The Impact of the Brexit Referendum on Wealth
Consequences of Merger and Acquisition Announcements in the
United Kingdom and the European Union
A Bidder’s Perspective
Master Thesis MSc International Financial Management Rijksuniversiteit Groningen
Klaas Lucas Kramer S2715082
January 11, 2019
Supervisor: Dr. P.P.M. Smid
Abstract
Table of contents
1. Introduction ... 3
2. Literature review and hypotheses ... 5
2.1 The influence of the Brexit on announcements of cross-border acquisitions from a bidder’s perspective ... 5
2.3 Listing status ... 9
2.4 Industry relatedness ... 10
2.5 Relative size of the firm ... 11
2.6 Leakage and delayed effects ... 12
2.6.1 Leakage effects ... 12
2.6.2 Delayed effects ... 13
3. Data and methodology ... 14
3.1 Data ... 14
3.2 Methodology ... 18
4. Results ... 20
4.1 Abnormal returns for cross-border M&A announcements ... 20
4.2 The impact of the method of payment to the bidders’ abnormal returns ... 25
4.3 The impact of the listing status of the target firm to the bidders’ abnormal return ... 27
4.4 The impact of industry relatedness to the bidders’ abnormal return ... 28
4.5 The impact of relative firm size to the bidder’s abnormal return ... 29
4.6 Leakage and delay results ... 30
5. Conclusion ... 31
References ... 34
Appendices ... 37
Appendix A1 ... 37
1. Introduction
Since 2012, the idea of the United Kingdom (UK) leaving the European Union (EU) is
discussed and deliberated. At the 23rd of June in 2016, the inhabitants of the United Kingdom
voted with 51 percent against 49 percent in favor of leaving the European Union, causing uncertainty in economic, social and political environments. Developed countries account for over two thirds of cross-border acquisitions (Faccio and Masulis, 2005). For that reason, the Brexit referendum will most likely have large consequences for firms in the UK and Europe that engage in cross-border merger and acquisitions (M&As).
Cross-border M&As are mainly motivated by imperfections in product and factor markets and differences in regulations across countries (Harris and Ravenscraft, 1991). On the other hand, cross-border M&As result in more internal uncertainty for acquirers (Gatignan and Anderson, 1988). Moreover, cross-border M&As could be affected by differences in investor protection. According to Hagendorff, Collins and Keasy (2008) the UK could be classified as having very high standards of investor protection compared to most European countries.
difference in short-term wealth effects between EU and UK bidders? Do firm and deal characteristics have an impact on the bidder’s wealth in case of a cross-border M&A? This study addresses these questions by investigating the impact of the Brexit referendum on the acquirer’s stockholder wealth in the case of merger and acquisitions announcements. A standard market model will be used to calculate the abnormal returns of the bidder, while regressions are used to analyze the impact of firm and deal characteristics on the bidder’s wealth effect in case of a M&A announcement. The sample of this study consists of 441 cross-border M&A announcements between firms in the UK and the EU, which are divided in four subsamples: (1) EU firms that announce to acquire UK firms before the Brexit referendum, (2) EU firms that announce to acquire UK firms after the Brexit referendum, (3) UK firms that announce to acquire EU firms before the Brexit referendum and (4) UK firms that announce to acquire EU firms after the Brexit referendum. Additionally, the method of payment, the listing status of the target firm, the relative firm size and industry relatedness between the bidder and target firm are included in this study as deal and firm characteristics. Furthermore, this study will look at any possible leakage or delay effects around the announcement.
This study contributes to the literature by providing evidence that cross-border M&A announcements have a positive effect on the bidders’ wealth. Furthermore, it provides evidence that the period after the Brexit referendum will generate higher wealth effects upon announcement to the bidder than the period before the Brexit referendum. In addition, this study finds no evidence that UK bidders earn higher returns compared to European bidders. Lastly, this study provides evidence that cash payments are seen as a more favourable method of payment compared to stock payments.
target, relative firm size in terms of assets and leakage and delayed effects. Section 3 describes the data and the methodology used. Section 4 presents the empirical results and section 5 presents the conclusions, limitations and suggestions for further research.
2. Literature review and hypotheses
2.1 The influence of the Brexit on announcements of cross-border acquisitions from a bidder’s perspective
This paper studies the impact of the Brexit on the shareholder value of the acquiring firms when there is a cross-border M&A announcement between a European and UK firm. Bradley, Desai and Kim (1988) argue that possible synergistic gains could be exploited by an M&A. An increase in market share or economies of scale and scope could be important arguments to engage in M&As as well. Additionally, firms mainly engage in cross-border acquisitions because of the exploitation of new markets or to take advantage of certain imperfections of the international capital market such as exchange rate movements or tax advantages (Harris and Ravenscraft, 1991). On the other hand, cross-border deals result in more
internal uncertainty for acquirers (Gatignan and Anderson, 1988). Moreover, cross-border
Therefore, it will most likely have large consequences in terms of trade and for that reason on M&As.
Given the time of writing this study, there are not many empirical studies regarding the impact of the Brexit on this topic. Most of the papers or studies are not useful for this literature review, because these studies are conducted by consultancy firms. Given that the Brexit will most likely results in segregation between the UK and Europe, the costs, risks and uncertainties associated with cross-border acquisitions between them are most likely to increase. For that reason, this study expects that the Brexit will have a negative impact on cross-border acquisitions. Based on the literature regarding cross-border acquisitions between UK and EU firms and the limited literature regarding the Brexit, the first hypotheses are formulated as follows:
H1a. Cross-border M&A announcements will have a positive effect on the stockholder’s wealth of the acquiring firm.
H1b. Cross-border M&A announcements before the Brexit referendum will have higher returns than cross-border M&A announcements after the Brexit referendum for the stockholders of the acquiring firm.
H1c. Cross-border M&A announcements will have higher returns for UK bidders than cross-border M&A announcements for European bidders.
2.2 Method of payment
According to previous literature, the method of payment matters in an M&A deal. The signaling hypothesis of information asymmetry developed by Myers and Maljuf (1984) assumes that the management of the bidder firm has superior information regarding the true value of the target firm. In this way, the method of payment could signal information about the true value of the target firm. If the bidder firm offers cash, it could mean that the bidders believe that the target firm is undervalued and that they want to keep the gains for their own shareholders. Vice versa, if the bidders offer stock, they probably believe the target is overvalued and the bidders want to share the risks between both sides of shareholders.
