The effect on the share price after a merger or acquisition of pharmaceutical companies around the announcement date

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The effect on the share price after a merger or acquisition of

pharmaceutical companies around the announcement date.

Thomas van Doorn

Student Number: 10260625

Bachelor Program Economics & Business Specialization Economics & Finance

Faculty of Economics and Business, University of Amsterdam Amsterdam, July 5th, 2015

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Statement of originality

This is to certify that to the best of my knowledge, the content of this thesis is my own work. This thesis has not been submitted for any degree or other purposes.

I certify that the intellectual content of this thesis is the product of my own work and that all the assistance received in preparing this thesis and sources have been acknowledged.

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Abstract

This thesis examines the effect of merger and acquisition announcements on the stock price of the top 100 mergers and acquisitions (measured in value of transaction) in the pharmaceutical industry between January 2010 and May 2015. An event study is used to calculate abnormal returns, where the S&P500 figures as the market index to calculate the expected returns. The empirical review used two event windows for the event study, namely [-2,+2] and [-20,+20], with an estimation window of [-100,-20]. From the 100 mergers and acquisitions, 80 target firms and 51 acquiring firms where included in the event study.

The target firms yielded an average cumulative abnormal return of 30.22% in the smallest event window. This return is significantly different than zero at a significance level of 5% due to the T-value of 7,93.

An average cumulative abnormal return of 3,50% has been the outcome of the event study in the smallest event window for the acquiring firms. This return is considerably smaller than that of the target firms, yet it is still significantly different than zero at a 5% significance level with a T-value of 2,86.

This paper can conclude from these results that the average abnormal returns around the announcement date of a merger or acquisitions in the pharmaceutical industry are positive and not equal to 0 at a significance level of 5%. Differently stated, the share prices of

pharmaceutical companies will increase around the M&A announcement date.

This conclusion is largely in line with other M&A studies in the pharmaceutical industry. Higgins and Rodriguez (2006) found positive average cumulative abnormal returns of 3.51 per cent for acquirers that operate within the same therapeutic category as the target firm. However, Hassan, Patra, Tuckman, and Wang (2007) only found positive abnormal returns on acquisitions, and not on mergers in the pharmaceutical industry.

The results of target firms are consistent with my predictions. However, the hypothesis on acquiring firms is rejected, because I didn’t expect to find positive cumulative abnormal returns on acquiring firms. Both my hypothesis on deal size and form of the transaction didn’t have enough statistical significance to be confirmed. Qualitatively, I found that higher

transaction values will lead to lower cumulative abnormal returns, and that mergers have a more positive influence on the CAR than acquisitions. However, both these results are not statistically significant.

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1. Introduction

Merger and Acquisition (M&A) is a phenomenon that has developed over the last 40 years. Most firms saw M&A as a corporate development to create growth and diversity. The popularity of M&A is shown by Cartwright and Schoenberg (2006): ‘In 2004, there were 30,000 acquisitions completed around the world, which equates to one transaction every 18 minutes.’

Whether the shareholders of the acquiring firm experience an increase in wealth from mergers and acquisitions is currently an on-going debate among academic researchers. Some of the researchers argue that mergers and acquisitions create synergies that will positively influence the wealth of both the acquiring company and the consumers (Weston, Mitchell and Mulherin, 2004). Others believe that M&A activities create agency problems and thus have managerial entrenchments. With managerial entrenchment, managers will direct the company in their own best interests instead of that of the firm, what will not result in an optimal return (Jensen, 1986).

There have been many studies on mergers and acquisitions. For example, Agrawal and Jaffe (2000) found that only 56% of the acquiring firms report that their acquisition has met the original objectives. Not many studies have been done specifically on the pharmaceutical sector, while in recent years M&A-activity in this sector has been really high. Therefore, this paper analyses mergers and acquisitions focusing on the pharmaceutical industry in the period 2010-2015. To get a look at what happens within a pharmaceutical firm during a merger or

acquisitions, this paper will take a look at the change in share price of the target and acquiring firm prior and after the announcement date.

The focus of this paper is specifically on the pharmaceutical industry for several reasons. At first, the pharmaceutical industry is globally active and engages in M&A-activities frequently. This high M&A-activity in this sector makes it interesting to research what the motives are for mergers and acquisitions to occur so frequently in the pharmaceutical industry are. Secondly, there are high cost of research and development in the pharmaceutical industry. Bringing drugs to the market has a low rate of success for drugs coming through the pipeline (Kola and Landis, 2004). The research and development department therefore can’t guarantee any certain return. This brings an extra incentive for both big pharmaceutical companies to use mergers and

acquisitions to supplement or substitute the early stages of research, as well as for small pharmaceutical companies, where the M&A-activities might be needed to survive these high costs. At last, in the pharmaceutical industry there is a high potential of abnormal returns to blockbuster drugs. When the new drug is a huge success, the returns can be extremely high. When these high returns are unexpected they will also yield high abnormal returns. For example, Pfizer’s cholesterol lowering drug Lipitor was acquired through M&A-activity and became a blockbuster drug in 2005 with global sales of over $12 billion (Bloomberg News, 2006). So, if abnormal returns exist, the pharmaceutical sector is a likely industry to find them. This thesis will start with a literature review on mergers and acquisitions in the pharmaceutical industry. Different forms of M&A as well as motives for these transactions will be discussed. After this literature study a short-horizon event study will be done on the 100 biggest mergers

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and acquisitions in the last 15 years in the pharmaceutical industry, which will measure the impact of the merger or acquisition on the value of the target and acquirer firm.

This thesis is organized as follows: Section 2 describes mergers and acquisitions in a theoretical context. It forms the basis to explain why mergers and acquisitions can create or destruct shareholder value. Section 3 describes the main findings of recent studies on the share price of merger and acquisitions around the announcement date. This section will also contain my hypotheses on this subject. After this, section 4 describes the data selection and the

methodology of the event study. Section 5 shows all the empirical results of this study. Finally, section 6 discusses the main findings and presents a conclusion on this paper.

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2. Literature Review

2.1 Types of Mergers and Acquisitions

A merger is defined as two firms forming a new company together (Shy, 1995). The stocks of both separately owned companies are surrendered and new stocks in the name of the new company are issued. During an acquisition, one firm takes over another and will be the single owner of the two firms. The firm that is taking over runs the entire company with its own identity. Different than in mergers, stocks of the acquired company are bought by the public ahead of the acquisition and are not surrendered. These stocks continue to be traded in the stock market.

According to Grinblatt and Titman (2002) there are three types of mergers and acquisitions, namely strategic-, financial-, and conglomerate acquisitions. Strategic acquisitions are mergers and acquisitions focused on synergies. This strategic method wishes to ensure cost savings and increased profits. Financial acquisitions are mergers and acquisitions where the acquirer

believes the target stock are undervalued. The aim of this method of merger or acquisition is to raise the undervalued shares of the target stock by reorganization. Lastly, conglomerate

acquisitions are mergers and acquisitions where two firms operate in different types of business. Extending corporate territories and extending a product range are two important purposes of conglomerate acquisitions.

These three types of mergers and acquisitions can also be identified in two integration methods of mergers and acquisitions. Firstly, horizontal integration happens when there are mergers and acquisitions between firms in the same industry. These firms are often competitors and are offering the same goods or services. Second, vertical integration are mergers and acquisitions where the two firms operate at a different level of the supply chain in the same industry. This merger or acquisition can decrease the dependence and thereby increase their profitability.

This paper is focused on the strategic- and financial acquisition types, because most M&A’s in the pharmaceutical industry are strategic- and financial acquisition types. The conglomerate acquisition will not be the main focus, because here the acquisition has to include business from another industry and this paper focuses only on the pharmaceutical sector. Horizontal and vertical integrations are both often used in the pharmaceutical sector and therefore both important to this study.

