Mergers and acquisitions : do acquirer firms get abnormal return from mergers in Europe?

Mergers and Acquisitions

Do acquirer firms get abnormal return from mergers in Europe?

Date: 02-02-2015 Student: Boudewijn van der Velden Student number: 10448314 Faculty of economics and business Code: BSc ECB University of Amsterdam

This document is written by Student Boudewijn van der Velden

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The Faculty of Economics and Business is responsible solely for

the supervision of completion of the work, not for the contents.

1. Introduction/relevance 2. Review of literature 2.1. Economic theory on M&A 2.2. Empirical evidence 2.21. Arguments for difference in results 3. Research 3.1 Data & Sample 3.2 Methodology 4. Results 5. Conclusion 6. References 7. Appendix

1. Introduction/relevance

The reason behind mergers is wealth creation, which is in line with value maximizing behaviour of firms. The creation of wealth is due to synergy profits that can be made. When examining synergy profits there are numerous reasons why this could incur. The most common synergy profits are: cost efficiency (economies of scale), because of the diminishing of administrative costs and overhead costs (Johnson et al., 2008). The second is revenue synergy, which is often mentioned as economies of scope, by for example using cross selling and bundling different products together (Sevenius, 2003).

There is a lot of research that concludes that value is created in the process of a merger. In the paper of B, D & HK (1988) the result was found that in a successful tender offer the combined value, reflected by its stock prices, of the acquirer and target firm increased with 7.4%. According to these results it is profitable to merge. For the past 6 years the m&a activity in Europe has been on a downward slope falling 54% in value and 22% in volume of deals from 2008 to 2014 (Delloitte, 2014). As this year m&a activity increased across the globe, Europe unfortunately stayed behind (WallstreetJournal). This was also stated by the CNBC, which says that Europe stays largely absent from the m&a boom as they call it.

A merger starts with a firm that wants to acquire another firm. For the hypothetical acquirer wanting to bid on a firm, they must see profits in this endeavour or else they won’t start the whole merger process. That is why this paper measures the value created with a mergers or acquisition by the acquirer firm. This will give insight into the profitability of a European company merging. The measurement of value creation is done by abnormal returns, which means the stock price returns of company i relative to its peer group market. As peer group market several local indices are chosen and implemented on the corresponding countries.

The main question is: do mergers create value? In this research the focus is on the acquirer side of the merger and that is why the research question is: Do acquirer firms get abnormal return from mergers in Europe? With the results

found in this research a European firm could indicate its usefulness to announce a merger and what the average expected abnormal return would be by doing this.

This research contributes to the literature because there is a lack of existing European merger research in recent years. Also day-by-day results will be presented along side the chosen event windows including a regression that checks for a spill of information before the announcement date. A possible shift in abnormal returns at the rumour date is also accounted for in another regression. This research also has respectively to other existing research a large sample size, which will improve the significance of the results.

Further on existing economic theory and empirical literature will be presented and discussed. After that it will be shown how the sample data was retrieved and the corresponding methodology will be given. And as last the results of this paper and the conclusion will be presented.

2. Review of literature

2.1 Economic theory on M&A The terms Merger and Acquisition are often used as one and the same, though there are differences. When a company takes over or buys another company it is seen as an acquisition, the former company ceases to exist and it establishes itself as the new owner. A merger is when both firms join together creating a new firm. However this difference doesn’t really matter according to Sherman and Hart (2006) because the result will be the same, two firms that had been operating separately on their own now operate as one firm.

The sole purpose of acquiring a firm is to create synergy. This means that the sum of the two is larger than its parts. As Sirower (1997) says, it increases its competitiveness and cash flows more than the entities expected to do so independently. Synergies can take many different forms. This depends on the type of merger and the business that the incumbent is involved in. Sevenius (2003) summed up the four most common synergies, which are: cost synergies, revenue synergies, financial synergies and market synergies. The first two are

already mentioned in the introduction, as these are the most simplified form of synergies (Harding & Rovit, 2004). Financial synergy is gained by getting a better cost of capital through reduced risk. With market synergies there is the benefit of having more negotiation power over your suppliers and customers.

