -0.006636 -0.5972707 -0.0316487 -1.1629156

-34 0.0080945 0.7285466 -0.0235542 -0.8012859

-33 0.0005598 0.0503831 -0.0229944 -0.7317212

-32 0.0017222 0.1550053 -0.0212722 -0.638205

-31 0.0022328 0.2009642 -0.0190394 -0.5419039

-30 -0.006391 -0.5752248 -0.0254305 -0.6901219

-29 0.0062099 0.5589198 -0.0192206 -0.4993952

-28 -0.0015513 -0.1396282 -0.0207719 -0.5185293

-27 0.0123439 1.1110194 -0.008428 -0.2027349

-26 0.0036235 0.3261317 -0.0048045 -0.1116537

-25 -0.0028609 -0.2575001 -0.0076655 -0.1724832

-24 0.0026448 0.2380436 -0.0050207 -0.1095993

-23 0.0001485 0.0133627 -0.0048722 -0.1033617

-22 0.0044827 0.4034665 -0.0003895 -0.0080433

-21 0.0099139 0.8922997 0.0095243 0.1916846

-20 -0.0027085 -0.2437766 0.0068159 0.1338686

-19 0.0083023 0.7472496 0.0151181 0.2901049

-18 0.0068399 0.6156302 0.0219581 0.412096

-17 -0.0032602 -0.2934327 0.0186979 0.3435226

-16 -0.0100428 -0.9039038 0.0086551 0.1558013

-15 0.0024866 0.2238054 0.0111417 0.1966676

-14 0.0038762 0.3488795 0.0150179 0.2601331

-13 0.0052309 0.4708098 0.0202488 0.3444203

-12 -0.0016274 -0.1464776 0.0186214 0.3112297

-11 0.005573 0.5016003 0.0241944 0.3975779

-10 -0.00034 -0.0306013 0.0238544 0.3856166

-9 0.0017711 0.1594064 0.0256255 0.4077229

-8 -0.0007554 -0.0679875 0.0248701 0.3896626

-7 0.0057775 0.5200034 0.0306476 0.4730694

-6 0.0045925 0.4133506 0.0352401 0.5361313

-5 -0.0040325 -0.3629455 0.0312076 0.4681416

-4 -0.0109684 -0.9872129 0.0202392 0.2994753

-3 0.0046981 0.4228513 0.0249373 0.3641041

-2 -0.0023609 -0.2124921 0.0225764 0.3253798

-1 -0.0029329 -0.2639755 0.0196435 0.2795486

0 0.2295539 20.661066 0.2491974 3.5028349

1 -0.0287653 -2.5890297 0.2204321 3.0613873

2 0.0

[peace)final dissertation

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