2.2 Motives

According to Cartwright and Schoenberg (2006) the use of mergers and acquisitions in firms is increasing every year. All mergers and acquisitions happen with certain motives. In this section these motives will be classified. Motives that increase the value of the firm are listed under section 2.2.1. Motives that decrease the value of the firm but increase the wealth of the manager are listed under section 2.2.2.

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2.2.1 Motives that increase shareholder value

Motives that increase the firm value are shareholder gains. A shareholder gain is the growth in the firm’s market value due to the merger or acquisition. This is called the

shareholder gain since a market value increase of the firm directly benefits its shareholders. Motives that raise the shareholder value are discussed in the next 7 paragraphs: efficiency gains, synergy gains, cost savings, financial cost savings, market power, pre-emptive and defensive M&A, and disciplinary takeovers.

Farrell and Shapiro (2001) showed in their paper that there are efficiency gains in mergers and acquisitions. According to them, these efficiencies correspond to changes within the joint production capabilities of the merging parties. Efficiency gains can be divided into economies of scale and economies of scope. A firm is said to have economies of scale when the average cost of production falls while the production level increases. Firms with higher economies of scale turn to advantage since fixed costs (and overhead) can be spread over more units, which results in a lower cost per unit produced (Tirole, 1988). According to Panzar and Willig (1982),

economies of scope are cost savings that result from the scope, rather than the scale, of the firm. With economies of scope, the average total cost of production decreases as a result of increasing the number of different goods produced. For example, it is less costly to combine two or more product lines in one firm than to produce them separately. Both economies of scale and economies of scope are relevant arguments for the pharmaceutical M&A-sector. Especially the economies of scale are important for smaller pharmaceutical firms to overcome the high fixed costs of the drug market.

Synergies are the potential benefits of combining the firms that go beyond the technical efficiencies of economies of scope and scale. Various factors, such as combined talent and technology, affect the synergies and influence the merged firm in a positive way. Synergies can be divided into diffusion of how and into research and development. Diffusion of know-how is explained by Roller, Stennek and Verboven (2006, p.17): “Firms may have different technological or administrative capabilities due to different patents, different experiences, a different management or organisation. A merger between firms with different characteristics may then lead to a diffusion of know-how across the participants. This can bring the firms closer to their joint production possibility frontier, without shifting the frontier itself.” Such a

technological progress can take the form of product or process innovation. This product or process innovation can be extremely important for pharmaceutical companies. With better products and processes to make their medicines, pharmaceutical firms might produce that one blockbuster drug more easily. Roller, Stennek and Verboven (2006) also pointed out that research and development (R&D) is a powerful non-tradable asset that can experience future growth. By developing new products or processes the firm will improve and expand their operations. Merging firms in the pharmaceutical industry generally claim that by merging their R&D departments, together they are able to faster introduce new or better quality products and at the same time innovate in cost reducing processes.

Next to these efficiencies, cost saving is an important motive for firms to get involved into M&A-activity. Lowering variable- and fixed cost savings are all cost savings that are not financial cost

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savings. The financial costs savings will be dealt with in the next paragraph. Variable costs are costs that vary with production. Conversely, fixed costs are the costs that do not vary with production. Reorganization is the most important cost saving motive for M&A-activity. After a merger or acquisition, a more optimal reallocation of production can be established. For example, shifting production from a production line with higher marginal costs to another with lower marginal costs will be cost saving.

Financial costs are costs that do not lower the cost of production, but only change the

distribution of costs within the company (Roller, Stennek and Verboven, 2006). Financial costs motives are to get better interest rates and to get involved into diversification. For small firms in the pharmaceutical industry, liquidity constraints can make it complicated to borrow at a

competitive interest rate. For these firms, merging will be a solution since larger firms have better access to the capital market. Diversification is a technique for reducing non-systematic risk by investing in a variety of assets. The modern portfolio theory of Markowitz (1952) is the main driver of this motive. This financial strategy has its focus on the composition of a portfolio that is selected on their overall risk-return performance. This portfolio consisting of multiple mergers or acquisitions will also reduce the risk of bankruptcy. For the pharmaceutical company diversification can be a relevant motive to get involved into M&A-activity because when a big firm sells multiple drugs it will be less risky and more diversified to apply to diseases that occur in the world.

The ability of a firm to manipulate and raise its prices above marginal costs is called market power. Excessive market power can be described as the ability to exclude competitor firms in their segment. Gaining market power is a relevant motive for pharmaceutical mergers and acquisitions since large firms want to grow even larger and use market power to set their own prices of the drugs they produce. Farrell and Shapiro (1990) found general conditions under which horizontal mergers raise price. According to them, this raise in price is solely due to the increased market power of the firm.

Motives to gain market power through a merger or acquisition are: through unilateral effects, collusion, and to raise entry barriers. Unilateral effects are present in horizontal mergers and are characterized by the hazard that the merged company finds it profitable to increase their price after their unification. Collusive behaviour occurs when firms agree to set prices, fix output quotas and avoid competitive pressures. These coordinated effects are important in horizontal mergers because with a smaller amount of competitors it’s easier to detect

deviations from the agreed upon collusion. Collusion is unlikely when there aren’t entry barriers for new firms to enter the sector. So, raising entry barriers will increase a firm’s market power. Merging with other firms can potentially raise entry barriers if for example the merger or acquisition consolidates two competing technologies. It will be costly for competitors to match these technologies and therefore considered as an entry barrier.

According to Fridolfsson and Stennek (2005), pre-emptive and defensive motives can also lead to a merger or acquisition in the pharmaceutical industry. Quoted from their work (2005, p. 1083): “We provide a possible explanation for the empirical puzzle that mergers often reduce profits, but raise share prices. If being an ‘insider’ is better than being an ‘outsider’, firms may

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merge to pre-empt their partner merging with a rival. The insiders’ stock market value is increased, since the risk of becoming an outsider is eliminated. These results are derived in an endogenous- merger model, predicting the conditions under which mergers occur, when they occur, and how the surplus is shared.” So, according to Fridolfsson and Stennek (2005), mergers and acquisitions can be motivated by a pre-emptive or defensive strategy.

Disciplinary takeovers are takeovers where managers of the acquiring firm believe that a target firm can be managed better and can thus create a profit. M&A-activity in the pharmaceutical industry can be driven by the fact that managers believe that a firm is undervalued. If so, pharmaceutical acquirers can make a profit out of this merger or acquisition. The rational behind these disciplinary takeovers can be divided into a motive for corporate control and a motive for the acquiring of free cash flows. The motive of corporate control states that when managers of the acquiring firm believe the takeover firm is undervalued, they will merge and replace its management to increase their joint profits. This is an efficient market theory as managers who are incompetent or not pursue goals in the shareholder’s best interest will be eliminated. Some companies have high free cash flows where the excess of free cash flows is due to an inefficient management of the company. These companies with high free cash flows are often targets of hostile takeovers. Managers of the acquiring company believe that they can create a profit of this excess of free-cash flows.

2.2.2 Motives that decrease shareholder value

In this section, two motives that decrease shareholder value will be discussed. These motives are agency problems and hubris.

Managers are supposed to direct the company in the shareholders’ best interest, that is maximize shareholder wealth. However, sometimes the manager actually wants to create personal wealth by maximizing their managerial gains. This is shown by Mueller (1969, p. 644): “Managerial salaries, bonuses, stock options, and promotions all tend to be more closely related to the size or changes in size of the firm than to its profits. Similarly, the prestige and power which managers derive from their occupations are directly related to the size and growth of the company and not to its profitability.” Motives that are influenced by managerial gains are commonly called ‘the agency problem’ and will decrease the value of the firm. Conclusive, the agency problem is a conflict of interest between the management of the firm and the firms’ shareholders.