Creating and especially sustaining a merger is not easy, that being said it is common for mergers to fail; this is among others thanks to the complexity in valuating synergies. The valuated synergy will influence the price paid for a firm. Often this value is overestimated and this will damage the shareholders value of the acquiring firm (Sirower, 2004). A merger is classified as a failure when it did not increase its shareholders value or achieved its goals set at the date of buying the firm (Rankine, 2001). According to Johnson et al (2004) the reasons for over valuating synergies are due to (1) lack of experience, (2) poor financial advice and (3) managers who are to optimistic. Also a reason for disappointing returns for the acquirer could be because of information asymmetry. When the buyer has incomplete information, he will tend to overpay. In the high price paid for the target firm, the gains of this transaction will transfer to the shareholders of the target firm.

An important issue that should not be ignored is that a possible principle agent problem is disastrous in the merger decision making progress (Hendrikse, 2003). The CEO of the company should have the right incentives to endow a merger. In some cases the CEO (agent) has other incentives then the shareholders (principal). A negative abnormal return can be the consequence of this conflict of interest between principal and agent. This misalignment of interests justifies also what Grinstein and Hribar (2004) states; that a merger often results in the agent receiving a large compensation, which causes them to focus more on their own gains then those of the shareholders.

2.2 Empirical evidence

Over the years a lot of empirical research has been done trying to capture the effect of m&a on the shareholders value. There is a difference in the results found for the acquiring firm and the target firm. The results found by researchers concerning the target firm are widely the same; the abnormal return seems to

always have a positive trend. When looking at the abnormal return for the acquiring firm the results are more contradictory. The different results found by researchers will be given and discussed. In the results section the findings of this paper will be put in place between existing literature. In the appendix table 1 a summery of existing literature around acquiring firms’ abnormal return is given. The outcomes in the studies made around M&A differ a lot; this is among other things because it is very sensitive to a change in the model specification used (Malatesta 1983). As seen in table 1 in the appendix the results are somewhat even distributed among the positive and negative side, with 18 studies finding a positive return and 19 with a negative return.

In the column event window of table 1 in the appendix, the period of time surrounding the announcement date is given. This event windows used differs over the empirical research done. Because they are not the same in all cases it makes it more difficult to compare the results. Most of the studies use a window that begins before the announcement; the reason for this is to capture a possible information leak (Schipper and Thompson, 1983). For instance when there are rumours going around of a firm that will be merging, the stock price should already show this change in an efficient market. There are researchers that study only the announcement day, this means a (0,0) event window. Using this window ignores the fact that there could be gains before the announcement by an information leak and also ignores the fact that the announcement could be done after trading hours (Jianyu et al, 2009).

However in the literature there are also studies that use a much bigger event window. This will correct for the mistakes that could be made when the event window is to small as stated above. A big event window could give problems as well due to a decrease in the accuracy of the results. When the period size chosen increases, the possibility of including another market event goes up, this will give the results less predictive power. Bearing this trade-off in mind, this paper will focus mainly on the (-5,+5) window.

2.21 Arguments for difference in results

Behind the negative returns found by researchers lies a line of theory. Research has been done to find out which characteristics could influence the failure of a merger. One cause, according to McCormick and Mitchel (1993), for lower abnormal return for the bidder is when the acquirer has a low level of leverage. This could be due to the risk aversion of managers of high-levered companies. What is behind this is that risk averse managers accept less projects and when it does accept a project the stock price will thus react more. What also makes debt an attractive characteristic is that taking on more debt will align the decisions that managers make more with the interests of the stockholders. With more debt the threat of default is larger and will make the managers exert more effort (Grossman and Hart 1982)

In line with the alignment of interests argument made above, a key characteristic of the bidder is that the managers should have a high share ownership in the company. The manager should make decisions consistent with the firm’s long-term earnings. If a manager has low share ownership in the company its interests could diverge from those of the shareholders (Lewellen, Loderer and Rosenfeld 1985). Overconfidence of management is also a factor that decreases abnormal return. The probability of an overconfidence management is positively related to the internal funds available, because when the firm has large funds to spend the management will tend to make decisions faster and with less care (Malmendier and Tate, 2008). Also Stulz (1990) and Jensen (1989) have argued that less free cash flow means less resources to waste on unprofitable m&a’s.

