Impact Of Mergers & Acquisitions On Shareholder Wealth In EU Banking Sector Between 2005 And 2017

Background of the Study

Merger and acquisition (M&As)within the financial industry is one of the highly discussed event around the world owing to its far reaching impact and the importance to the financial sector of the world economy. when it comes to the European union, then it can be seen that, during the last two decades, out of total mergers around the world 10.6% has taken place within this region and additionally involvement of large European institutions into cross sector or cross border merger has revamped the purpose and scope of the merger and acquisition during the recent years that has brought it into limelight (Fuller 2016). M&As is such a phenomenon that not only takes within the banking industries, rather it takes place in most of the industries ranging from automobile to entertainment, however, impact of the same are not far reaching due to their constrained potential to influence the world financial market (Boschma and Hartog 2014). Contrary to this, when M&As takes place within the financial market, it can be seen that world economy face large amount of consequences either in positive sense or in negative form due to the potential of the banking industry to determine the growth path of the world economy (Kyriazopoulos and Drymbetas 2015). Under this situation, around the world, it has become one of the main topic for the researches to determine how M&As influence the market and trace its impact on the different economies.

This report is aimed to trace the impact of mergers & acquisitions on shareholder wealth in EU banking sector between 2005 and 2017. for this purpose this report will focus on the what caused the merger, why it took place in the EU banking sector and how did it happened within the selected region. In this chapter of the research, researcher will describe the research aim and objective while portraying the main research question. Moving forward, researcher in this report will describe the rationale of the study in order to make the research work valid and essential. Next to this, in this chapter researcher will focus on the explanation of the structure of study in order to provide a clear idea regarding the future growth of the study. In order to conclude the first chapter of the research work, researcher will provide a chapter summary portraying the finding from the discussion above and then it will move forward to the next subsequent chapters.

This research describes the M&As involved within the EU banking sector over the last two decades and has been prepared in order to trace to impact of the same on the shareholder wealth. Until 1980 it has been observed that the financial industries within the EU member states used to operate under a highly regulated government ownership and regulated market that played a crucial role in shaping the economic growth of the respective economies (Karolyi and Taboada 2015). With the presence of the controlled market environment it can be seen that corporate control over the banking industry in the EU market has been low, thus the biasness within the ownership structures of cross shareholdership used to be limited as well. Predominant nature of the local banking services nature prevailed until 1980 within the EU member market, thus the M&As was almost nonexistence at the same time within the region (Pohl and Tortella 2017). However, the scenario, changed since the early 2000s when the smaller financial institutions started to merge in order form larger banks. considering the two decades between 1980 to 2000s, it can be seen that a concentration and restructuring within the small EU countries took place with the view to bring in larger nationalised institutions, which are ready to compete in the international market as a joint outcome of the regional cooperation between the EU member countries that introduced the M&As within the selected region (Lebedev et al. 2015).

Research Aims and Objectives

Apart from United Kingdom, France and Italy, none of the EU member countries has large banks that can compete against the world banks from different regions, thus still 1980s to 1990 no impact of the M&As can be observed in this member countries, however, since 2000s, many smaller banks started to merge with each other with two objective, which were controlling the domestic market with larger market share and dominate the world financial market with substantial market share (Rao-Nischolson and Salaber 2016). With the introduction of M&As in the UK and other large nations in EU, M&As got pace and it can be seen that it has revamped the persisting characteristics of the merger and acquisition which was characterised by geographic expansion into different parts of the world. new M&As phenomenon was more focused to control the financial market in the emerging markets like Central and eastern Europe, South-East Asia, Latin America and other places around the world. These recent changes in case of the M&As framework within the final market of the EU has shaped the future of the merger and acquisition and it has caused far reaching impact on the shareholders of the banks as well (Lazarides and Drimpetas 2016).

Research aim is as follows:

Impact of mergers & acquisitions on shareholder wealth in EU banking sector between 2005 and 2017

Objectives of the research is as follows:

• To determine the shareholder wealth in EU banking due to mergers & acquisition
• To determine how merger and acquisition can impact on the profitability of the banks

Research question are as follows:

• How and to which extent merger and acquisition impact the profitability?
• What is the impact of the merger and acquisition on the shareholder value in relation to the financial impact of the same?