Agency problems occur more easily with mergers and acquisitions, because in bigger firms it’s easier for managers to act in their own best interest. This holds true because in bigger companies, dispersion of the shareholders is larger and the board can’t constantly keep an eye on the managers.

Managers who act in the firms’ best interest strive for maximization of shareholders wealth and are looking for synergies in M&A decisions. Hubris states that despite these good intentions the managers incorrectly overestimate the synergetic gains and end up overpaying for a target that might have no synergies at all (Roll, 1986). The most important example of hubris in the

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and development can be positively influenced by M&A-activity as shown by the synergy motive in sector 2.2.1. However, there are academic researchers who think that research and

development will not benefit from mergers and acquisitions. According to them, merging firms today make cuts on research and development and eliminate entire research sites. LaMattina (2011, p. 559) showed this with an example on the pharmaceutical company Pfizer Inc.: “Before 1999, Pfizer had never made a major acquisition. Over the next decade, it acquired three large companies — Warner-Lambert (in 2000), Pharmacia (in 2003) and Wyeth (in 2009) — and multiple smaller companies, such as Vicuron, Rinat and Esperion. Over this time frame, to meet its business objectives, Pfizer closed numerous research sites in the United States, including those at Kalamazoo, Ann Arbor, and Skokie, Illinois. It has also recently announced the closure of the Sandwich site in the UK. These sites housed thousands of scientists, and many major drugs — such as atorvastatin (Lipitor), amlodipine (Norvasc) and sildenafil (Viagra) — were discovered there. The same pattern has been observed after most of the mergers and acquisitions by other major pharmaceutical companies during the past decade.” 2.3 Literature Review conclusions

All mergers and acquisitions happen with certain motives. As shown, motives can

increase the value of the firm but can also decrease firm value. All these motives are relevant to the pharmaceutical industry. However, it is hard to tell which of these above motives convinces the management of the firm to get involved in M&A-activity. Therefore, it is difficult to see in advance if a merger or acquisition will create or destroy firm value. To get a better

understanding in the value-effect of the merger or acquisition, further research will be needed and is done in section 4.

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3. Empirical evidence

3.1 Findings from recent studies

Other academic researchers have investigated the effects of mergers and acquisitions in the pharmaceutical industry. In this section the results of these recent studies are shown: Danzon, Epstein and Nicholson (2007) analysed the determinants and effects of significant M&A transactions across the entire pharma-biotech industry over the period 1988-2000. Among large firms (over $20 million in sales and $1 billion in market value) they found that firms with a low Tobin’s q (the market value of a company divided by the replacement value of the firm's assets), hence with a low expected earnings growth, are more likely to acquire another firm. For small firms, mergers appear to be primarily an exit strategy. Danzon, Epstein and Nicholson (2007) also found that firms with a high propensity to merge have low growth rates in R&D

expenditure and sales regardless of whether they merge or not. This implies a negative post-merger return.

Hassan, Patra, Tuckman, and Wang (2007) analysed mergers and acquisitions focusing on the U.S. pharmaceutical industry in the period 1981-2004. They found two results:

First, no abnormal returns on mergers in the pharmaceutical industry were found. This holds true both for US pharmaceutical mergers with other US-based companies as for US

pharmaceutical mergers with foreign-based companies. Secondly, pharmaceutical acquisitions, which are investigated separately from mergers, indicate a statistically significant positive abnormal return. According to Hassan, Patra, Tuckman and Wang (2007, pp. 17-18) “This makes intuitive sense because bigger pharmaceutical companies acquire a patent, division, or a smaller biotech company for strategic reasons and the market reacts positively if the acquisition is considered value-adding to the existing product portfolio of the acquiring company. In contrast, mergers, particularly of large companies, may contain return reducing, as well as profit

enhancing, elements or they may not be sufficient to augment a weak pipeline.” As a result, the merger may end up with modest or even negative returns.

Higgins and Rodriguez (2006) investigated the outsourcing of research and development through acquisitions in the pharmaceutical industry. The sample for this analysis included firms who are present in Recombinant Capital’s alliance data set from 1994-2001 and who both have sales and pipeline data available. Higgins and Rodriguez found positive average cumulative abnormal returns of 3.51 per cent for acquirers that operate within the same therapeutic category as the target firm. Next to that, they found that this abnormal return is lower for acquirer firms that are not within the same therapeutic category as the target firm, namely 2.57 per cent abnormal return.

3.2 Hypotheses

As discussed earlier in the introduction, the focus of this paper is specifically on the pharmaceutical industry for several reasons. The pharmaceutical industry is globally active, engages in M&A activities frequently, has high fixed cost due to research and development, and bringing drugs to the market has a low rate of success for drugs coming through the pipeline

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(Kola and Landis, 2004). However, when the new drug is a huge success, the returns can be extremely high. When these high returns are unexpected, they will also yield high abnormal returns. The above reasons make the pharmaceutical industry different than any other market. If abnormal returns exist, the pharmaceutical sector is a likely industry to find them.

As findings from previous studies in the pharmaceutical industry show, there are different outcomes on abnormal returns due to M&A-activity. Given the potential for high returns from all the motives discussed in section 2, it seems likely that if M&A is wealth enhancing in general, we should also find this effect for the pharmaceutical industry. From 13 merger and acquisition studies in industries other than the pharmaceutical industry, Jensen and Ruback (1983)

concluded that target firms earn cumulative abnormal returns of 20% to 30%. Therefore, the following hypothesis is formulated:

Hypothesis 1: Target firms posses significantly positive abnormal returns at a 5% significance level around the announcement date.

For acquiring firms, Jensen and Ruback (1983) found negative cumulative abnormal returns between -1% and -5%. According to these researchers there where also positive abnormal returns for acquiring firms, but these results are very small. Therefore, the following hypothesis is formulated:

Hypothesis 2: Acquiring firms posses significantly negative abnormal returns at a 5% significance level around the announcement date.

According to Moeller and Schlingeman (2005), smaller firms have higher cumulative abnormal returns than bigger firms. Larger firms are more affected by over-valuation according to these researchers, which results in lower returns. Unlike these results, Fuller, Netter, and Stegemoller (2002) found the opposite results. However, Peterson and Peterson (1991) are in line with Moeller and Schlingeman (2005) and show that smaller firms have higher cumulative abnormal returns. According to them, bidding firms pay a higher premium to small firms than to larger target companies. Therefore, the following hypothesis is formulated:

Hypothesis 3: The cumulative abnormal returns of smaller firms are more positive than for larger firms around the announcement date.

As already discussed, Hassan, Patra, Tuckman, and Wang (2007) only found positive abnormal returns on acquisitions, and not on mergers in the pharmaceutical industry. Therefore, my last hypothesis is formulated:

Hypothesis 4: The abnormal return pattern around the announcement date is bigger with acquisitions in comparison to mergers.

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4. Data and methodology

4.1 Sample selection

This thesis focuses on the biggest mergers and acquisitions that have taken place in the pharmaceutical industry in a five-year period from January 2010 until May of 2015. This section will look into the share prices of these pharmaceutical mergers and acquisitions to examine what happens with this share price pre- and post-merger announcement.

The data for these pharmaceutical mergers and acquisitions is found by searching the Thompson One database. The Thompson One database, formerly known as SDC Platinum, provides detailed firm specific information such as deal values, payment methods etc. For the restrictions of this data in Thompson One, see Appendix 1. In this paper, the sample selection contains 100 pharmaceutical mergers and acquisitions that have the highest value of

transaction. DataStream codes where available in Thompson One, so the pharmaceutical transactions could be directly transported into the DataStream database.