Lang, Stulz and Walkling find that shareholders of bidding firms gain significantly more when the Tobin’s Q is high (1989). The Tobin’s Q is the total market value of the firm divided by the total asset value of the firm. A high Q is related to a well-managed firm and vice versa. The core of this is that value is created when a well-managed firm takes over a poorly managed firm, because the combined value will be higher. This synergy doesn’t exist when a poorly managed firm takes over a well-managed firm, this will only redistribute wealth of the bidder tot the target, which is not in favour of the bidder his shareholders.

An increase in legislation will also tamper with the abnormal return gained by the bidder. This finding by Jarrell and Bradley explains the difference that can occur in the results of researches spread over a large period of time (1980). In the paper of Schipper and Thompson it is assumed that an increase in regulation is paired with a negative impact on the acquiring firm because it causes higher costs involved in the merger activity (1983). This assumption made first hand is backed up by both results of Jarrel and Bradley (1980), and also Schipper and Thompson (1983). The addition of Bradley, Desai and Kim is that a change in regulation won’t have effect on the total synergetic gains, but it will have a significant impact on the distribution of the gains between bidder and target, shifting wealth from the acquirer to the target firm (1988). Further more difficulties in calculating abnormal return can arise because of the difference in relative firm size. For instance when comparing same sized bidder and target, and when bidder is ten times larger. The synergy involved measured in euros stays the same. But when abnormal return is measured, the percentage gain of the firm ten times larger is also ten times smaller. This makes it seem that the gain of relative large bidders is insignificant (Asquith, Bruner and Mullins 1983). Not only the relative size between bidder and target, but also the size of the acquirer in general has effect on abnormal return. When examining the research of Moeller Schlingemann and Stulz they conclude that the return on announcement for smaller acquiring firms is roughly 2 percentage points more (2004).

3. Research

3.1 Data & Sample

The selected sample consists of European acquiring company’s between January 4, 2010 and December 31, 2015. To get a sense of M&A activity in Europe a graph is given below that portrays the distribution across the countries. The graph is based on the data retrieved from the ZEPHYR database. As you can see United Kingdom takes the lead by far in merger activity. Because the UK takes in such a big part of our sample, an extra regression will be done without the UK firms in them to look if the outputs differ allot from the whole sample. This way it can be examined whether the UK firms drag all the results or not. Also another separate sample was computed to examine whether there is an effect surrounding the rumour date of the merger. The last pillar, others, contains European countries that had less then seven merger announcements during our sample period.

Following Zimmerman there are two leading M&A databases, which are broadly used (2006). There is the Mergerstat database that covers acquisitions when at least one of the firms involved is a US firms, and second there is the ZEPHYR database which is covers not only US but also M&A activity in the rest of

the world. ZEPHYR is said to be particularly useful when examining European deals, and since the focus of this study is Europe, the ZEPHYR database is used to conduct the deal data. To get the data fitting this research the following criteria are included in the ZEPHYR database: - All deals with Zephyr Editorial News

- Time period: on and after 04/01/2010 and up to and including 31/12/2014 (completed-confirmed, announced) - Listed/Unlisted/Delisted companies: listed acquirer - World regions: Eastern Europe, Western Europe, Euro-Area, European Union, European Union enlarged (28) (Acquirer) In addition to the search criteria also the announcement date and the acquirers ISIN number had to be displayed in the data. Both announcement date and ISIN number are needed in DataStream to find the daily stock prices matched by date and firm. Since ISIN number couldn’t be used as criteria, some of the data did not contain an ISIN number. Although Europe was entered as a criteria for the acquirer a few Japanese, Indian and US companies slipped through. All of these impurities in the data were selected and manually deleted from the sample, leaving a total of 904 firms in the selected data sample.

For the calculation of the abnormal return a peer group as market portfolio is needed. The market portfolio contains local indices of every stock. By using these local indices, the market portfolio considers the geographical distribution of the firms in the sample resulting in more accurate estimates of the 𝛼 and the 𝛽 and thus a better expected return.