M&As around the world has become one of the main phenomenon for discussion by the different researchers. Owing to the magnitude of the M&As in the financial institutions within the EU zone, it has become the epicentre of all the studies regarding this phenomenon. In addition to this, the researcher has also found that since last two decades there has been large amount of merger and acquisition within the small nations around the EU member countries that has forced all other nations to consider the same growth path of the future financial development (Apergis et al. 2016).

Moreover, it has also been found that revamping of the financial merger has caused the reshaping in the persisting view point regarding the mergers and has caused the EU members countries to rethink the definition of the same. Under this situation, it has become one of the vital elements to determine the impact of the M&As on the shareholder wealth for the better understanding regarding the far reaching impact of the financial mergers (Chiaramonte and Casu 2017). Thus, present research which is aimed to trace the shareholder impact due to the merger and acquisition in the EU region is highly important.

This report is divided into five chapters which defines the research objective, analyse the same and provide recommendations through statistical analysis. First chapter of the research is meant to provide an introduction to the research work and provide general perspective of the research while mentioning the rationale of the study in order to provide requirement of the same. In this chapter, the researcher has mentioned the research aim and objectives while providing research question in order to provide better idea about the research work and its desires. In the second chapter, the researcher will provide literature review regarding the M&As in the EU. In order to doing so, the researcher will use previous research work as the source of the literary evidences.

Rationale of the Study

In this section, researcher will describe the motive of the merger and acquisition in the banking sector and portray the different type of merger took place within the same industry in order to provide better understanding regarding the M&As. in addition to this, researcher in this section will provide various other details regarding the merger and acquisition while culturing the previous research works in the same section. Moving forward, there will be research methodology chapter, where it will explain the methodologies of the research work. In this section, the researcher will portray how to determine the performance and impact of the M&As in the EU banking industry while considering the short run and long term events. In addition to this, it will portray the research philosophy and mention the data analysis process in order to provide clear idea to the readers regarding the analysis process. In the next section there will be analysis of the research that will determine the researcher objective with utilisation of the data and statistical software. Moving forward, there will be fifth chapter, where the research will provide discussion regarding the finding and provide recommendation depending upon the same.

In this section of the research, researcher will demonstrate extensive review of the available academic paper in order to explain the motives of the M&A in the banking sector. Throughout this chapter, researcher will portray the different views regarding the M&A in the banking sector and next to this it will portray the different types of bank mergers. In section 2.1, it will demonstrate the motive of the M&A in the banking sector with the idea of horizontal, vertical and conglomerate mergers. In section 2.2, it will determine the M&A factor depending upon the firm specific, macro determinants and deal specific view of the same. In section 2.3, this chapter will portray the market performance analysis of the M&A in short and long term and in section 2.4 efficiency and operating performance analysis of the M&A in the banking sector will be demonstrated.

As per Greve and man (2017), it can be seen that there are various motives that leads to M&A and they can be classified into synergy motives, agency motives and behavioural motives. Synergy motives tries to gain synergy motives, whereas agency motives aims to enhance the gain of managers at the cost of shareholder and next to this behavioural motives aim to please the gain through the expense of the shareholders. These three key motives of activity of M&A activities were studied to valuation of motives for the M&A and to determine the count of M&A for each different motive associated with the same. As per the initial hypothesis, it has been argued by Berkovitch and Narayanan (1993) that the Cumulative Abnormal Return (CARs) and eventually different researchers have showcased that aggregate values of the involved firms enhance the scope of M&A of the firm. Next to this it can be seen that synergy motive of the M&A can be accounted for the primary motive of the M&A and it is reason for the 75% M&A in the banking sector in the EU region as per the previous literatures (Cartwright and Cooper 2014). However, it has failed to determine the scenario in the case where the particular M&A can be motivated through the several factors. Besides this, it can be seen that, one of the main motive of the M&A is to enhance the operational attributes of the merging banks that would enhance the wealth of stakeholders as well. However, different type of motives are there that influence the M&A in the banking sector as mentioned below:

Structure of the Study

This type of mergers occurs between two organizations offering comparative or good product offerings or administrations to a similar market. These mergers happen when consolidating elements are in rivalry. At the end of the day, organizations are immediate contenders of each other in this sort of mergers. As per Markdies (2012) when bidder also, target organizations are from a similar industry line, these kinds of mergers are called even mergers. As indicated by Martz (2013), horizontal mergers help to wipe out the rivalry with the goal that the organization expands its piece of the pie, power and incomes. Furthermore, Sudarsanam (2004) likewise demonstrate that operational effectiveness as a consequence of changes in the extent of economies and the size of economies, and expanded piece of the pie, showcase power and system externalities will prompt new development open doors for the organizations.