On the other hand, according to Dutta Saadi and Zhu (2013) cross-border acquisitions are more complex in nature due to the uncertainty involved in dealing with a target in a foreign market. Therefore, payment decisions may need further considerations. Various studies indicate that there are advantages in using stock financing over cash financing as a method of payment in cross-border acquisitions. When using stock financing, the stockholders of the target firm retain some ownership. According to Kang and Kim (2008), it is more important to have ‘local’ shareholders monitoring the new merged firm, because it will probably increase the synergy realization for the firm. Furthermore, stock financing could send a signal that the acquirer’s stock has high liquidity and intrinsic value if it is accepted by the target firm. This would imply that stock-offers are seen as more favorable by the market than cash-offers in cross-border acquisitions.
in cash bids. Using a European sample, Martynova and Renneboog (2006) report higher abnormal returns for cash (12%) than for stock financed deals (7%). Therefore, the next hypothesis is as follows:
H2. Abnormal returns in case of cash payments are larger than abnormal returns in the case of stock payments.
2.3 Listing status
Prior research suggests that the abnormal returns of an M&A announcement are also influenced by the listing status of the target firm (Moeller and Schlingemann, 2004). The liquidity theory is an important theory to explain the importance of the listing status of the target firm. The liquidity theory states that the bidder will pay relatively more for a listed firm in comparison to an unlisted firm. This is due to the illiquid market of unlisted firms. Therefore, the bidders have more bargaining power to demand a lower acquisition price for an unlisted firm. Additionally, Mateev (2017) argues that hubris has a larger negative impact with listed target firms compared to unlisted target firms. Managers who are overconfident and motivated by increasing their own private benefits are more interested in the larger size and more publicity usually associated with a listed target firm. Hence, managers are willing to pay a higher premium for the listed target firm.
In addition, he finds a significant negative return of -0.89% when a UK firm announced an acquisition of a listed target firm. These results are in line with the theories described above. This results in the next hypothesis:
H3. Acquiring firms which announce an M&A with an unlisted firm earn higher abnormal returns than those which announce an M&A with a listed firm.
2.4 Industry relatedness
Many studies that analyze the impact of an M&A announcement on the stockholder returns of the bidder firm consider the industry relatedness as an important variable. The literature differs about whether diversification is welfare enhancing or destroying. Lewellen (1971) argues that the industry diversification leads to more stable cash flows. Additionally, Stein (1997) suggest that the need for external financing decreases when a firm is diversified. Chatterjee (1986) argues that there are collusive, operational and financial synergies in case of an M&A. However, only financial synergies could be achieved in the case of an acquisition with a firm from an unrelated industry. Furthermore, Levy and Sarnat (1970) argue and prove theoretically that horizontal and vertical mergers have a larger potential than conglomerate mergers, because of the absence of economies of scale in conglomerate mergers. On the other hand, Martynova and Renneboog (2006) and Roll (1986) both argue that diversification is mainly driven by the personal objectives of the managers. Hence, diversification will decrease the wealth of the acquiring firm.
hand, Martynova and Renneboog (2006) find significant higher wealth effects around the M&A announcement day when the target is from a related industry compared to a target from an unrelated industry in 2,419 European bids between 1993 and 2001. This brings us to the next hypothesis:
H4. Firms acquiring industry related targets earn higher abnormal returns than firms acquiring industry unrelated target firms.
2.5 Relative size of the firm
Prior research suggests that, in the event of an M&A, the relative firm size between the bidder and the target matters. Kitching (1967) argues that acquisitions between firms that are about the same size would have a larger potential than those between firms which differ significantly in firm size. This is due to the greater combination potential. However, when the acquirer is significantly larger than the target, the combination potential is reduced. Additionally, Kitching (1967) argues that the human integration needs are easily overlooked by the acquirer when the target is significantly smaller. In result, it will not generate the forecasted synergies. Moeller and Schlingemann (2004) argue that hubris is an important reason why relatively larger firms tend to pay a higher premium, which in turn will affect the stockholder wealth of the bidder in a negative way.
are negatively related to the size of the bidder. Additionally, Asquith, Bruner and Mullins (1983) find a positive and statistically significant relationship between the bidding firm’s cumulative excess return and the relative size of the target firm. They find on average a cumulative excess return of 1.8 percent if the target firm is half the firm’s bidding size compared to one-tenth of the bidder’s size. This brings us to the next hypothesis:
H5. Relatively small acquiring firms have larger abnormal returns upon announcement then relatively large acquiring firms.
2.6 Leakage and delayed effects
2.6.1 Leakage effects
According to the M&A Research Centre (MARC, 2016), the number of leaked deals of
M&As increased in 2015. The researchers used the event study methodology to determine
There is not much empirical evidence which focuses on information leakage prior to the announcement day. Mateev (2017) finds in a European sample including the UK two days before the announcement an abnormal return which equaled 0.14 percent. This is significant at the five percent level, suggesting that the market participants acted on certain information received two days before the announcement. Mateev (2017) rejects his hypothesis, that information leakage leads to significantly positive abnormal returns for bidders on the day before the announcement, because the findings one day prior to the announcement are negative and insignificant. Considering, the fact that Mateev (2017) finds significant abnormal returns two days prior to the announcement it is worthwhile to analyze the possible leakage effect in this study. This leads to the following hypothesis:
H6a. Information leakage leads to significant positive abnormal returns for bidders in the days prior to the announcement.
2.6.2 Delayed effects
Following the efficient market hypothesis, the market should incorporate the announcement of an M&A directly in the stock prices at the announcement day itself. However, the post-event period could also be analyzed to assess whether there is any delay in the reach of the information being disseminated (Peterson, 1989). If there is any delay in the dissemination of information, it would mean that the market does not work efficient. Peterson (1989) suggest that the dissemination of company-specific information could take longer than one day. It is possible that a firm releases information, but the next day is the first possibility
for the press to cover it.Furthermore, it is not known whether the information published by the
possibility exists that information is not disclosed or published at all. Therefore, this study will analyze possible delay effects as well.
There are various studies that investigate the abnormal returns during a period after the announcement. Shah and Arora (2014) examine a sample of M&A announcements in the Asia-Pacific region in the year 2013 and find statistical evidence of delay effects for the target firm. However, they do not find significant delay effects for the bidder firm. On the other hand, Amewu and Alagidede (2018) find evidence of delay effects in the case of M&A announcements. This is in the form of positive and significant ARs for the acquirer shareholders after the announcement day. Mateev (2017) finds as well significant positive effects the day after the announcement in 2,823 European acquisitions between 2002 and 2010. Considering the empirical results and the theoretical reasoning above, this study comes to the following hypothesis:
H6b. Information delay leads to significant abnormal returns for the bidder in the days after the announcement.