Country Market index DataStream index Europe UK France Germany Sweden Switzerland Ireland Netherlands Spain Norway Italy Russia Denmark Finland Belgium SX5E FTSE100 CAC40 DAX OMXS30 SMI ISEQ AEX IBEX35 OBX FTSEMIB MIXEC OMXC20 OMXH25 BEL20 DJES50I FTSE100 FRCAC40 DAXINDX SWEDOMX SWISSMI ISEQUIT AMSTEOE IBEX35I OSLOOBX FTSEMIB RSMICEX DKKFXIN HEX25IN BGBEL20

Using these indices in DataStream gave some trouble because not all of them could be retrieved for the sample period. The countries whose indices weren’t found are the last four in the table above: Russia, Denmark, Finland and Belgium. Because the primary local index couldn’t be used, they are linked to the broader less accurate European index, EuroStoxx50. This is also done with the countries that were classified as “others”. Because not all stock data is available in the same currency, all non-euro stock prices were converted to euros using DataStream.

The last adjustment made to the sample is deleting the errors that were given in the DataStream output. Two different errors occurred and were all deleted: In some output the return values remained exactly zero and this is highly unlikely. Secondly some stock values couldn’t be retrieved for the specific dates. In the end left 855 valid firms with all the data available needed to get the results. The sample size without UK firms contains 527 mergers and the sample size of the rumour dates has 1175 mergers. 3.2 Methodology

For this research the difference of the actual return and the normal return without a merger announcement is measured. The problem is that the second of the two doesn’t exist, so it has to be estimated. The null hypothesis to the

question whether firms that function as the acquirer in a merger or acquisition incur an abnormal return will be:

H0: Acquiring firms do not incur abnormal returns

H1: Acquiring firms do incur abnormal returns

The results will be tested with a two-sided significance level because following the existing literature it is not clear whether the results will be negative or positive.

The limitation of the methodology used in this research is that it does not use control variables to check what might be the firm specific factors that influence the abnormal return. This is because there are few recent European papers on m&a. The importance of this paper was about the results and not which factors influence them, as this is already often studied ending up with similar results. The expectations as far as the results go are that the findings will be a bit negative, because this would explain why European m&a activity is at a low. Though it is hard to say what makes your results the same as other literature, because something as simple as different years can already make the results go the other way, next to complications in methodology used.

To answer the question an appropriate model will be chosen to compute the normal return needed. There are three options of modelling the normal return. First the single-index model, also know as the constant mean return model. This model assumes that the mean return of a stock is constant. The normal return would be calculated by taking the mean of the daily return observed in the estimation window. The market model assumes that the returns are driven by market returns. Third model is the CAPM, this is very similar to the market model because it also uses index market returns, but it also needs the daily risk free return. Since the sample contains a lot of small countries it complicates the use of the CAPM because all benchmarks for the risk-free rate have to be available, and thus the widely excepted market model of Warner and Brown is chosen (1985). According to Campbell et al the market model is an improvement over the single-index model and results in better identification of event effects (1997). The methodology is based on a rational marketplace where an event will directly affect the stock prices. According to Fama, Fisher, Jensen and Roll the traditional event study uses the calculation of the Cumulative

Average Abnormal Return (CAAR), which begins with the simple model below (1969): 𝑅𝑖𝑡= 𝛼𝑖+ 𝛽𝑖𝑅𝑚𝑡+ 𝜀𝑖𝑡

This is the first step of calculating the daily abnormal return surrounding the announcement date. Where 𝑅 is the normal return and 𝑅𝑚𝑡 is the return of the

country index chosen for security i, on time t. The 𝛼𝑖 and the 𝛽𝑖 are calculated for

each firm in excel using these two lines of data, this is done during the estimation window chosen. In this research the daily average abnormal returns are reported from day -5 to day +5, with cumulative average abnormal returns for the windows (-5,+5), (-1,+1) and (-5,-1). The last event window leaves doesn’t contain the announcement date but only a period before, this is to check whether there is a significant information leak. Below follows the time chart: Announcement date t=0 The estimation window chosen goes from t=-120 till t=-20 to get a good estimate for the alpha and the beta. The t=-20 is chosen because this way a possible information leak is excluded in the estimation of the alpha and beta. With the alpha and beta for each firm the abnormal return is calculated.

𝐴𝑅𝑖𝑡= 𝑅𝑖𝑡− 𝛼𝑖− 𝛽𝑖𝑅𝑚𝑡

Where ARit is the abnormal return for firm i on time t, and Rit the actual return.

With the abnormal returns calculated for every firm in the sample the average abnormal return is calculated for each day in the chosen event window. This is done by taking the mean value of the summation of the abnormal returns of the sample firms for day t.