Vertical reconciliation is the level of how much a firm includes tasks with its providers and purchasers. In spite of horizontal activities and coordination, which is a merger between contenders; vertical joining happens between players that are reciprocal. At the end of the day, vertical mergers happen between a client and an organization or a provider and an organization.

The reason for vertical mergers is to deal with the esteem chain. As indicated by Sudarsanam (2004), an organization may go into arm’s-length exchanges with its providers to acquire their data sources or with its merchants to offer their yields. Vertical mergers additionally offer to the organization the capacity to control its expenses. Likewise, to the advantages with respect to cost lessening, vertical mergers additionally give an expanded upper hand to the organization over its rivals (Sudarsanam, 2004). Finally, Sudarsanam (2004) additionally shows that vertical mergers are far less incessant than horizontal acquisition and merger activities.

When two organizations work in totally unexpected ventures in comparison to each other, despite the phase of generation, a merger between these organizations is known as combination mergers (Linder and Crane, 1993). As it were, aggregate mergers happen between organizations that are neither contenders nor potential or genuine purchasers or then again providers of each other. There are two kinds of aggregate mergers, specifically unadulterated combination mergers and blended combination mergers. In the event that there is no monetary relationship between the bidder and target firms, at that point this merger is called unadulterated combination mergers. Then again, blended combination mergers happen between the firms that are searching for item or market augmentations. As indicated by Lubatkin, (2013), the basic role of the aggregate mergers is broadening, which makes an incentive by expanding market intensity of the organization and effective inside capital market. Because of combination mergers, consolidating organizations diminish their levels of hazard introduction.

In this section of the literature review, key motives that emphasise on the decision making process of M&A’s will be discussed. Depending upon determinants of the merger and acquisition, it can be seen that there are firm specific factors, macro determinants and deal specific factors.

Operating performance of the target and bidder: As per the determinant of the M&A it can be seen that firms which have low or worse operating performance, they tend to merge more quickly and frequently with the other organisation so as to shelve the risk. In addition to this, it can be seen that poor performing firms tend to go for M&A because they are also the first target of the market competitors. As per the number of studies, it can be seen that European banking organisation who are less efficient and have low amount of market debt are often merged with the competitor so as to make large banks.

Capitalisation: It acts as one of the main force of determination of the M&A’s because as per the studies, low capitalised targets reflect low management abilities and performance of the same can be enhanced under the post-merger situation. Thus, capitalisation, can be considered as one of the main parameter that determine the M&A’s.

Prospects of growth in future: Acquisition and growth rate is directly related with the M&A of the same. However, during present date, as per the research of Lebedev et al., (2015) it can be seen that poorly performing banks faces higher amount of merger and acquisition because they have higher growth prospect and lower risks.

Size: Smaller banks are likely to face higher number of merger and acquisition because they have smaller markets and lower growth rate that provides them low growth prospect in future. However, it is also true that if the small firms with higher potential of growth and small in size, then they have good amount of M&A prospect.

Previous researches regarding the M&A has contested the characteristics of deal specific factors in order to trace the outcome whether they are sensitive to the parameters of the deal or not. List status, size of bidder and industrial relatedness are the various deal specific factors that largely influence the M&A plans of the EU banking sector.

Listed status: as per the existing literature, different reaction of the market players of takeover can be perceived and consequently, scholars has distinguished the plenty of reasons to determine these difference. For instance, bargaining power hypothesis, managerial hypothesis along with the liquidity hypothesis has influenced the M&A in the EU banking by a large extend. Information regarding privately owned targets makes the process of asset estimation by the publicly owned firms that creates the method of the M&A complicated. In this part, bidder often gets benefited through the market illiquidity and depending upon the bargaining power of the different clients get information regarding the assets of the banks that going to merged. It makes the private firms for the M&A less lucrative to the external bidders and enable the public bidders to attain additional benefit.

Method of payment: as per the existing literature, it can be seen that theory of cash financed mergers outperform the stock finance deals during the short run making it a problematic situation for the ideal related determinants that largely influence the M&A. In this regard, it is important to identify that payment method acts as an important signalling mechanism for the market and the hypothesis of the previous researches has showcased that asymmetry in availability of information that makes the situation of M&A hard. As per the Grigoriev and Petrunina (2015), abnormal returns demonstrated significantly so as to cash financed deals and allows the bidders to look into the financing method of the targeted bank that guide the bidder to take into account of the financial performance as well as the market share and performance of the selected bank.