DataStream is a financial database that contains firm data, equities and macroeconomic data. This paper found most of the daily stock prices prior and past to the announcement date of the transaction in the DataStream database from the university of Amsterdam. The top 100 mergers and acquisitions with the highest value of transaction are used in this paper and are shown in Appendix 2. However, not all these 200 firms (100 targets and 100 acquirers) had share prices that where available in DataStream. The firms without a valid DataStream code, and thus without share prices available, are coloured in red.

Next, the statistical program Stata calculates the event study and needs a sufficient amount of share price information to compute the event and estimation window. All firms coloured in yellow in appendix 2 did not have enough share price information and are excluded from the event study. The event study eventually contained of 80 target firms and 51 acquirer firms.

In Stata, share price performance of the pharmaceutical companies in the dataset are compared to the S&P500 index. The S&P500 is used over the same five-year period (2010 – 2015) as the share price information. The S&P500 is a good benchmark for the pharmaceutical industry since it is a capped market capitalization weighted index of 500 large companies and one of the most commonly followed equity index. The DataStream database is used again to collect the S&P500 data.

4.2 Methodology

According to Bruner (2002), there are four approaches to measure profitability of

mergers and acquisitions. These four methods are: event studies, accounting studies, surveys of executives and clinical studies. This paper measures profitability of mergers and acquisitions in the pharmaceutical industry through abnormal returns. The abnormal return is the difference between the actual return and the expected return. This paper will perform four types of event studies, two on the target companies and two on the acquirer companies.

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To calculate the expected return on the share prices of our pharmaceutical firms, this paper will make use of the market model of Brown and Warner (1980). According to Armitage (1995) an estimation window of 100-300 days prior to the event of interest is sufficient for an assessment of all the normal market model parameters. Therefore, an estimation window of 100 to 20 days prior to the announcement date will be used in the event study of this paper. The market model determines a required rate of return of an asset, given the asset’s non-diversifiable risk. The market model is described as follows:

𝑅̃

_𝑖𝑡

= 𝛼

_𝑖

+ 𝛽

_𝑖

∗ 𝑅

_𝑚𝑘𝑡

+ 𝜀

_𝑖𝑡

(𝑡 = −100 ; 𝑡 = −20)

(1)

In this model, 𝑅̆̃𝑖𝑡 is the actual return for share i in time period t (from 100 to 20 days prior to

the announcement date). Ordinary least square regression (OLS) in the statistical program Stata is used to calculate the parameters alpha (𝛼) and beta (𝛽) of this model. The return of the market (𝑅𝑚𝑘𝑡) is determined by the S&P 500 stock index over a period of 100 to 20 days prior to

the announcement date. Finally, 𝜀𝑖𝑡 is the error term.

The event windows for this study are [-20 ; +20] and [-2 ; +2]. The [-X ; + Y] notation of event windows is used where –X are the days prior to the announcement date and +Y are the days after the announcement date. The market model (1) calculated the expected return and now the abnormal returns (𝐴𝑖𝑡) for each of the two event windows can be estimated:

𝐴

_𝑖𝑡

= 𝑅

_𝑖𝑡

− 𝑅̃

_𝑖𝑡 (2)

𝐴

_𝑖𝑡

= 𝑅

_𝑖𝑡

− (𝛼

_𝑖

+ 𝛽

_𝑖

∗ 𝑅

_𝑚𝑘𝑡

+ 𝜀

_𝑖𝑡

)

(3)

Here, 𝑅𝑖𝑡 is the actual return for share i on day t.

Next, all daily abnormal returns are averaged for each event day across N securities:

𝐴

_𝑡

̅̅̅ =

1

𝑛

∑

𝐴

𝑖𝑡 𝑛

𝑡=1 (4)

Finally, the cumulative abnormal returns (CARs) are computed by summing the daily average abnormal returns for the total period of interest:

𝐶𝐴𝑅

̅̅̅̅̅̅

_(𝑡

1;𝑡2)

= ∑

𝐴

̅̅̅

𝑡 𝑡₂

𝑡=1 (5)

In formula (5), the cumulative abnormal returns are calculated for each two of the event windows from 𝑡1 to 𝑡2. Calculations of the minimum/maximum CAR, the average CAR and the

median CAR of the total sample of firms are computed in Excel.

To test the statistical significance of the abnormal average returns and the cumulative average abnormal returns, and therefore test the hypothesis, a T-test is done in Stata. This T-test is calculated with the following formula:

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𝑇 − 𝑇𝑒𝑠𝑡 =

𝐴

̅̅̅

𝑡

𝑆𝐷(𝐴_𝑖𝑡) √𝑁

⁄

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When the T-value of this test is larger than 1.96, the average abnormal return for that firm will be significantly different from zero at a 5% significance level. With this T-test, the cumulative abnormal returns for target firms and for acquiring firms will be tested. This will give a result on my hypotheses 1 and 2.

To test the hypotheses 3 and 4 I will make use of a regression analysis in excel. The two

determinants deal size (hypothesis 3) and form (hypothesis 4) are investigated for the two event windows and for both acquiring and target firms. The significance of these results will be tested with a p-value. If the p-value is smaller than 0.05, the result is statistically different than zero at the 5% significance level. In formulas, the hypothesis are described as follows:

Hypothesis 3, deal size: If the value of the transaction is bigger than the median of the entire sample, the value ‘1’ is assigned. If the value of the transaction is smaller than the median, the value ‘0’ is assigned. The regression formula is:

𝐶𝐴𝑅 = 𝛽₁+ 𝛽₂𝐷𝑒𝑎𝑙 𝑠𝑖𝑧𝑒 + ℯ

Where, 𝛽𝐷𝑒𝑎𝑙 𝑠𝑖𝑧𝑒 = A dummy variable for the deal size of the firm

Hypotheses 4, form: If the form of the transaction is a merger, than the value ‘1’ is assigned. When the form of the transaction is an acquisition, than the value ‘0’ is assigned. The regression formula is:

𝐶𝐴𝑅 = 𝛽₁+ 𝛽₂𝐹𝑜𝑟𝑚 + ℯ

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5. Empirical results

This section will present and discuss the empirical findings of this study. Here, the results of the short-term event study of the 100 pharmaceutical mergers or acquisitions are shown. The event study is done on target and on acquiring firms. The total average cumulative abnormal returns are calculated by averaging all the single cumulative abnormal returns of the firms. The single cumulative abnormal returns are shown in Appendix 3 for target firms with an event window of [-2,+2], in Appendix 4 for target firms with an event window of [-20,+20], in Appendix 5 for acquirer firms with an event window of [-2,+2], and in Appendix 6 for acquirer firms with an event window of [-20,+20].

The average cumulative abnormal returns of the target and acquiring firms in the two different event windows are shown in table 5.1. This table also presents the T-value of the total sample of firms. The sample is based on 100 firms as is discussed in section 4. However, due to lacking stock price information in the DataStream database, the final sample size was reduced to 80 target firms and 51 acquiring firms.

Table 5.1: Average CAR of Target and Acquiring firms Event window

Target Firms (N=80) Acquiring Firms (N=51)

Av. CAR T-value Av. CAR T-value

[-2,+2] 30,2217% 7,93* 3,5048% 2,86*

[-20,+20] 29,8403% 6,38* 3,8992% 2,30*

*Significant at the 5% level or better

For target firms, table 5.1 shows some serious positive cumulative abnormal returns. And in both event windows these result are significantly different than zero at the 5% level. This result is consistent with hypothesis 1. For the target firm, when the event window moves closer to the announcement date, the average cumulative abnormal return of the sample will increase. For acquiring firms, table 5.1 also shows positive shareholder wealth effects, but these results are not so substantial as for the target firms. Still, these results are significantly different than zero at the 5% level according to the large T-value. Remarkably, this is inconsistent with my second hypothesis where I expect to find no significant cumulative abnormal returns for

acquiring firms. Also different than with the target firms, here the average cumulative abnormal return of the sample decreases when the event window moves closer to the announcement date.