3. Data and methodology 3.1 Data
addition, this study focuses on real M&As. Therefore, buybacks or recapitalizations are excluded from this sample. Lastly, at least one year of financial stock price data of the acquiring firm before the announcement needs to be available. The Euro Stoxx 50 and the Financial Times Stock Exchange 100 index are used as the market indices for respectively the European and UK firms.
Table 1
Distribution of deals by nation, period and bidder origin. Number of EU firms acquiring UK firms before the Brexit Number of EU firms acquiring UK firms after the Brexit Number of EU firms targeted by UK firms before the Brexit Number of EU firms targeted by UK firms after the Brexit Total number of firms France 22 29 8 9 68 Germany 20 16 19 11 66 Sweden 23 32 5 4 64 Netherlands 4 8 23 15 50 Ireland 16 17 8 9 50 Spain 3 3 15 11 32 Italy 2 1 9 10 22 Belgium 4 3 5 5 17 Finland 3 5 4 3 15 Denmark 3 3 2 3 11 Luxembourg 3 4 2 0 9 Romania 0 0 4 4 8 Austria 1 2 1 2 6 Poland 2 1 2 0 5 Malta 1 1 0 2 4 Cyprus 0 0 2 2 4 Croatia 0 0 3 0 3 Portugal 0 0 1 1 2 Greece 0 0 2 0 2 Czech Republic 0 0 0 2 2 Hungary 0 0 0 1 1 Total 107 125 115 94 441
This results in a final sample of 441 M&A deals that is divided for this study in four subsamples: (1) EU firms that announce to acquire UK firms before the Brexit referendum, (2) EU firms that announce to acquire UK firms after the Brexit referendum, (3) UK firms that announce to acquire EU firms before the Brexit referendum and (4) UK firms that announce to acquire EU firms after the Brexit referendum. These subsamples respectively contain 107,125,115 and 94 M&A announcements. Table 1 shows the distribution of nations by subsample. Looking at the distribution of nations in Table 1, French firms appear most in the sample. However, German and Swedish firms follow closely. The firms from these three countries account for 45 percent of the sample. This study retrieved the data of firm and deal characteristics from the Zephyr database of Bureau van Dijk which are shown in Table 2.
These firm and deal characteristics are divided in the same four subsamples as described and used in table 1. The category unknown is included in Table 2 for missing deal and firm characteristics. This is the case for the method of payment, industry relatedness, and for the relative firm size. Some variables are unclear or not known and therefore missing in the database. With respect to the method of payment, 74 percent favor cash over shares or a mixed form of cash and shares as a form of payment. The public status refers to the fact whether the target firm is listed or not. In this case, only eight firms in the whole sample are listed. Furthermore, the sic codes are also retrieved from the database. This is a system for classifying
industries by a four-digit code. In Table 2 the firms are seen as related when at least the first
two digits of the code are a match. This is the same method as Mateev (2017) uses to classify the relation between firms and industry. 43 percent of the firms in this sample are industry related when excluding the category unknown.
the finance literature according to Dang, Li and Yang (2018). Therefore, this study uses the total assets approach to measure the relative firm size between the bidder and the target firm as well.
Table 2
Distribution of deal characteristics by period.
Deal characteristics Number of EU firms acquiring UK firms before the Brexit Number of EU firms acquiring UK firms after the Brexit Number of EU firms targeted by UK firms before the Brexit Number of EU firms targeted by UK firms after the Brexit Total number of firms Total 107 125 115 94 441 Method of payment Cash 21 31 45 31 128 Stock 2 3 4 2 11 Mixed 6 5 8 15 34 Unknown 78 86 58 46 268 Total 107 125 115 94 441 Public status Unlisted 106 122 111 94 433 Listed 1 3 4 0 8 Total 107 125 115 94 441 Industry relatedness Related 42 44 49 50 185 Unrelated 64 81 60 36 241 Unknown 1 0 6 8 15 Total 107 125 115 94 441 Relative firm size in Assets 0-3 percent 53 72 52 54 231 3-5 percent 7 10 10 4 31 5-10 percent 5 4 8 2 19 Over 10 percent 7 8 11 11 37 Unknown 35 31 34 23 123 Total 107 125 115 94 441
Several studies, such as Mantravadi and Reddy (2007) and Dutta and Jog (2009), use different proxies for the relative firm sizes to examine the effects of the different firm sizes between the bidder and the target firm. This study also uses a proxy to examine the impact of relative firm size between the bidder and target firm on the acquirer stockholder wealth when there is an M&A announcement. As can be seen in Table 2, the relative firm size in terms of assets is for most of the target firms below three percent.
3.2 Methodology
An event study (see MacKinlay, 1997) is used to measure the stockholder wealth effects of the acquirer around and on the announcement day. The announcement day of an M&A deal
will be indicated as t=0. The expected returns are estimated, using the market model, with
realized daily returns in an estimation window of 261 days till 10 trading days prior to the announcement, see equation 1:
𝑅𝑖𝑡 = 𝛼𝑖+ 𝛽𝑖𝑅𝑚𝑡+ 𝜀𝑖𝑡 (1)
In this formula Rit represents the return on security i on day t. The return on the market index is
noted as Rmt andαi is the intercept. Additionally, βi is the slope and εit is the error term. The
intercept, slope and the error term are calculated by using ordinary least squares (OLS).
Once the market model parameters are known, the abnormal returns (AR) and the cumulative
abnormal returns (CAR) for security i on day t and period 𝜏1 𝑡𝑜 𝜏2 ,respectively, are:
𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡− 𝛼̂𝑖 − 𝛽̂𝑖𝑅𝑚𝑡, (2)
𝐶𝐴𝑅𝑖(𝜏1,𝜏2) = ∑𝜏2 𝐴𝑅𝑖𝑡
𝑡=𝜏1 (3)
Following from the AR, the conditional variance is:
which consists of two components. The disturbance variance from equation 1 and an additional
variance, because of the sampling error in 𝛼̂𝑖 and 𝛽̂𝑖.