Industrial relatedness: intuitive argument of the M&A highlights that the synergetic gains through the merger and acquisition that enhance the performance and cost of integration are lower. As per the research of Rani et al. (2014), CARs approximation depicts 1.6% insignificant and focused abnormal returns are diversifying mergers around the announcement and as per the long run research CARs for the non-conglomerate mergers is as high as 6.2%, whereas the CARs for the conglomerate deals is as low as -11.33% depicting the industry relatedness factors can sufficiently influence the M&A.

Market based assessment of the M&A is event study approach and it generally calculate the abnormal return within a particular date so as to obtain CARs so as to measure the reaction of the market so to determine the market performance in case of a particular event. As per the Efficient Market Hypothesis (EMH) all publicly available information is completely reflected in the price. Thus, in case market as a whole is efficient and rational it changes the prices of stock that will be reflected by the company value allowing the researcher to determine the impact of the merger event. As per the research work of the Cartwright and Cooper (2014), the formula depending upon which CARs short run M&A event studies was discussed is as follows:

[R_mt and R_it is the return in period t of stock I for the market m. ?_it is the zero mean disturbance]

As per the estimation method, it has been observed that the residuals are distributed more closely in case of the normal distribution compared to the daily distribution and residuals are correlated with the return of the market index. Previous studies has showcased that shot run performance of the M&A use to face technical problems and these are encountered while implementing the confounding events. Through exclusion of the confounding events, though previous literatures have tried to mitigate the issue, due to the various fluctuation, it can be seen that various researchers has showcased that the performance of the M&A under the short run situation is hard.  

Long run analysis of the performance of M&A is to investigate the connection between the market and post-merger performance. As per the long run study of impact due to the M&A, it is important to determine to which extent various external factors influence the outcome of the mergers. Utilising the BHAR methodology previous literatures has showcased that as per the long run performance estimation, buy and hold methodology is being utilised by the large amount of bidders. It allow the bidders to rebalance the biasness within the firm and biasness exist due to the new listing is also tried to be reduced by the means of the addition of the constantly adding the market index.

Cost profit analysis of the M&A is another important factor in the literature in this field. As per the study of Ahmed et al. (2018), it has been found that during the post-merger efficiency of the EU banking sector has reduced by 20% and thus the goal of his study was to determine how to close each firm is to gain full efficiency. As per the efficient frontier methodology, it can be observed from the previous studies that managerial synergies are often exaggerated and agency theory also showcase that personal gain and reputation makes the M&A inefficient by a large extent. Though, considering the studies from 1990s, it can be seen that mixed result was there in the EU banking sector where the banks irrespective of their size and performance has showcased good amount of efficiency in case of post-merger. On the other hand, as the EU economy has galloped towards the deteriorating financial market during the 2008, M&A has showcased less amount of efficiency. Though the studies regarding the performance analysis of the EU M&A is limited, however, most of the available analysis has showcased that there is there is significant amount of efficiency in small universal banking institution, however, they are limited to small changes during the long run because during short run they have faced large amount efficiency and performance deficiency.

Through this method of evaluation of M&A performance researchers try to analyse the performance of the firms that are margining with each other. Majority of the study utilise the Return on Equity and Return on Assets studies for the post-merger efficiency and operating performance study. As per the several studies regarding the EU banking performance, it has been observed that post-merger performance of the banks has declined and weak increase in the profitability is one of the major concern that has restrained the banks to merge post 2005. As per the substantial array of literatures, it can be observed that the performance of the EU banking industry has faced a wide amount of downfall depending upon the sample size, time period of the merger and location of the banks. Contrary to this, some other papers has also showcased that M&A has showcased that there has been large amount of growth in the profitability for the firms who have good growth prospect and had less amount of risk burden. As per the finding of the Nurullah and Staikouras (2015), it has been observed that the new merger that has taken place during the 2008 to 2012 in the US market has showcased good amount of growth in performance due to the governmental support in case of the mergers. On the other hand EU market showcase a completely paradigm shift in their result due to the different pictures of the market scenario. Depending upon the pre-merger factors during 1997 to 2002, M&A in the EU region has declined the performance and showcased that the domestic as well as the cross-border mergers has reduced by 2.44% during the same time.