That target firms have a higher average cumulative abnormal return compared to acquiring firms is consistent with the study of Andrade, Mitchell & Stafford (2001). According to them, when mergers or acquisitions create shareholder wealth, most of these abnormal returns appeared from the target firm.

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In table 5.2, the descriptive statistics of the target and acquiring firms are shown. These

statistics are calculated for the [-2.+2] event window. This table specifically makes a distinction between the positive and negative cumulative abnormal returns of all the single firms in the sample.

Table 5.2: Descriptive statistics of Target and Acquiring firms in the [-2,+2] event window. Target Firms (N=80) Acquiring Firms (N=51) Negative CAR Positive CAR Negative CAR Positive CAR

Number 7 73 17 34

Minimum CAR -8,4601% 0,6404% -15,9577% 0,0025%

Maximum CAR -0,5300% 234,5517% -0,0630% 30,4687%

Mean -4,3912% 33,5407% -3,8772% 7,1958%

Median -4,6323% 25,6613% -3,7579% 3,0208%

No fewer than 73 out of 80 target firms in our sample have positive cumulative abnormal returns. Even a maximum return of 234,55% is achieved by the target firm Idenix

Pharmaceuticals Inc. that was acquired by Merck&Co. The average of the abnormal returns that are positive is 33,54% and the median of these positive returns is 25,66%. Only 7 target firms have negative abnormal returns, where the minimum abnormal return isn’t really impressive, namely only a shareholder wealth loss of -8,46%.

The abnormal returns of acquiring firms are a bit more spread out. 34 Pharmaceutical firms obtain positive abnormal returns that have an average return of 7,20%. However, 17 acquiring firms obtain negative abnormal returns, who together have a mean return of -3,88%. This is why the 51 acquiring firms together achieve an abnormal return of 3.50%, as is shown in table 5.1. The results of our two regressions for target firms are summarized in table 5.3 and in table 5.4 for acquiring firms.

Table 5.3: Regression results of target firms in the form 𝐶𝐴𝑅 = 𝛽1+ 𝛽2𝐷𝑒𝑡𝑒𝑟𝑚𝑖𝑛𝑎𝑛𝑡 + ℯ

[-20,+20] [-2,+2]

Determinants N 𝜷_𝟏 𝜷_𝟐 P-value 𝜷_𝟏 𝜷_𝟐 P-value

Deal size 80 28,7081 2,2645 _0,80975 _31,2004 _-1,9575 _0,7983

Form 80 24,0338 6,6360 0,64058 20,4304 11,2209 0,3313 For target firms, the determinant deal size shows no significant results in both the event

windows because of their high P-values. So for target firms, hypothesis 3 is not supported by the result of my regression. The determinant form as well only shows qualitative support in both event windows, which is not statistically significant. Conclusively, hypothesis 4 can’t be confirmed with these results.

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Table 5.4: Regression results of acquiring firms in the form 𝐶𝐴𝑅 = 𝛽1+ 𝛽2𝐷𝑒𝑡𝑒𝑟𝑚𝑖𝑛𝑎𝑛𝑡 + ℯ

[-20,+20] [-2,+2]

Determinants N 𝜷_𝟏 𝜷_𝟐 P-value 𝜷_𝟏 𝜷_𝟐 P-value

Deal size 51 4,4124 -1,0066 0,7696 4,3115 -1,5825 0,5238 Form 51 -4,6251 9,2499 0,14352 0,0399 3,7598 0,4147

The regression with 51 acquiring firms also stated no significant results. Qualitatively, the deal size coefficient is negative in both the event windows which indicate that higher transaction values will lead to lower cumulative abnormal returns. However, hypothesis 3 is not supported because of statistical insignificancy. Hypothesis 4 can’t be confirmed either because of their high p-value. However, both results of the form determinant are qualitatively positive.

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6. Conclusion

This paper measured abnormal returns on mergers and acquisitions in the pharmaceutical industry. These abnormal returns are calculated to evaluate the shareholder wealth effects around the announcement date of a merger or acquisition.

With a short-term event study, I found that target firms’ shareholders gain significantly from the announcement of a merger or acquisition for two different time periods. The event study found average cumulative abnormal return of 30.22% for target firms in the smallest event window. This return is significantly different than zero at a significance level of 5% due to the T-value of 7,93. For target firms, the bigger the event window, the smaller the return for target firms becomes.

For acquiring firms I found a positive shareholder wealth effect for the acquiring firms in two different time periods. An average cumulative abnormal return of 3,50% has been the outcome of the event study in the smallest event window. This return is considerably smaller than of the target firms, yet it is still significantly different than zero at a 5% significance level with a T-value of 2,86. These results on acquirer firms are comparable with the result of Higgins and Rodriguez (2006) who found positive average cumulative abnormal returns of 3.51 per cent for acquirers that operate within the same therapeutic category as the target firm.

When combining the results of the target and acquiring firms together, this paper can state that the average abnormal returns around the announcement date of a merger or acquisitions in the pharmaceutical industry are not equal to 0 at a significance level of 5%. This holds true because all the above results rejected my null hypothesis with a T-value larger than 1.96. Differently stated, an answer to the research question would be that share prices of pharmaceutical companies will increase around the M&A announcement date. One of the arguments that the pharmaceutical industry is different than other industries is because of their high potential of abnormal returns to blockbuster drugs. This can be the reason why I found so many positive abnormal returns in my event study.

This research found no significant results for both the target and acquiring firms at the regressions on cumulative abnormal returns for deal size and form. Therefore, the determinants deal size and form had no explanatory power with the cumulative abnormal return. Because of this insignificance, our hypothesis on transaction value and form could not be confirmed. Two limitations of this study can be indicated. The first constraint is the limited number of firms that are in the event study due to unavailable share prices. According to Schenk (1996), only event studies with a sample size of at least 100 mergers or acquisitions can be classified as scientific research. As already discussed, the sample size in this paper is reduced to 80 target and 51 acquiring firms because of insufficient data.

A second limitation is directed to the efficient market hypothesis. The abnormal returns of target and acquiring firms reflect an overview of the shareholders wealth. This theory is only credible when the share prices perfectly reflect available market information, and thus when the efficient market hypothesis is assumed. However, Danzon, Epstein and Nicholson (2007) showed in their paper that in industries like the pharmaceutical industry, there are constant

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informational asymmetries. These informational asymmetries can cause that abnormal returns on share prices do not reflect shareholder wealth perfectly.

Further research can be done by investigating the pharmaceutical industry in more subsection to see if these subsections have different cumulative abnormal returns. Subsections can be geographical (Europe, VS, Asia) and for example in the pharmaceutical industry (healthcare, biotechnology, supplies). Another part of further investigation can be a multivariate regression with more determinants (for example EBIT, Total Assets, liquidity, volatility etc.) on cumulative abnormal returns, to see if these results will be different than mine and perhaps significant.