The main event window will be (-10, +10). This event window is mainly to see the dynamics of the ARs before and after the announcement day. Such that possible leakage or delayed effects could be noticed. As a robustness check several other event windows will be analyzed. Following from the AR and the CAR, the average abnormal return (AAR) and the cumulative average abnormal return (CAAR) could be derived as follows:
𝐴𝐴𝑅𝑡 = 1 𝑁∑ 𝐴𝑅𝑖𝑡 𝑁 𝑖=1 (5) 𝐶𝐴𝐴𝑅(𝜏1,𝜏2) = ∑𝜏𝑡=𝜏2 1𝐴𝐴𝑅𝑡 (6)
the AARs and CAARs will be tested through a normal test statistic and a generalized sign test as described by Cowan (1992). The calculation of these tests could be found in appendix A1.1 and appendix A1.2 respectively. This study chooses the latter as well, because, according to Cowan (1992), compared to the rank test, the generalized sign test is better suited to investigate the CARs over an event window of several days. Additionally, several regressions will be done for different event windows in the following form:
𝐶𝐴𝑅𝑖(𝜏1,𝜏2) = 𝛽0+ 𝛽1𝐸𝑈𝑖 + 𝛽2𝐴𝐹𝐵𝑅𝐸𝑋𝑖+ 𝛽3𝐼𝑁𝐷𝑈𝑆𝑇𝑅𝑌𝑖 + 𝛽4𝐿𝐼𝑆𝑇𝐸𝐷𝑖+
𝛽5𝑆𝐻𝐴𝑅𝐸𝑆𝑖 + 𝛽6𝑀𝐼𝑋𝐸𝐷𝑖 + 𝛽7𝑅𝐴𝑇𝐼𝑂3𝑖 + 𝜀𝑖, (7)
where EUi is a dummy which becomes 1 if there is a European bidder and 0 if there is a UK
bidder. AFBREXi is a dummy, which takes the value 1 for announcements after the Brexit
referendum and 0 if the announcement took place before the Brexit referendum. INDUSTRYi
refers to the industry relatedness between the bidder and target firm. The industry dummy takes the value 1 if the firms are related and takes the value 0 if the firms are unrelated. The variable
if otherwise. SHARESi is a dummy, which becomes 1 if the method of payment is shares and
0 if otherwise. MIXEDi is also a method of payment dummy and it takes the value 1 if the
method of payment is mixed and 0 if the method of payment is different. Mixed in this study is
defined as the payment with shares and cash. The CASHi dummy refers to method of payment.
The cash dummy takes the value 1 if the method of payment is cash and it takes the value 0 if the method of payment is different. It is not possible to regress the dummies shares, mixed and cash at once, because of multicollinearity problems. Therefore, this study will make the regressions with only the dummies shares and mixed for the method of payment and cash will be used as the reference category. Several other studies use different dummies to classify different categories of relative firm sizes. In this sample 73 percent of deals are between 0 and 3 percent in terms of relative firm size when excluding the category unknown. Therefore, the three percent level will be used as the benchmark for relative firm size in this study. The
RATIO3i dummy will take a value of 1 if the relative firm size in terms of assets in book value
between the bidder and target is three percent or larger and 0 if the relative firm size is below the three percent threshold. This study excludes all the unknown variables when running the regressions, nevertheless the study has still enough observations to have reliable results. Furthermore, a White test is used to detect heteroscedasticity and white heteroscedasticity consistent standard errors are included in every regression to deal with this problem. Lastly, the Durbin Watson test is used to check if there is autocorrelation in the sample, which is not the case.
4. Results
4.1 Abnormal returns for cross-border M&A announcements
sample. The AAR and the CAAR are computed for the event window (-10, +10) around the announcement day. On the announcement day (day 0) the AAR is 0.41 percent positive, which is significant at the one percent level. This means that there is an increase of 0.41 percent to the bidders’ wealth on the day of the M&A announcement. Table A2.1 in the appendix shows the CAARs for the total sample for different event windows. The event windows (-2, +2) and (-1, +1) are both significant and positive as well with values of 0.87 and 0.63 percent respectively.
This finding supports the argument of Harris and Ravenscraft (1991) that firms mainly engage in cross-border acquisitions, because of the exploitation of new markets or to take advantage of certain imperfections of the international capital market such as exchange rate movements or tax advantages. Furthermore, this result is in line with the findings of Mateev (2017) who finds significant positive wealth effects for the bidder in cross-border acquisitions between the EU and the UK from 2002 to 2010. Therefore, hypothesis H1a: “Cross-border M&A announcements will have a positive effect on the stockholder’s wealth of the acquiring firm”, is accepted.
Table 3
The abnormal returns around the announcement day for the total sample.
Event window AAR T-test CAAR T-test
-10 0.05% 0.31 0.05% 0.31 -9 -0.03% -0.18 0.02% 0.09 -8 -0.12% -0.76 -0.10% -0.36 -7 -0.18% -1.13 -0.28% -0.88 -6 0.03% 0.20 -0.25% -0.70 -5 0.08% 0.52 -0.16% -0.43 -4 -0.04% -0.25 -0.20% -0.49 -3 0.09% 0.56 -0.12% -0.26 -2 0.14% 0.92 0.03% 0.06 -1 0.01% 0.07 0.04% 0.08 0 0.41% 2.60*** 0.45% 0.86 1 0.21% 1.30 0.65% 1.20 2 0.10% 0.65 0.76% 1.33 3 -0.15% -0.96 0.61% 1.03 4 0.02% 0.15 0.63% 1.03 5 -0.20% -1.29 0.43% 0.68 6 0.05% 0.31 0.48% 0.73 7 -0.08% -0.49 0.40% 0.60 8 -0.05% -0.33 0.35% 0.51 9 -0.06% -0.36 0.29% 0.41 10 -0.04% -0.25 0.25% 0.35
Fig. 1. Daily abnormal returns for the total sample
Additionally, this study analyzes the period before and after the Brexit referendum to investigate if there is a difference in the bidders’ wealth related to the Brexit. Table A2.2 in the appendix presents the AARs for the event window (-10, +10) around the announcement and their corresponding t-statistics for the samples before and after the Brexit referendum. On the announcement day there is a positive insignificant wealth effect of 0.14 percent for the period before the Brexit referendum. However, the period after the Brexit referendum has a positive significant wealth effect to the bidders of 0.69%, which is significant at the 1 percent level.
This finding is also presented in table 4. Additionally, table 4 presents the CAARs of three other event windows for the periods as well. The CAARs for the period before the Brexit referendum generate positive, but insignificant returns to the bidders. However, the corresponding non-parametric sign test designed by Cowan (1992) is positive and significant for the event windows (-5, +5), (-2, +2) and (-1, +1). Meaning that a significant number of M&A announcements has a positive effect to the bidders’ wealth effect. The event windows (-2, +2), (-1, +1) and (0) generate significantly positive CAARs in the period after the Brexit referendum and the sign test confirms this result. However, only the CAARs of the event window (0) are significant at the ten percent level when using a two-sample test with unequal variances to compare the different between the periods. Hence, this study finds a significant
-0.30% -0.20% -0.10% 0.00% 0.10% 0.20% 0.30% 0.40% 0.50% -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
difference on the ten percent level in wealth effects on the announcement day itself in favor of the period after the Brexit referendum.