This chapter of the research work explain the methodology of the data analysis. Through the next consecutive section of this chapter, researcher will explain the population of the study, sample size and method of data collection. Next to this, through analysis of the data collection procedure, this section will highlight the data analysis tool utilising which data analysis in the next chapter of the research work will be done.

For the purpose of the research only the banks those have been merged during 2005 to 2017 in the EU region will be chosen. Considering the population of the M&A in the EU banking sector, there are approximately 1027 M&A within the given time frame (Grigorieva and Petrunina 2015). These banks has been chosen as the population of the present research work.

A researcher can take the help of two types of sampling method:

• Probability sampling
• Non-probability sampling

As far as the present research is considered, it will be performed utilising the probability sampling because the number of banks which have performed M&A during 2005 to 2017, will be chosen as the sample for the research work. As per the same sample of the following research work is considered, it can be seen that there are 430 Public Ltd. Companies that has been found as per the parameters through applying the elimination rule. As the elimination criteria, researcher has considers only those banks which have M&A deal between 5 million to maximum.

As the method of data collection, researcher has utilised the probability sampling and secondary data collection methodology. Data regarding the stock price of the bank has been retrieved from the Thomson Reuters and each company’s time series data from DataStream.

Following research will utilise the Event Study Market Model Analysis method in order to determine the impact of the shareholder’s wealth. Through this methodology, depending upon the basic knowledge regarding the stock prices demonstrate the discounted value of the future stream of profit of the firm. Thus, in case of observing the stock market response in order to announce the particular event of M&A, the different in the equity value of the firm impacted by the event study analysis. Utilising the expected and actual return of the average accumulative abnormal return over the chosen time will be calculated.

As the initial step to analyse the sample of the firm will be included within the analysis and then it will determine the event window. For the requirement of the present study, M&A in the EU banking sector within the time frame of 2005 to 2017 has been selected. In order to reduce the impact of the other contemporaneous event on the prices of the stock and any firm with the announcement connected to the dividends, earning will be excluded from the analysis in the present research work. Approval of the M&A of dates were sourced by the Thomas Reuters.

As the second step of the event study, three event windows such as 21 days, 11 days and 3 days with the symmetric event windows of  +,- 10 days, +,-5 and +,-1 days have been chosen. In order to reduce the missing out of any official announcement made regarding the short term stock price reaction connected with the event post announcement of the M&A, these event windows have been chosen. Moreover, various other window length are chosen in order to analyse the result.

As the third step, the Normal return prediction, during the event window in absence of the vent will be done. Utilising the model of the study that estimate the expected returns will be considered as the market model. Through the liners time series model, security return, dependent variables will be regressing against the percentage change in the market index.  As per the market model for the study of the security i for the time frame t can be expressed utilising the below mentioned time series model:

[Where, R_it is the daily return of the security i for the time period t;

a_i,B_i, are the market model parameters for the security i, and security-specific intercept and the slope coefficient respectively;

R_mt is the return of the market for the time period t

is the error term for the year j, security i, at t^th period. It is assumed that  fulfils the assumptions of the linear regression model].

In addition to this, it can be seen that over the regression period   has the Mean of Zero and it has variance independent over the time. This derives the estimation of, is the elasticity of the returns on the stock against return on the index. As per the market model, zero investment portfolios on both sides of the equation is the case same as here, where the hypothesis are as follows:

H_o = There is no significant change in the shareholders’ wealth due to M&A in the EU banking sector

H₁= There is moderate of good amount of change in the shareholders’ wealth due to M&A in the EU banking sector

As the fourth step of the analysis of the abnormal return within the event window, abnormal return is defined as the difference between the predicted and actual returns.  It thus showcase the effect of the firm specific event of the M&A on the wealth of the net of the market effects on the wealth of shareholder. Announcement regarding the M&A have impact on the performance on the company value of  would have the different from zero. Below is the equation of the:

—- [2]

Through the above equation daily residual for the different firm can be computed over the vent window. Next to this for the day t within the period of the event the Average Residuals Mean Abnormal Return (MAR_t) across the members of the sample is calculated. Through the equation 3, mentioned below, Average residual can be mentioned:

=  ————- [3]