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Appendices

Appendix 1: Restrictions of this data in Thompson One

Data restrictions Sample

Available M&A Data in Thompson One with a target mid industry:

Biotechnology, Healthcare Equipment & Supplies, Pharmaceutical

32223

With a date effective/unconditional: Between 01/01/2010 to 05/30/2015

6124 Deal type: Discloded Value M&A 4600

Target Public Status: Public 385

Deal Status: Completed/Unconditional 385 Value of transaction: Top 100 100

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Appendix 2: Top 100 M&A with highest value of transaction in period 2010-2015

Target ID Target Name Acquioror ID Acquioror Name

Date Announced

Value of Transaction ($mil)

1 Auspex Pharmaceuticals Inc 101 Teva Pharmaceutical Industries 03-30-2015 $3.394,01 2 Hyperion Therapeutics Inc 102 Horizon Pharma PLC 03-30-2015 $1.017,06 3 Pharmacyclics Inc 103 AbbVie Inc 04-03-2015 $20.773,97 4 Salix Pharmaceuticals Ltd 104 Valeant Pharmaceuticals Intl 02-22-2015 $14.467,61 5 Foundation Medicine Inc 105 Roche Holding AG 12-01-2015 $780,21 6 NPS Pharmaceuticals Inc 106 Shire PLC 11-01-2015 $5.138,90 7 Volcano Corp 107 Koninklijke Philips Electn 12-17-2014 $947,58 8 Cubist Pharmaceuticals Inc 108 Merck & Co Inc 08-12-2014 $9.334,67 9 Avanir Pharmaceuticals Inc 109 Otsuka America Inc 02-12-2014 $3.427,68 10 Prosensa Holding BV 110 BioMarin Pharmaceutical Inc 11-24-2014 $801,06

11 Allergan Inc 111 Actavis PLC 11-17-2014 $68.445,40

12 Durata Therapeutics Inc 112 Actavis PLC 06-10-2014 $799,82 13 CareFusion Corp 113 Becton Dickinson & Co 05-10-2014 $12.000,11 14 Auxilium Pharmaceuticals Inc 114 Endo International PLC 09-16-2014 $1.838,92 15 InterMune Inc 115 Roche Holding AG 08-24-2014 $8.314,53 16 Nobel Biocare Holding AG 116 Danaher Corp 07-29-2014 $2.114,64

17 Covidien PLC 117 Medtronic Inc 06-15-2014 $42.729,87

18 Idenix Pharmaceuticals Inc 118 Merck & Co Inc 09-06-2014 $3.828,16 19 CFR Pharmaceutical SA 119 Abbott Laboratories 05-16-2014 $3.334,30 20 Chelsea Therapeutics Intl Ltd 120 H Lundbeck A/S 08-05-2014 $647,65 21 Furiex Pharmaceuticals Inc 121 Forest Laboratories Inc 04-28-2014 $1.436,41 22 Ranbaxy Laboratories Ltd 122 Sun Pharmaceutical Inds Ltd 07-04-2014 $3.225,51 23 Questcor Pharmaceuticals Inc 123 Mallinckrodt PLC 07-04-2014 $5.592,21 24 Nordion Inc 124 Sterigenics International Inc 03-28-2014 $815,07 25 Forest Laboratories Inc 125 Actavis PLC 02-18-2014 $25.439,73 26 Cadence Pharmaceuticals Inc 126 Mallinckrodt PLC 11-02-2014 $1.341,25 27 ArthroCare Corp 127 Smith & Nephew PLC 03-02-2014 $1.739,80 28 Diagnosticos da America SA 128 Cromossomo Participacoes II SA 12-23-2013 $760,82 29 Gentium SpA 129 Jazz Pharmaceuticals PLC 12-19-2013 $860,43 30 Given Imaging Ltd 130 Covidien PLC 08-12-2013 $978,47 31 Atrium Innovations Inc 131 Investor Group 11-29-2013 $717,64 32 Algeta ASA 132 Aviator Acquisition AS 11-26-2013 $2.709,36 33 Patheon Inc 133 DSM Pharmaceutical Products 11-19-2013 $1.394,55

34 ViroPharma Inc 134 Shire PLC 11-11-2013 $4.210,81

35 Santarus Inc 135 Salix Pharmaceuticals Ltd 07-11-2013 $2.677,40 36 Paladin Labs Inc 136 Endo Health Solutions Inc 05-11-2013 $1.561,19 37 Celesio AG 137 Dragonfly GmbH & Co KgaA 10-24-2013 $4.818,33 38 MAKO Surgical Corp 138 Stryker Corp 09-25-2013 $1.483,58 39 Astex Pharmaceuticals Inc 139 Otsuka Holdings Co Ltd 05-09-2013 $886,86 40 Hi-Tech Pharmacal Co Inc 140 Akorn Inc 08-27-2013 $601,99 41 Trius Therapeutics Inc 141 Cubist Pharmaceuticals Inc 07-30-2013 $786,58 42 Optimer Pharmaceuticals Inc 142 Cubist Pharmaceuticals Inc 07-30-2013 $775,50

43 Elan Corp PLC 143 Perrigo Co 07-29-2013 $8.537,99

44 Onyx Pharmaceuticals Inc 144 Amgen Inc 06-30-2013 $9.692,51 45 CML HealthCare Inc 145 LifeLabs Inc 06-25-2013 $1.163,30 46 Warner Chilcott PLC 146 Actavis Inc 10-05-2013 $5.096,08 47 Conceptus Inc 147 Evelyn Acquisition Co 04-29-2013 $1.063,42 48 Life Technologies Corp 148 Thermo Fisher Scientific Inc 04-15-2013 $15.501,39 49 MAP Pharmaceuticals Inc 149 Allergan Inc 01-22-2013 $944,02 50 Trauson Holdings Co Ltd 150 Stryker Corp 01-17-2013 $764,00

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51 GlaxoSmithKline Consumer 151 GlaxoSmithKline Pte Ltd 11-26-2012 $863,74

52 Pronova BioPharma ASA 152 BASF AS 11-21-2012 $728,38

53 Schiff Nutrition Intl Inc 153 Reckitt Benckiser Group PLC 11-15-2012 $1.318,07 54 PSS World Medical Inc 154 McKesson Corp 10-25-2012 $1.459,07 55 China Kanghui Holdings 155 Medtronic Inc 09-28-2012 $801,96 56 Medicis Pharmaceutical Corp 156 Valeant Pharmaceuticals Intl 03-09-2012 $3.073,57 57 Par Pharmaceutical Cos Inc 157 TPG Capital LP 07-16-2012 $1.885,65 58 Amylin Pharmaceuticals Inc 158 Bristol-Myers Squibb Co 06-29-2012 $7.183,42