Table 4
Cumulative average announcement returns by periods.
Panel A: Sample before the Brexit referendum (N=222)
Event window CAAR t-statistic Sign Test Positive
(-5, +5) 0.57% 0.63 2.17** 54.5%
(-2, +2) 0.80% 1.32 1.91* 53.6%
(-1, +1) 0.42% 0.89 2.58*** 55.9%
(0) 0.14% 0.50 1.37 51.8%
Panel B: Sample after the Brexit referendum (N=219)
Event window CAAR t-statistic Sign Test Positive
(-5, +5) 0.78% 1.50 2.26** 53.9%
(-2, +2) 0.95% 2.70*** 2.39** 54.3%
(-1, +1) 0.84% 3.08*** 2.12** 53.4%
(0) 0.69% 4.38*** 2.26** 53.9%
Panel C: Difference before and after the Brexit referendum
Event window Before After Difference(t-stat)
(-5, +5) 0.57% 0.78% -0.33
(-2, +2) 0.80% 0.95% -0.28
(-1, +1) 0.42% 0.84% -0.94
(0) 0.14% 0.69% -1.69*
Note: This table reports the cumulative average abnormal returns over four different event windows. Panel A reports the sample before the Brexit referendum and Panel B reports the sample after the Brexit referendum. Additionally, this table reports the t-statistic, sign test and the percentage positive CAARs for each event window. Panel C reports the mean difference between the two samples. Here a two-sample t-test with unequal variances is used to test the significance of the means. *, **, *** refer to the 10%, 5% and 1% significance level respectively.
Table A2.3 in the appendix provides the ARs with their corresponding t-statistic of the UK and European bidders for the event window (-10, +10) around the M&A announcement. The table reports a positive insignificant return of 0.16 percent for the European bidders, whereas it reports a positive and highly significant return of 0.68 percent on the announcement day. Moreover, Table 5 presents the CAARs of the UK and European bidders. Here it could be seen that the CAARs for the European firms are slightly positive yet insignificant. Contrarily, the CAARs of the UK firm are positive and highly significant in the event windows 2, +2), (-1, +1) and (0). However, the differences between the UK and EU are insignificant for all event windows.
Table 5
Cumulative average announcement returns by bidder regions.
Panel A: EU sample (N=233)
Event window CAAR t-statistic Sign Test Positive
(-5, +5) 0.51% 0.59 2.19* 54.5%
(-2, +2) 0.65% 1.11 1.80* 53.2%
(-1, +1) 0.30% 0.67 1.27 51.5%
(0) 0.16% 0.62 0.94 50.4%
Panel B: UK sample (N=209)
Event window CAAR t-statistic Sign Test Positive
(-5, +5) 0.85% 1.59 2.24** 53.8%
(-2, +2) 1.12% 3.10*** 2.38** 54.3%
(-1, +1) 0.98% 3.51*** 3.35*** 57.6%
(0) 0.68% 4.23*** 2.73*** 55.5%
Panel C: Difference between the EU and UK
Event window EU UK Difference(t-stat)
(-5, +5) 0.51% 0.85% -0.54
(-2, +2) 0.65% 1.12% -0.89
(-1, +1) 0.30% 0.98% -1.53
(0) 0.16% 0.68% -1.56
Note: This table reports the cumulative average abnormal returns over four different event windows. Panel A reports the sample for European bidders and Panel B reports the sample for UK bidders. Additionally, this table reports the t-statistic, sign test and the percentage positive CAARs for each event window. Panel C reports the mean difference between the two samples. Here a two-sample t-test with unequal variances is used to test the significance of the means. *, **, *** refer to the 10%, 5% and 1% significance level respectively.
must pay higher premiums to UK target shareholders if the quality of corporate governance for UK shareholders is reduced. This study does not find evidence suggesting that EU bidders pay higher premiums to UK target shareholders. Therefore, this study rejects hypothesis H1c: “Cross-border M&A announcements will have higher returns for UK bidders than cross-border M&A announcements for European bidders”.
4.2 The impact of the method of payment to the bidders’ abnormal returns
Table 6
Determinants of the bidders’ announcement cumulative average abnormal returns for the total sample.
Note: This table reports the results of the cross-sectional regression for the total sample, where the CAAR is the dependent variable on the windows of (-5, +5), (-2, +2), (-1, +1) and (0) days around the announcement. An EU dummy is used to control for the European firms. To distinguish between before and after the Brexit referendum an AFBREX dummy is included. The industry dummy captures the effect if firms are industry related. Listed refers to the listing status of the target firm. Shares and Mixed relate to the method of payment and Ratio3 is a dummy which distinguishes the relative size between the bidder and target firm at the three percent threshold. The figures in the parentheses are the p-values, where *, **, *** refer to the 10%, 5% and 1% significance level respectively.
The results are in line with the results of Martynova and Renneboog (2006) who also find a significant positive difference in favor of cash bids compared to stock bids. Furthermore, these results support the theory of Myers and Maljuf (1984) who argue that the method of payment could signal information about the true value of the target firm. In case the bidder’s firm offers cash, it could mean that the bidders believe that the target firm is undervalued. If the bidders offer stock, it is possible that they believe that the target firm is overvalued. Hence, cash bids would be received more positively relative to bids with stocks. Since this study finds a significant positive difference in favor of cash bids compared to bids with stocks, hypothesis 2: “Abnormal returns in case of cash payments are larger than abnormal returns in the case of stock payments” is accepted.
Explanatory variables
CAAR (-5, +5) CAAR (-2, +2) CAAR (-1, +1) CAAR (0)
4.3 The impact of the listing status of the target firm to the bidders’ abnormal return
Table 6 reports the listing status of the target firm as well. The coefficients for the listing status of the four regressions are slightly negative, but insignificant. Therefore, it seems that the listing status of the target firm has no impact on the bidders’ CAARs in the event of an M&A announcement. However, this is not the case when this study splits the sample into different subsamples. Table 7 reports the determinants of the bidders’ announcement CAARs before and after the Brexit referendum and reports significant negative values for the period before the Brexit referendum, whereas it has some significant positive values for the period after the Brexit referendum.