[Where,

is the Abnormal Return of the i^th security on the t^th day

N_t is the securities number that have abnormal returns on the t^th day

Lastly, through the assessment of the abnormal return for the several holding periods ranging from the t1, t2 and other dates cane be calculates according to the formula in the equation mentioned below:

=  ——— [4]

As per the null hypothesis the researcher will try to analyse the impact on the corresponding cumulative abnormal returns and stock prices with the expected value of zero. Thus, the following hypothesis for t-statistics will be used:

=  ——— [5]

Where,

is the standard deviation of the excess return on the t^th date within the vent period

Nt is the number of the securities that have abnormal returns on the t^th day

Model	Inputs (pre and post announcement of acquisition)	Output (Pre and post announcement of merger announcement)
Market model	Stock market prices Return on security	Average Cumulative Abnormal Returns

In order to assess the changes in the average abnormal earning through the post-merger and pre-merger declaration periods. Through the utilisation of the T-test based on the one-way analysis of variance techniques that compares the difference in the observations between the period and groups.

Conclusion: 

From the above discussion it can be seen that the research will be done on the secondary data sourced by the financial statement of the chosen firm. As the sample population, the researcher will choose the banks which have merged during 2005 to 2017 in EU region. The research will utilise the positivism philosophy of research and cross sectional data will be used for the data analysis section.

This chapter of the report provides the analysis of the data collected from the secondary source and demonstrate its findings regarding the M&A impact on wealth of stakeholders during 2005 to 2017. Result of the data analysis has been presented in the table formats in order to showcase the major findings. With the different presentation of data analysis under the different sub sections, this chapter will demonstrate how the M&A has impacted on the shareholder wealth.

As the chosen sample, there were 588 M&A from the EU banking sector during 2005 to 2017 and from the same data, it can be found that most of the bank mergers took place during 2007. Through the utilisation of the Excel, researcher has performed the following analysis regarding the sample data of the M&A in the EU banking sector during 2005 to 2017.

Whole study was distributed in two section where long run event window and short run event window has been utilised to understand the implication of the merger in case of the EU banking sector during the timeframe of 2005 to 2017. with the CAR model, and t-Test against the value of zero, the researcher has tried to trace the significant gain in the total investor’s wealth

t-Test: Paired Two Sample for Means
	CARit [-1,1]	CARit [-5,5]
Mean	-0.005916886	-0.089172328
Variance	0.041185602	9.354471351
Observations	588	588
Pearson Correlation	1
Hypothesized Mean Difference	0
df	587
t Stat	0.706983277
P(T<=t) one-tail	0.239928711
t Critical one-tail	1.647453612
P(T<=t) two-tail	0.479857423
t Critical two-tail	1.964013537

As per the above figure, it can be found that P value in the t-Test is lower than the critical level of the test at 1% level of significance highlighting the fact that null hypothesis need to be accepted. Thus, it demonstrate that, during short run, there has been no significant wealth generation through the merger and acquisition.

t-Test: Paired Two Sample for Means
	CARit [-1,1]	CARit [-10,10]
Mean	-0.005916886	-0.081274289
Variance	0.041185602	7.770794133
Observations	588	588
Pearson Correlation	1
Hypothesized Mean Difference	0
df	587
t Stat	0.706983277
P(T<=t) one-tail	0.239928711
t Critical one-tail	1.647453612
P(T<=t) two-tail	0.479857423
t Critical two-tail	1.964013537

As per the above figure, it can be found that during long run, P value in the t-Test is lower than the critical level of the test at 1% level of significance highlighting the fact that null hypothesis need to be accepted. Thus, it demonstrate that, during short run, there has been no significant wealth generation through the merger and acquisition.

In order to analyse the impact of M&A on the stock valuation of the banks, cumulated abnormal return model has been used. As per the CAR model, change in the stock value of the banks engaged in the M&A event can be traced. As the percentage change in the market index, average price is deducted that provide the unsystematic portion of the change in the value of the stock price. With the t-Test, researcher has tried to understand the significant amount of deviation in the mean value of abnormal return.

t-Test: Paired Two Sample for Means
	T-10 to T0	T0 to T+10
Mean	-0.008719758	-0.00143654
Variance	0.005777838	0.006084155
Observations	587	587
Pearson Correlation	0.086065352
Hypothesized Mean Difference	0
df	586
t Stat	-1.694724676
P(T<=t) one-tail	0.045329474
t Critical one-tail	1.647458056
P(T<=t) two-tail	0.090658948
t Critical two-tail	1.964020461