59 Gen-Probe Inc 159 Hologic Inc 04-30-2012 $3.918,85

60 Ardea Biosciences Inc 160 AstraZeneca PLC 04-23-2012 $1.245,38 61 Human Genome Sciences Inc 161 GlaxoSmithKline PLC 04-19-2012 $2.910,10 62 Guangzhou Baiyunshan Pharm 162 Guangzhou Pharm Co Ltd 03-28-2012 $928,75 63 ZOLL Medical Corp 163 Asahi Kasei Corp 12-03-2012 $2.200,32 64 Micromet Inc 164 Armstrong Acquisition Corp 01-26-2012 $1.146,40 65 Inhibitex Inc 165 Bristol-Myers Squibb Co 07-01-2012 $2.523,87 66 SonoSite Inc 166 Fujifilm Holdings Corp 12-15-2011 $796,16 67 Pharmasset Inc 167 Royal Merger Sub II Inc 11-21-2011 $10.996,33 68 Pharmaceutical Prod Dvlp Inc 168 Pharm Product Dvlp Inc SPV 03-10-2011 $3.870,88 69 Caliper Life Sciences Inc 169 PerkinElmer Inc 08-09-2011 $611,62 70 Omega Pharma NV 170 Couckinvest NV 02-09-2011 $868,38 71 Kinetic Concepts Inc 171 Chiron Holdings Inc 07-13-2011 $5.139,02 72 Immucor Inc 172 IVD Acquisition Corp 05-07-2011 $1.687,50 73 Taisho Pharmaceutical Co Ltd 173 Taisho Pharmaceutical Co Ltd 05-13-2011 $6.382,52 74 Cephalon Inc 174 Teva Pharmaceutical Industries 02-05-2011 $6.310,94 75 Synthes Inc 175 Johnson & Johnson 04-18-2011 $20.097,79 76 American Med Sys Holdings Inc 176 NIKA Merger Sub Inc 11-04-2011 $2.703,52 77 Clinical Data Inc 177 Magnolia Acquisition Corp 02-22-2011 $1.199,75 78 Beckman Coulter Inc 178 Danaher Corp 07-02-2011 $5.782,22 79 Martek Biosciences Corp 179 Greenback Acquisition Corp 12-21-2010 $1.054,64 80 Q-Med AB 180 Galderma Holding AB 12-13-2010 $1.068,49 81 Eurand NV 181 Axcan Pharma Holding BV 01-12-2010 $582,98 82 AGA Medical Holdings Inc 182 Asteroid Subsidiary Corp 10-18-2010 $1.300,22 83 ZymoGenetics Inc 183 Bristol-Myers Squibb Co 07-09-2010 $837,57 84 Genzyme Corp 184 Sanofi-Aventis SA 08-29-2010 $23.898,85 85 SSL International PLC 185 Reckitt Benckiser Group PLC 07-21-2010 $3.812,56 86 NBTY Inc 186 The Carlyle Group LLC 07-15-2010 $3.640,44 87 Abraxis BioScience Inc 187 Celgene Corp 06-30-2010 $3.578,19 88 Valeant Pharmaceuticals Intl 188 Biovail Corp 06-21-2010 $3.717,01 89 Talecris Biotherapeutics Hldg 189 Grifols SA 07-06-2010 $3.559,93

90 ev3 Inc 190 COV Delaware Corp 01-06-2010 $2.692,42

91 Sperian Protection SA 191 Honeywell Holding France SAS 05-19-2010 $1.136,58 92 Facet Biotech Corp 192 Abbott Laboratories 10-03-2010 $718,76 93 OSI Pharmaceuticals Inc 193 Ruby Acquisition Inc 01-03-2010 $4.031,01

94 Millipore Corp 194 Merck KGaA 02-28-2010 $6.126,52

95 Alcon Inc 195 Novartis AG 04-01-2010 $12.144,40

96 Chattem Inc 196 Sanofi-Aventis SA 12-21-2009 $1.780,60 97 FGX International Holdings Ltd 197 Essilor International SA 12-16-2009 $558,26 98 Shanghai Indl Pharm Invest Co 198 Shanghai Pharm Co Ltd 10-15-2009 $1.056,65 99 Varian Inc 199 Agilent Technologies Inc 07-27-2009 $1.511,90

100 Alcon Inc 200 Novartis AG 07-04-2008 $27.733,60

No information available in Datastream Not enough information available for Stata

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Appendix 3: CAR for target firms with an event window of [-2,+2]

Target Id Target name Date

Cumulative Abnormal

Return T-value

1 Auspex Pharmaceuticals Inc 30-mrt-15 42,9753 1,303

2 Hyperion Therapeutics Inc 30-mrt-15 7,6367 1,078

3 Pharmacyclics Inc 04-mrt-15 15,7315 1,484

5 Foundation Medicine Inc 12-jan-15 108,9810 1,171

7 Volcano Corp 17-dec-14 53,7266 0,968

8 Cubist Pharmaceuticals Inc 08-dec-14 29,6321 0,783

9 Avanir Pharmaceuticals Inc 02-dec-14 6,4439 0,527

10 Prosensa Holding BV 24-nov-14 72,5703 1,205

11 Allergan Inc 17-nov-14 7,0712 1,419

12 Durata Therapeutics Inc 06-okt-14 83,8704 1,116

14 Auxilium Pharmaceuticals Inc 16-sep-14 40,3435 0,867

16 Nobel Biocare Holding AG 29-jul-14 15,8059 0,989

18 Idenix Pharmaceuticals Inc 09-jun-14 234,5517 1,029

19 CFR Pharmaceutical SA 16-mei-14 41,3414 0,875

20 Chelsea Therapeutics Intl Ltd 08-mei-14 23,7926 0,723

21 Furiex Pharmaceuticals Inc 28-apr-14 19,7677 0,697

22 Ranbaxy Laboratories Ltd 07-apr-14 17,3962 1,687

23 Questcor Pharmaceuticals Inc 07-apr-14 15,5069 1,244

24 Nordion Inc 28-mrt-14 7,2860 0,693

25 Forest Laboratories Inc 18-feb-14 32,6715 1,273

26 Cadence Pharmaceuticals Inc 11-feb-14 19,8165 0,768

27 ArthroCare Corp 03-feb-14 7,7485 0,838

28 Diagnosticos da America SA 23-dec-13 9,2256 0,829

29 Gentium SpA 19-dec-13 -8,2047 -2,688

31 Atrium Innovations Inc 29-nov-13 25,1161 1,081

32 Algeta ASA 26-nov-13 32,9173 1,098

33 Patheon Inc 19-nov-13 61,4524 1,005

34 ViroPharma Inc 11-nov-13 25,4988 1,020

35 Santarus Inc 07-nov-13 32,6453 0,899

36 Paladin Labs Inc 05-nov-13 51,3587 1,054

37 Celesio AG 24-okt-13 11,2906 1,496

38 MAKO Surgical Corp 25-sep-13 80,0287 0,969

39 Astex Pharmaceuticals Inc 05-sep-13 29,1168 1,401

40 Hi-Tech Pharmacal Co Inc 27-aug-13 24,3270 1,042

41 Trius Therapeutics Inc 30-jul-13 15,2699 0,698

42 Optimer Pharmaceuticals Inc 30-jul-13 3,4245 0,912

43 Elan Corp PLC 29-jul-13 0,6404 0,383

46 Warner Chilcott PLC 10-mei-13 -2,0150 -1,225

47 Conceptus Inc 29-apr-13 18,0377 0,951

48 Life Technologies Corp 15-apr-13 13,5880 1,164

49 MAP Pharmaceuticals Inc 22-jan-13 55,3251 0,939

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51 GlaxoSmithKline Consumer 26-nov-12 20,1693 1,021