Table 7
Determinants of the bidders’ announcement cumulative average abnormal returns before and after the Brexit referendum.
In column 1 the value for the listing status is -0.057 which is significant at the ten percent level. This means that the CAAR for the bidder on a listed target is 5.7 percent lower compared to an unlisted target in the event of an M&A announcement before the Brexit referendum. However, column 5 represents the period after the Brexit referendum and shows a positive significant value of 0.044 for the listing status. Hence, the fact that a target firm is listed has a positive impact on the CAARs of the bidders after the Brexit referendum for the data used. Furthermore, Table A2.5 in the appendix shows the results of the regressions which make a distinction between European firms acquiring UK firms and vice versa. In this table the coefficients of the European sample are slightly positive, but insignificant. In this case there is no evidence that the listing status of the target firms has an impact on the CAARs of European bidders. Contrarily, it reports significant negative values in all the different event windows for UK firms. The event window (-1, +1) for UK firms has a negative value of -0.044, which is significant at the 5 percent level. This means that if the firm is listed it will reduce the UK acquirers’ CAAR with 4.4 percent compared to an M&A announcement with an unlisted target firm.
The results are peculiar and not completely in line with certain economical reasoning such as the liquidity and hubris theory. The results differ with Faccio et al. (2006) who found an insignificant average excess return of -0.38% for acquirers of listed targets and a significant average excess return of 1.48% for acquirers of unlisted target in a sample of 17 West European countries from 1996 to 2001. Therefore, hypothesis H3: “Acquiring firms which announce an M&A with an unlisted firm earn higher abnormal returns than those who announce an M&A with a listed firm” is rejected.
4.4 The impact of industry relatedness to the bidders’ abnormal return
relatedness between the bidder and target firm could have an impact on the ARs in the event of an M&A announcement. Table 6 reports the determinants of the bidders’ announcement CAARs for the total sample. In this table, all the industry coefficients are slightly positive. However, they are highly insignificant. This is also the case for all the other regressions in the subsamples. This means that this study does not find evidence that the industry relatedness between the bidder and target firm has an impact on the acquirers’ stockholder wealth in the event of an M&A announcement. These findings are not in line with the reasoning of Martynova and Renneboog (2006) and Rolls (1986). They all argue that diversification is mainly driven by the personal objectives of the managers. Hence, diversification will decrease the wealth of the acquiring firm. Furthermore, Martynova and Renneboog (2006) find significant higher wealth effects around the M&A announcement day when the target is from a related industry compared to a target from an unrelated industry in 2,419 European bids between 1993 and 2001. Hence, the findings of this study are not in line with the findings of Martynova and Renneboog (2006). However, the results are in line with the findings of Mateev (2017). He finds no statistically significant evidence that industry diversification has a negative impact for bidders. Since this study finds no statistical evidence associated with industry relatedness, hypothesis H4: “Firms acquiring industry related targets earn higher abnormal returns than firms acquiring industry unrelated target firms” is rejected.
4.5 The impact of relative firm size to the bidder’s abnormal return
find evidence that the relative firm size between the bidder and target firm in terms of the book value of assets has an impact on the bidders’ stockholder wealth in the event of an M&A announcement. The results of this study are not in line with the economical reasoning of Kitching (1967) and Moeller and Schlingemann (2004) as well as the empirical findings of Asquith et al. (1987) and Moeller and Schlingemann (2004). Hypothesis H5: “Relatively small acquiring firms have larger abnormal returns upon announcement then relatively large acquiring firms” is rejected, because no statistical evidence was found related to relative firm size.
4.6 Leakage and delay results
This section presents the results related to leakage and delayed effects. Table 8 shows the results of the CAARs of the total sample and the different subsamples. Panel A reports the CAARs and their corresponding test statistic for the event window (-2, -1). If there is any leakage or delay effect, it should affect the CAARs significantly before or after the announcement day, respectively. However, this is not the case for the CAARs in all the samples for the event window (-2, -1).
Table 8
Cumulative average announcement returns by subsamples.
Panel A: Event window (-2, -1)
Sample CAAR T-test Sign test Positive
Total sample 0.15% 0.70 2.66*** 53.1%
Before the Brexit referendum 0.29% 0.76 2.98*** 57.2%
After the Brexit referendum 0.02% 0.08 0.77 48.9%
EU bidders 0.04% 0.10 0.94 50.4%
UK bidders 0.28% 1.25 2.87*** 56.0%
Panel B: Event window (+1, +2)
Sample CAAR T-test Sign test Positive
Total sample 0.31% 1.38 1.99** 51.5%
Before the Brexit referendum 0.37% 0.96 0.96 50.5%
After the Brexit referendum 0.24% 1.10 1.85* 52.5%
EU bidders 0.45% 1.21 1.99** 53.9%
UK bidders 0.15% 0.67 0.78 48.8%
Additionally, Table 3 shows an abnormal return of 0.14 percent with a test statistic of 0.92 two days prior to the announcement. However, this is not significant either. Therefore, this study does not find evidence suggesting any leakage effects.
Panel B reports the CAARs for the different samples for the event window (+1, +2) to identify possible delay effects. The CAAR for the total sample is 0.31 percent with a corresponding test statistic of 1.38, which is not significant. The CAARs of the other subsamples are insignificant as well. On the day after the announcement, the AR is 0.21 percent. This is quite high compared to the other abnormal returns around the announcement day, yet it has an insignificant test statistic of 1.30. Therefore, this study does not find evidence suggesting any delay effects. This is not in line with the report published by the M&A research center or
the findings of Mateev (2017). Therefore, hypotheses H6a: “Information leakage leads to
significant positive abnormal returns for bidders in the days prior to the announcement” and H6b: “Information delay leads to significant abnormal returns for the bidder in the day’s after the announcement” are both rejected.
5. Conclusion
announcements have a positive effect on the bidders’ stockholder wealth in the EU and the UK. This is in line with the findings of Mateev and Andonov (2016) and Mateev (2017). Furthermore, this study finds significant positive ARs after the Brexit referendum, whereas it finds small positive insignificant ARs before the Brexit referendum. This suggests that the Brexit referendum has a positive impact on the bidders’ stockholder wealth. This result was not expected. Moreover, this study did not find evidence suggesting that UK bidders obtain a larger positive wealth effect compared to European bidders. This is not in line with the findings of Mateev and Andonov (2016) and the economical reasoning that European bidders must pay higher premiums for the reduction in corporate governance quality of the UK target firm.