𝐴𝐴𝑅𝑡= 1 𝑁 𝐴𝑅𝑖𝑡 ! !!! Because the max window chosen is (-5,+5), the daily average abnormal returns are reported from 5 days before and 5 days after the announcement. This is step 2 of calculating the CAAR, and helps to eliminate idiosyncratic risk. The corresponding test statistic is given by: 𝑡 𝑠𝑡𝑎𝑡𝑖𝑠𝑡𝑖𝑐 = 𝐴𝐴𝑅𝑡 𝜎𝐴𝑅 /√𝑁 Where 𝜎𝐴𝑅 is the standard deviation of the abnormal return of al firms on time t. For each firm the daily abnormal return in the event window is summed up to get the Cumulative Abnormal Return (CAR). 𝐶𝐴𝑅𝑖 𝑡1, 𝑡2 = 𝐴𝑅𝑖𝑡 !! !! The third and last step of calculating the CAAR for the event window is done by again taking the mean of the sum of every firms CAR. 𝐶𝐴𝐴𝑅 𝑡1, 𝑡2 = 1 𝑁 𝐶𝐴𝑅𝑖(𝑡1, 𝑡2) ! !!! The CAAR checks if there has been an effect over the time period instead of one day. This is helpful when the effect of the announcement is not only on the event date itself but spread over a period of time. The cumulative average abnormal returns are given in the results for the three event windows (-5,+5), (-1,+1) and (-5,-1) with the t-statistic test for their significance.

4. Results

In table 2 the results are shown for the daily average abnormal return on all eleven days of the event window. The reaction of the stock price varies over the days in the event window. As it begins slightly negative and goes to positive heading to the announcement date. Cannot say too much about it because before the announcement date all the results are not significant. Hitting the event date t=0 the average abnormal return turned out positive with a value of 0.549% and significant at a 1% level. The two days after it stays positive with on t=2 another significant positive AAR of 0.112% significant at 10%. The third and fourth day after the announcement is slightly negative again, this could be due to the stabilizing of the shock in the market, but then again they are just slightly negative and not significant. The result found at t=0 points out that there is a significant abnormal return for the acquirer. With a 1% significance the null hypothesis can be rejected and implies that there is an abnormal return for the acquirer firm in a merger or acquisition at the announcement date.

Table 2

Day AAR (%) t-statistic

-5 -4 -3 -2 -1 0 1 2 3 4 5 -0.012 -0.030 -0.014 0.042 0.004 0.549 0.119 0.112 -0.026 -0.003 0.017 -0.200 -0.584 0.204 0.496 0.063 2.849*** 1.226 1.686* -0.412 -0.044 0.215 Without UK t=0 0.392 2.435** The symbols *, ** and *** denote significance at the 10%, 5% and 1% respectively

The CAAR’s of the event windows (-1,+1), (-5,+5) and (-5,-1) are given in table 2. These are to test for a significant change over a spread of time. And both the (-1,+1) and (-5,+5) gave positive results significant at the 1% level where the window (-5,-1) is not significant at all. Also the CAAR is given for the sample without UK firms, which is significant and positive. The rumour date turned out to be positive but not significant. Table 3 Event

window CAAR (%) t-statistic

(-1, +1) (-5, +5) (-5, -1) 0.673 0.786 0.018 3.178*** 2.752*** 0.132 Without UK (-5, +5) 0.829 2.599*** Rumour date (-5, +5) 0.384 1.481 The symbols *, ** and *** denote significance at the 10%, 5% and 1% respectively

This indicates that not only the return on the announcement date is positively significant but is also significant when looking at multiple days surrounding t=0. The results place this paper on the positive abnormal return side of the existing literature with a high significance.

5. Conclusion

This research aims to answer the question if the announcement of a merger has a significant impact on the stock price return of the acquiring firm. To answer this question the movement of each individual firm’s stock price is observed and studied around the announcement date. After estimating their alpha and beta with the market model of Warner and Brown (1985) their cumulative average abnormal return was calculated in the eleven-day event period. The sample for this research consists of European mergers from 2010 until 2014. After deleting missing data the corrected sample included 855 firms, 527 for the sample without United Kingdom in it and 1175 for the rumour date sample.