Above table showcase the long run t-Test and as per the same, it can be seen that null hypothesis is accepted depicting there is no significant change in the stock return during long run post-merger. One of the main reason of the same is the lack of wealth generation by the parties engaged in the M&A.

t-Test: Paired Two Sample for Means
	T-5 to T0	T0 to T+5
Mean	-0.002989298	-0.00271416
Variance	0.003577175	0.002728546
Observations	587	587
Pearson Correlation	-0.004400854
Hypothesized Mean Difference	0
df	586
t Stat	-0.083763624
P(T<=t) one-tail	0.466636488
t Critical one-tail	1.647458056
P(T<=t) two-tail	0.933272976
t Critical two-tail	1.964020461

as per the figure below, t-Test showcase that, null hypothesis is accepted in case of the short run too, where no moderate amount of change in the stock return can be observed.

t-Test: Paired Two Sample for Means
	T-1 to T0	T0 to T+1
Mean	0.001440879	0.000182472
Variance	0.000933818	0.000838533
Observations	587	587
Pearson Correlation	0.199395119
Hypothesized Mean Difference	0
df	586
t Stat	0.809241504
P(T<=t) one-tail	0.209352346
t Critical one-tail	1.647458056
P(T<=t) two-tail	0.418704692
t Critical two-tail	1.964020461

with the event window from T-1 to 10 to T+1, P value was greater than the critical level of the test at 1% level of significance highlighting the fact that null hypothesis need to be accepted.

Conclusion:

From the above analysis it can be found that post-merger, there has been no significant change in the wealth of the stakeholder and the stock return of the banks engaged in the M&A. In addition to this, it can also be found that the researcher has traced that during the short and medium run, there has been no significant amount of wealth generation by the event of M&A. However, moderate amount of wealth generation can be seen during the long run event window that highlight the fact that, there is possibility of wealth generation during the long run.

This section of the report is aimed to demonstrate the findings of the above analysis and while drawing the conclusion for the research work, it will provide recommendations based on the findings of the research work. Through highlighting the limitation of the research work, this section will demonstrate the brief overview of the finding and provide explanation regarding the future research work. In the section 5.5, this section of the research work will present the recommendation for the policies to gauge or enhance the situation of the M&A in the EU banking sector.

Research work are subject to limitations and the present research is same as well. The present research is limited to the EU banking sector and the bids which are lower than 5 million has been omitted from the sample population. In reality, there were more than 1027, mergers throughout the EU region in between 2005 to 2017, however, for the present research analysis, only 588 mergers has been chosen. One of the major reason for doing so is to reduce the amount of complexity in the research work that has caused it to choose a short event window as well. As the event window, researcher has chosen +, – 10, +,-5, +,-1 that makes the finding constrained in nature. As it may so happen that impact on the stakeholders wealth would have been enhanced after one year or later from the date of merger and in that case, present research work fails to trace the same. Moreover, the study is limited to EU region only that has constrained the findings and restricts it to be accepted as the generalised outcome of M&A.

Conclusion:

This study was aimed to determine the impact of M&A on the shareholder wealth and as per the analysis mentioned above, it can be found there, there is no significant impact of the M&A on the wealth of the shareholders. This lead to the conclusion that, bank mergers in the EU banking sector in between 2005 to 2017 were not wealth creating in nature for the shareholders for both the entity attached with the M&A. in addition to this, it can also be seen that, as per the literature review, there has been least or no change in the stock returns of the banks who were engaged in the M&A in EU within the time frame from 2005 to 2017. If the medium run and short run event window of M&A is considered, then it can be seen that, there has null hypothesis has been accepted, depicting no significant change in the wealth of shareholders through M&A for both the parties engaged in the business. Contrary to this, if the long run window can be considered, then it can be seen that null hypothesis is rejected and alternative is accepted in case of the stock return, depicting the moderate amount of change in the shareholder wealth through the M&A. Thus, it highlights the fact that, there is possibility that, over the years, shareholders wealth will be affected through the M&A. On the other hand, as per the CAR model, it can be seen that throughout the different event window has been no significant impact on the shareholders wealth due to M&A. It highlights the fact that, M&A in the banking sector is not wealth generator for the stakeholders and within the short span of even occurrence it has least amount of significant impact on the stock return of the banks.