Prior research suggest that the method of payment influences the bidder’s stockholder wealth. Indeed, this study finds that cash payments are associated with higher CAARs of bidders compared to payments with stocks. This study finds contradicting results related to the listing status of the target firm. This study finds no evidence in the total sample that the listing status of the target firm influences the bidder wealth effects. However, it finds evidence suggesting that it influences the bidders’ wealth negatively before the Brexit referendum and positively after the Brexit referendum. Additionally, this study does not find evidence suggesting that the industry relatedness and relative firm size impact the bidder’s wealth. Lastly, the results indicate that there are no leakage or delay effects in this study.
References
Asquith, P., Bruner, R.F., Mullines, D.W., 1983. The gains to bidding firms from merger. Journal of Financial Economics 11, 121-139.
Amewu, G., Alagidede, P., 2018. Do mergers and acquisitions announcements create value for acquirer shareholders in Africa. Journal of Finance and Economics 23 (4), 606-627. Boone, A.L., Mulherin, J.H., 2000. Comparing acquisitions and divestitures. Journal of Corporate Finance 6 (2), 117-139.
Bradley, M., Desai, A., Kim E.H., 1988. Synergistic gains from corporate acquisitions and their division between the stockholders of target and acquiring firms. Journal of Financial Economics 21, 3-40.
Bruner, R., 2002. Does M&A pay? A survey of evidence of the decision maker. Journal of Applied Finance 12 (1), 48-68.
Campa, J.M., Moschieri, C., 2008. The European M&A industry trends: patterns and shortcomings. In: Working Paper, no. 762. University of Navarra, Spain.
Chatterjee, S., 1986. Types of synergy and economic value: the impact of acquisitions on merging and rival firms. Strategic Management Journal 7, 119-139.
Cowan, A.R., 1992. Nonparametric event study test. Review of Quantitative Finance and Accounting 2, 343-358.
Craig MacKinlay, A., 1997. Event studies in economics and finance. Journal of Economic Literature 35, 13-39.
Dang, C., Li, Z., Yang, C., 2018. Measuring firm size in empirical corporate finance. Journal of Banking and Finance 86, 159-176.
DeLong, G., 2001. Stockholder gains from focusing versus diversifying bank mergers. Journal of Financial Economics 59, 221-252.
Doukas, J., Travlos, N.G. 1988. The effect of corporate multinationalism on shareholders wealth; evidence from international acquisitions. Journal of Finance 43, 1161-1175.
Dutta, S., Saadi, S. Zhu, P., 2013. Does payment method matter in cross-border acquisitions? International Review of Economics and Finance 25, 91-107.
Dutta, S., Jog, V., 2009. The long-term performance of acquiring firms: A re-examination of an anomaly. Journal of Banking and Finance 23, 1400–1412.
Erel, I., Liao, R.C., Weisbach, M.S. 2012. Determinants of cross-border mergers and acquisitions. Journal of Finance 67, 1045-1082.
Fuller, K., Netter, J., Stegemoller, M., 2002. What do returns to acquiring firms tell us? Evidence from firms that make many acquisitions. Journal of Finance 57 (4), 1763-1793.
Francis, B., Hasan, I., Sun, X. 2008. Financial market integration and the value of global diversification: evidence from US acquirers in cross-border mergers and acquisitions. Journal of Banking and Finance 32, 1522-1540.
Gatignan, H., Anderson, E., (1988). The multinational corporations degree of control over foreign subsidiaries: An empirical test of transaction costs explanation. Journal of Law, Economics and Organisation 4, 305-336.
Hagendorff, J., Collins, M., Keasy, K., 2008. Investor protection and the value effects of bank merger announcements in Europe and the US. Journal of Banking and Finance 32, 1333-1348. Harris, R.S., Ravenscraft, D., 1991. The role of acquisitions in foreign direct investment: evidence from the U.S. stock market. Journal of Finance 46 (3), 825-844.
Houston, J., James, C., Ryngaert, M., 2001. Where do mergers gains come from? Bank mergers from the perspectives of insiders and outsiders. Journal of Financial Economics 60, 285-331.
Jarrell, Gregg A., Poulsen A.B., 1989. The returns to acquiring firms in tender offers: evidence from three decades. Financial Management 18, no. 3,12.
Jensen, M.C., Ruback, R.S., 1983. The market for corporate control: the scientific evidence. Journal of Financial Economics 11, 5-50.
Kang, J., Kim, J., 2008. The geography of block acquisitions. Journal of Finance 63, 2817– 2858.
Kitching, J., 1967. Why do mergers miscarry. Harvard Business Review 45, 84-101. Levy, H., Sarnat, M., 1970. Diversification, portfolio analysis and the uneasy case of conglomerate mergers. Journal of Finance 25, 365-383.
Lewellen, W., 1971. A pure financial rational for the conglomerate merger. Journal of Finance 26 (2), 521-545.
MacKinlay. A.C., 1997. Event studies in economics and finance. Journal of Economic literature 35 (1), 13-39.
Mateev, M., Andonov, K., 2016. Do cross-border and domestic bidding firms perform differently? New evidence from continental Europe and the UK. Research in International Business and Finance 37 (2), 327-349.
Moeller, S.B., Schlingemann, F.P., 2005. Global diversification and bidder gains: A
comparison between cross-border and domestic acquisitions. Journal of Banking and Finance 29, 533-564.
Moeller, S.B., Schlingemann, F.P., 2004. Firm size and the gains from acquisitions. Journal of Financial Economics 73, 201-228.
Myers, S.C., Maljuf, N., 1984. Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics 13 (2), 187-221. Peterson, P., 1989. Event studies: A review of issues and methodology. Journal of Business and Economics 28 (3), 36-66.
Roll, R., 1986. The hubris hypothesis of corporate takeovers. Journal of Business 59, 196-216.
Shah, P., Arora, O., 2014. M&A announcements and their effect on return to shareholders: An event study. Journal of Accounting and Finance Research 3 (2), 170-190.
Appendices
Appendix A1
A1.1 The test statistic
The test statistic is calculated as follows:
𝑡 =𝐴𝐴𝑅𝑡
𝜎𝑎𝑟,
where t is the test statistic. 𝐴𝐴𝑅𝑡 represents the average abnormal returns on day t in the
sample and 𝜎𝑎𝑟 represents the standard deviation of the abnormal returns.