52 Pronova BioPharma ASA 21-nov-12 -8,4601 -2,781

53 Schiff Nutrition Intl Inc 15-nov-12 27,5289 0,965

54 PSS World Medical Inc 25-okt-12 31,8992 0,993

55 China Kanghui Holdings 28-sep-12 20,4926 0,884

56 Medicis Pharmaceutical Corp 03-sep-12 36,8926 0,946

57 Par Pharmaceutical Cos Inc 16-jul-12 37,5052 1,016

58 Amylin Pharmaceuticals Inc 29-jun-12 6,7685 0,790

59 Gen-Probe Inc 30-apr-12 17,1649 0,883

60 Ardea Biosciences Inc 23-apr-12 54,0486 1,032

61 Human Genome Sciences Inc 19-apr-12 101,8089 1,042

62 Guangzhou Baiyunshan Pharm 28-mrt-12 -0,5300 -0,037

63 ZOLL Medical Corp 12-mrt-12 18,6399 0,769

64 Micromet Inc 26-jan-12 31,1061 0,950

66 SonoSite Inc 15-dec-11 26,8738 1,024

67 Pharmasset Inc 21-nov-11 88,4174 1,037

68 Pharmaceutical Prod Dvlp Inc 03-okt-11 25,6613 0,873

69 Caliper Life Sciences Inc 08-sep-11 45,9536 1,117

70 Omega Pharma NV 02-sep-11 3,0630 0,626

71 Kinetic Concepts Inc 13-jul-11 5,3538 0,981

72 Immucor Inc 05-jul-11 28,4752 0,924

73 Taisho Pharmaceutical Co Ltd 13-mei-11 -5,0707 -1,829

74 Cephalon Inc 02-mei-11 4,6498 1,142

75 Synthes Inc 18-apr-11 13,5797 1,952

76 American Med Sys Holdings Inc 11-apr-11 33,3600 1,042

77 Clinical Data Inc 22-feb-11 -4,6323 -1,295

78 Beckman Coulter Inc 07-feb-11 10,2425 1,152

79 Martek Biosciences Corp 21-dec-10 38,0356 1,099

80 Q-Med AB 13-dec-10 12,3212 1,042

81 Eurand NV 01-dec-10 -1,8255 -0,283

82 AGA Medical Holdings Inc 18-okt-10 39,5286 0,988

83 ZymoGenetics Inc 07-sep-10 82,5053 0,983

85 SSL International PLC 21-jul-10 30,8847 0,888

86 NBTY Inc 15-jul-10 48,4947 1,144

87 Abraxis BioScience Inc 30-jun-10 19,3498 0,903

88 Valeant Pharmaceuticals Intl 21-jun-10 8,6001 0,792

89 Talecris Biotherapeutics Hldg 07-jun-10 29,4147 1,132

(29)

Appendix 4: CAR for target firms with an event window of [-20,+20]

Target Id Target name Date

Cumulative Abnormal

Return T-value

1 Auspex Pharmaceuticals Inc 30-mrt-15 -7,0031 -0,157

2 Hyperion Therapeutics Inc 30-mrt-15 31,0895 1,707

3 Pharmacyclics Inc 04-mrt-15 26,8461 1,243

5 Foundation Medicine Inc 12-jan-15 109,8740 1,132

7 Volcano Corp 17-dec-14 76,8160 1,371

8 Cubist Pharmaceuticals Inc 08-dec-14 38,2981 1,039

9 Avanir Pharmaceuticals Inc 02-dec-14 -28,1723 -1,860

10 Prosensa Holding BV 24-nov-14 53,4856 0,811

11 Allergan Inc 17-nov-14 7,5901 0,997

12 Durata Therapeutics Inc 06-okt-14 76,6501 0,978

14 Auxilium Pharmaceuticals Inc 16-sep-14 93,9095 1,971

16 Nobel Biocare Holding AG 29-jul-14 27,8081 1,497

18 Idenix Pharmaceuticals Inc 09-jun-14 271,9937 1,189

19 CFR Pharmaceutical SA 16-mei-14 50,5658 1,085

20 Chelsea Therapeutics Intl Ltd 08-mei-14 -20,1716 -0,561

21 Furiex Pharmaceuticals Inc 28-apr-14 -39,6661 -1,276

22 Ranbaxy Laboratories Ltd 07-apr-14 31,7452 1,881

23 Questcor Pharmaceuticals Inc 07-apr-14 20,7732 0,936

24 Nordion Inc 28-mrt-14 5,3738 0,435

25 Forest Laboratories Inc 18-feb-14 14,6496 0,508

26 Cadence Pharmaceuticals Inc 11-feb-14 -13,1227 -0,456

27 ArthroCare Corp 03-feb-14 14,4182 0,803

28 Diagnosticos da America SA 23-dec-13 17,4447 1,186

29 Gentium SpA 19-dec-13 -45,0767 -2,574

31 Atrium Innovations Inc 29-nov-13 12,2238 0,485

32 Algeta ASA 26-nov-13 53,8474 1,625

33 Patheon Inc 19-nov-13 55,9213 0,898

34 ViroPharma Inc 11-nov-13 5,8251 0,218

35 Santarus Inc 07-nov-13 34,9737 0,958

36 Paladin Labs Inc 05-nov-13 58,7885 1,184

37 Celesio AG 24-okt-13 29,7637 1,283

38 MAKO Surgical Corp 25-sep-13 69,8126 0,841

39 Astex Pharmaceuticals Inc 05-sep-13 78,8809 2,231

40 Hi-Tech Pharmacal Co Inc 27-aug-13 19,5973 0,813

41 Trius Therapeutics Inc 30-jul-13 38,2855 1,490

42 Optimer Pharmaceuticals Inc 30-jul-13 -6,9424 -0,843

43 Elan Corp PLC 29-jul-13 42,6217 0,815

46 Warner Chilcott PLC 10-mei-13 17,6252 0,880

47 Conceptus Inc 29-apr-13 18,8655 0,944

48 Life Technologies Corp 15-apr-13 3,8295 0,281

49 MAP Pharmaceuticals Inc 22-jan-13 41,0415 0,694

(30)

51 GlaxoSmithKline Consumer 26-nov-12 14,5946 0,708

52 Pronova BioPharma ASA 21-nov-12 -15,7116 -1,110

53 Schiff Nutrition Intl Inc 15-nov-12 52,5063 0,970

54 PSS World Medical Inc 25-okt-12 21,1800 0,648

55 China Kanghui Holdings 28-sep-12 8,1136 0,319

56 Medicis Pharmaceutical Corp 03-sep-12 35,0326 0,895

57 Par Pharmaceutical Cos Inc 16-jul-12 45,2779 1,211

58 Amylin Pharmaceuticals Inc 29-jun-12 -13,6450 -1,343

59 Gen-Probe Inc 30-apr-12 25,4340 1,319

60 Ardea Biosciences Inc 23-apr-12 48,6958 0,910

61 Human Genome Sciences Inc 19-apr-12 105,4466 1,066

62 Guangzhou Baiyunshan Pharm 28-mrt-12 0,3200 0,022

63 ZOLL Medical Corp 12-mrt-12 -8,3325 -0,333

64 Micromet Inc 26-jan-12 13,6563 0,395

66 SonoSite Inc 15-dec-11 6,4394 0,231

67 Pharmasset Inc 21-nov-11 62,3073 0,699

68 Pharmaceutical Prod Dvlp Inc 03-okt-11 -9,1934 -0,285

69 Caliper Life Sciences Inc 08-sep-11 39,2935 0,885

70 Omega Pharma NV 02-sep-11 17,9106 1,426

71 Kinetic Concepts Inc 13-jul-11 16,2407 1,079

72 Immucor Inc 05-jul-11 34,5949 1,118

73 Taisho Pharmaceutical Co Ltd 13-mei-11 4,7471 0,603

74 Cephalon Inc 02-mei-11 -1,1643 -0,168

75 Synthes Inc 18-apr-11 24,0316 2,676

76 American Med Sys Holdings Inc 11-apr-11 34,3459 1,054

77 Clinical Data Inc 22-feb-11 6,4854 0,254

78 Beckman Coulter Inc 07-feb-11 -11,6809 -1,037

79 Martek Biosciences Corp 21-dec-10 35,4570 0,935

80 Q-Med AB 13-dec-10 30,4354 1,551

81 Eurand NV 01-dec-10 0,1812 0,014

82 AGA Medical Holdings Inc 18-okt-10 34,0322 0,842

83 ZymoGenetics Inc 07-sep-10 111,2196 1,325

85 SSL International PLC 21-jul-10 31,1205 0,892

86 NBTY Inc 15-jul-10 61,2533 1,394

87 Abraxis BioScience Inc 30-jun-10 17,2552 0,731

88 Valeant Pharmaceuticals Intl 21-jun-10 6,3387 0,445

89 Talecris Biotherapeutics Hldg 07-jun-10 39,4756 1,427

The effect on the share price after a merger or acquisition of pharmaceutical companies around the announcement date