From the above analysis it can be found that there is ample scope of future research, where researchers can analyse the stakeholder impact from the M&A in the EU banking sector. As the alternative way of finding the same, researches can trace the same through BHAR model while utilising the long term return to the bidder with the assumption that market evaluate over the time due to the consequences of M&A. with model selection in the long term analysis, researchers can trace the long term impact on the stakeholders wealth through M&A and considering the event from the different part of the world will allow the findings to be accepted as the generalised one.

From the above analysis it can be found that the M&A has projected least amount of impact on the stakeholder’s wealth. Though the analysis has certain degree of limitation, however, with the following recommendations, it can turned to be useful for the future researches.

As per the findings, it has been found that the stakeholders in the financial sectors are jittery about the proposed bank mergers in presence of the anticipated market reactions. as the restrictive measure to reduce the scope of the anomaly in the M&A, announcement of the M&A need not to be considered as unbiased predictor during the capital gain of short term in case of both the combined entities and bidders. Thus, it would be ideal to recommend that banks need to be aware while deciding the M&A.

Secondly, it would be ideal to recommend that regulators need to enforce the bidding firms to provide complete disclosure regarding the mergers as this can act as the reason to demonstrate the fact that there were no significant impact of the M&A announcement on the bidders.

Thirdly, regulation need to deploy non market based tools of assessment in order to help in determining the past performance of both the bank to be mergers and the bidding bank as the means of developing possible reasons to break the market scepticism pre and post the merger event.

References:

Ahmed, F., Manwani, A. and Ahmed, S., 2018. Merger & acquisition strategy for growth, improved performance and survival in the financial sector. Jurnal Perspektif Pembiayaan Dan Pembangunan Daerah, 5(4), pp.196-214.

Apergis, N., Fafaliou, I. and Polemis, M.L., 2016. New evidence on assessing the level of competition in the European Union banking sector: A panel data approach. International Business Review, 25(1), pp.395-407.

Boschma, R. and Hartog, M., 2014. Merger and acquisition activity as driver of spatial clustering: The spatial evolution of the Dutch banking industry, 1850–1993. Economic Geography, 90(3), pp.247-266.

Cartwright, S. and Cooper, C.L., 2014. Mergers and acquisitions: The human factor. Butterworth-Heinemann.

Cartwright, S. and Cooper, C.L., 2014. Mergers and acquisitions: The human factor. Butterworth-Heinemann.

Chiaramonte, L. and Casu, B., 2017. Capital and liquidity ratios and financial distress. Evidence from the European banking industry. The British Accounting Review, 49(2), pp.138-161.

Fuller, G.W., 2016. Introduction. In The Great Debt Transformation (pp. 1-24). Palgrave Macmillan, New York.

Greve, H.R. and Man Zhang, C., 2017. Institutional logics and power sources: Merger and acquisition decisions. Academy of Management Journal, 60(2), pp.671-694.

Grigorieva, S. and Petrunina, T., 2015. The performance of mergers and acquisitions in emerging capital markets: new angle. Journal of Management Control, 26(4), pp.377-403.

Karolyi, G.A. and Taboada, A.G., 2015. Regulatory arbitrage and cross?border bank acquisitions. The Journal of Finance, 70(6), pp.2395-2450.

Kyriazopoulos, G. and Drymbetas, E., 2015. Do domestic banks mergers and acquisitions still create value? Recent evidence from Europe. Journal of Finance, 3(1), pp.100-116.

Lazarides, T. and Drimpetas, E., 2016. Defining the factors of Fitch rankings in the European banking sector. Eurasian Economic Review, 6(2), pp.315-339.

Lebedev, S., Peng, M.W., Xie, E. and Stevens, C.E., 2015. Mergers and acquisitions in and out of emerging economies. Journal of World Business, 50(4), pp.651-662.

Nurullah, M. and Staikouras, S.K., 2015. The separation of banking from insurance: Evidence from Europe.

Pohl, M. and Tortella, T., 2017. A century of banking consolidation in Europe: the history and archives of mergers and acquisitions. Routledge.

Rani, N., Yadav, S.S. and Jain, P.K., 2014. Impact of corporate governance score on abnormal returns and financial performance of mergers and acquisitions. Decision, 41(4), pp.371-398.

Rao?Nicholson, R. and Salaber, J., 2016. Impact of the financial crisis on cross?border mergers and acquisitions and concentration in the global banking industry. Thunderbird international business review, 58(2), pp.161-173.