A1.2 The generalized sign test
The generalized sign test is as follows:
𝑝̂ =1 𝑛∑ 1 251 ∑ 𝑆𝑖𝑡, 𝜏251 𝑡=𝜏1 𝑛 𝑖=1 where 𝑆𝑖𝑡 = {1 𝑖𝑓 𝐴𝑅𝑖𝑡 > 0 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
𝑝̂ is the probability that a stock in the estimation window has a positive abnormal return and n represents the number of stocks. The generalized sign test statistic is:
𝑍𝑔 =
𝑤−𝑛𝑝̂ [𝑛𝑝̂(1−𝑝̂)]1/2
where w is defined as the number of positive CARs in the event window. Appendix A2
A2.1 Cumulative average announcement returns for the total sample.
Event window CAAR t-statistic Sign Test Positive
(-5, +5) 0.67% 1.29 3.13*** 54.2%
(-2, +2) 0.87% 2.48** 3.04*** 54.0%
(-1, +1) 0.63% 2.29** 3.32*** 54.6%
(0) 0.41% 2.60*** 2.56** 52.8%
A2.2 The abnormal returns around the announcement day before and after the Brexit referendum.
Event window AAR before T-test AAR after T-test -10 -0.06% -0.22 0.16% 1.01 -9 0.14% 0.53 -0.20% -1.29 -8 -0.10% -0.37 -0.14% -0.88 -7 -0.27% -0.99 -0.09% -0.55 -6 0.19% 0.68 -0.13% -0.80 -5 0.12% 0.43 0.05% 0.29 -4 -0.04% -0.13 -0.04% -0.29 -3 0.06% 0.21 0.12% 0.77 -2 0.26% 0.95 0.03% 0.19 -1 0.03% 0.12 -0.01% -0.08 0 0.14% 0.50 0.69% 4.38*** 1 0.25% 0.91 0.16% 1.04 2 0.12% 0.45 0.08% 0.51 3 -0.16% -0.59 -0.14% -0.90 4 0.03% 0.11 0.02% 0.11 5 -0.24% -0.87 -0.17% -1.07 6 0.06% 0.21 0.04% 0.25 7 -0.20% -0.74 0.05% 0.32 8 0.07% 0.27 -0.18% -1.14 9 -0.15% -0.55 0.04% 0.23 10 -0.06% -0.23 -0.02% -0.10
Note: This table includes the abnormal returns and cumulative abnormal returns for the sample before and after the Brexit referendum on the event window (-10, +10) around the announcement day. Furthermore, a T-test is used to test the significance of the abnormal returns and cumulative abnormal returns. *, **, *** refer to the 10%, 5% and 1% significance level respectively.
A2.3 The abnormal returns around the announcement day of EU and UK bidders.
Event window AAR EU T-test AAR UK T-test -10 0.02% 0.09 0.08% 0.48 -9 0.09% 0.36 -0.16% -1.01 -8 -0.16% -0.62 -0.07% -0.46 -7 -0.31% -1.20 -0.03% -0.18 -6 0.09% 0.34 -0.03% -0.20 -5 0.09% 0.36 0.07% 0.42 -4 -0.02% -0.07 -0.06% -0.39 -3 0.23% 0.87 -0.06% -0.39 -2 0.09% 0.33 0.21% 1.30 -1 -0.05% -0.18 0.07% 0.46 0 0.16% 0.62 0.68% 4.23*** 1 0.19% 0.72 0.22% 1.39 2 0.26% 0.99 -0.07% -0.44 3 -0.25% -0.95 -0.04% -0.28 4 0.03% 0.13 0.01% 0.08 5 -0.23% -0.87 -0.18% -1.09 6 0.10% 0.38 -0.01% -0.05 7 -0.16% -0.61 0.01% 0.09 8 0.06% 0.23 -0.17% -1.08 9 -0.05% -0.20 -0.06% -0.37 10 0.08% 0.31 -0.17% -1.07
Table A2.4 Comparison between the different methods of payment.
Note: This table reports the pairwise comparisons between the different methods of payment for the total sample. This is done according to the Tukey’s method. The figures in the parentheses are the p-values, where *, **, *** refer to the 10%, 5% and 1% significance level respectively.
A2.5 Determinants of the bidders’ announcement cumulative average abnormal returns between the EU and the UK.
Explanatory variables EU (-5, +5) (-2, +2) (-1, +1) (0) UK (-5, +5) (-2, +2) (-1, +1) (0) (1) (2) (3) (4) (5) (6) (7) (8) Intercept 0.015 (0.474) 0.011 (0.559) 0.012 (0.431) 0.001 (0.938) 0.022 (0.180) -0.004 (0.737) -0.004 (0.683) 0.007 (0.352) AFBREX 0.011 (0.602) 0.008 (0.682) 0.008 (0.628) 0.011 (0.513) 0.002 (0.927) 0.014 (0.289) 0.009 (0.414) 0.009 (0.351) INDUSTRY 0.005 (0.814) 0.010 (0.617) 0.007 (0.655) 0.014 (0.399) 0.007 (0.722) 0.016 (0.234) 0.017 (0.148) 0.003 (0.737) LISTED 0.017 (0.346) 0.009 (0.589) 0.006 (0.703) 0.010 (0.463) -0.048* (0.070) -0.033* (0.096) -0.044** (0.040) -0.042* (0.058) SHARES -0.137 (0.154) -0.077 (0.329) -0.042 (0.408) -0.025 (0.525) -0.039 (0.292) -0.009 (0.589) -0.005 (0.680) 0.024 (0.343) MIXED -0.083** (0.014) -0.079* (0.026) -0.073** (0.024) -0.063* (0.067) 0.009 (0.744) -0.006 (0.781) -0.010 (0.611) -0.006 (0.685) RATIO3 0.013 (0.549) 0.004 (0.816) 0.007 (0.653) 0.003 (0.834) -0.016 (0.425) -0.008 (0.581) 0.003 (0.837) -0.012 (0.214) Number of observations 50 50 50 50 74 74 74 74 R-squared 0.252 0.209 0.232 0.202 0.072 0.080 0.087 0.130 Note: This table reports the results of the cross-sectional regression for the subsamples of the EU and UK, where the CAAR is the dependent variable on the window of (-5, +5), (-2, +2), (-1, +1) and (0) days around the announcement. To distinguish between before and after the Brexit referendum an AFBREX dummy is included. The industry dummy captures the effect if firms are industry related. Listed refers to the listing status of the target firm. Shares and mixed relate to the method of payment and Ratio3 is a dummy which distinguishes the relative size between the bidder and target firm at the three percent threshold. The figures in the parentheses are the p-values, where *, **, *** refer to the 10%, 5% and 1% significance level respectively.
Methods of payment CAAR (-5, +5) CAAR (-2, +2) CAAR (-1, +1) CAAR (0)