The results found are that there is positive abnormal return created in in an Europe merger in the windows (-1,+1) and (-5,+5) with respectively a 0.673% and 0.786% increase. The results for the rumour date and the check for any information leak are both positive and not significant. The results for the second regression when the sample did not contain mergers from the UK turned out to have a slightly higher CAAR of 0.829% than the original model, in event window (-5,+5). But the difference isn’t that big that is should drag the main results. With this outcome the null hypothesis can be rejected, and the assumption can be made that acquiring firms do earn abnormal return.

The expectations of a negative abnormal return, because of the low M&A activity in the Europe area, contradicts the results found in this research. Therefor this research is of value because it adds to the literature on mergers and acquisitions with European data.

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Rankine, D., 2001, Why Acquisitions Fail. Great Britain: Pearson Education Limited

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Zimmerman, A., 2006, “Mergers and Acquisitions.” Available at Zimmerman’s Research Guide:http://www.lexisnexis.com/infopro/zimmerman/disp.aspx?z=1687

7. Appendix

Table 1

Study by Sample size Region/

Industry Sample period Event window Cumulative abnormal returns Dodd and Ruback (1977) 124 1958-1978 (0,0) +2.83%** langetieg (1978) 149 1929-1969 (-120,0) -1.61% Bradley (1980) 88 1962-1977 (+20,-20) +4.36%** Dodd (1980) 60 1970-1977 (-1,0) -1.09%**

Jarrel and Bradley (1980) 88 1962-1977 (-40,+20) +6.66%** Bradley, Desai and Kim (1982) 161 1962-1980 (-10,+10) +2.35%** Asquith (1983) 196 1962-1976 (-1,0) +0.20% Asquith, Bruner, and Mullins (1983) 170 1963-1979 (-20,+1) +3.48%** Eckbo (1983) 170 1963-1978 (-1,0) +0.07% Malatesta (1983) 256 1969-1974 (0,0) +0.90% Dennis and McConnel (1986) 90 1962-1980 (-1,0) -0.12% (-6,+6) +3.24%** Asquith, Bruner and Mullins (1987) 343 1973-1983 (-1,0) -0.85%** Varaiya, Ferris (1987) 96 1975-1987 (-1,0) -2.15%** (-20,80) -3.90%** Jarrel, Brickley and Netter (1987) 440 1962-1985 (-15,+5) 1.14%** Bradley, Desai and Kim (1988) 236 1963-1984 (-5,+5) +1.0%** Jarrell Poulsen (1989) 461 1963-1986 (-5,+5) +0.92%** Lang, Stulz and Walkling (1989) 87 1968-1986 (-5,+5) 0% Morck, Shleifer and Vishny (1990) 326 1975-1987 (-1,+1) -0.70% Loderer and Martin (1990) 970 US 1966-1968 (-5, 0) +1.72%** 3401 US 1968-1980 (-5, 0) +0.57%** 801 US 1981-1984 (-5, 0) -0.07% Franks, Harris and Titman (1991) 399 1975-1984 (-5,+5) -1.45% Byrd and Hickman (1992) 128 1980-1987 (-1,0) -1.2%** Healy, Palepu and Ruback (1992) 50 50 largest US mergers 1979-1984 (-5,+5) -2.2% Sirrower (1994) 168 1979-1990 (-1,+1) -2.3%** Smith and Kim (1994) 177 1980-1984 (-5,+5) +0.50% (-1,0) -0.23% Frame and Lastrapes (1998) 54 banking industry 1990-1993 (0,0) +1.44% Eckbo and Thorburn (2000) 390 US/Canada 1964-1984 (-40,0) -0.30% Eckbo and Thorburn (2000) 1261 Canada 1964-1983 (-40,0) +1.71%** Kohers and Kohers (2000) 961 High tech firms 1987-1996 (-1,0) +1.37%** cash

deals 673 +1.09%** stock 1634 +1.26% entire sample Leeth and Borg (2000) 466 1919-1930 (-40,0) +3.12%** Mulherin and Boone (2000) 281 1990-1999 (-1,+1) -0.37% Walker (2000) 278 1980-1996 (-2,+2) -0.84%** Delong (2001) 280 banking industry 1988-1995 (-10,1) -1.68%** Houston et al (2001) 64 banking industry 1985-1996 (-4,1) -3.47%**