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Amsterdam Business School
MSc Finance – Track: Corporate Finance
Master Thesis
The Impact of CEO Stock Options
on Merger & Acquisitions
Abstract
This thesis studies the relationship between a CEO’s stock option holdings and corporate acquisitions. This is the first study to my knowledge that studies both vested and unvested stock option holdings in a mergers and acquisitions setting. The focus is contained to the market reaction and the choice of financing. The research is conducted using a sample of 2,549 domestic acquisitions between 1992 and 2016. By using OLS regressions, the results show that the values of a CEO’s unvested stock option holdings are positively related to the market reaction of an M&A. No such relationship exists with vested stock options. Using Logit regressions, I find no relationship between a CEO’s stock option holdings and the choice of financing. The results shed light on the importance of equity-based compensation for value-creating M&As, and the inclusion of both vested and unvested stock options when studying the stock option holdings.
Written by: Ishan Prabhakran (10826335)
Submitted in: July, 2018
Thesis Supervisor: Dr. Stefan R. Arping
1 Statement of Originality
This document is written by Ishan Prabhakaran who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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Table of Contents
1. Introduction ...………...3
2. Literature Review ……….5
2.1 Mergers & Acquisitions ...………5
2.1.1 Market Reaction ………6
2.1.2 Choice of Financing ………..6
2.2 Executive Compensation ………..8
2.2.1 Agency Theory ………..8
2.2.2 Equity Based Compensation ………..9
2.2.3 Information Content of Stock Options ………..10
2.2.4 CEO Confidence ………....11
2.3 Summary & Hypotheses ………...11
3. Methodology ..………13 3.1 Dependent Variables ……….13 3.1.1 Abnormal Returns ………...13 3.1.2 Choice of Financing ………...14 3.2 Independent Variables ………...15 3.2.1 Confidence ………..15 3.2.2 Unvestedness ………..15 3.3 Control Variables ………..16 3.3.1 Corporate Governance ………16 3.3.2 Deal Characteristics ………17 3.3.3 Firm Characteristics ………...18 3.4 Empirical Models ………..19 3.4.1 Abnormal Returns ………..19 2.4.2 Choice of Financing ………...21
4. Data & Summary Statistics ………..22
4.1 Sample Collection ………...22 4.2 Summary Statistics ………..24 5. Results ………....27 5.1 Abnormal Returns ………...27 5.2 Choice of Financing ………30 6. Robustness Analyses ……….32
6.1 Different Event Windows ……….33
6.2 Relative Deal Size ……….33
6.3 Different Specifications ……….34
7. Conclusion & Discussion ………..35
Bibliography ………..38
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1. Introduction
This thesis studies how certain aspects (market reaction and choice of financing) of an acquisition can be predicted by the value of stock options the CEO holds in the company. Mergers and acquisitions (M&A hereafter) are considered to be major investment decisions for firms, which can be undertaken for several reasons. The decision to acquire is finally taken by the CEO. This decision may not be in the best interest of the shareholders and the long-term value of the firm. Often, this problem is a result of the separation of ownership (shareholders) and control (CEO). Therefore it is crucial to align the incentives of both stakeholders. This can be done by designing an effective compensation package. It is well documented that increasing the equity-based compensation (EBC) offered to executives aligns their interests with shareholders, in turn leading to better acquisitions (I use M&A and acquisition interchangeably) (Bebchuk and Fried, 2003; Datta et al., 2001; Kang et al., 2010). Often the EBC components of a compensation package are complicated and require several conditions to be met before the amounts can be realised. This raises the question as to how exactly do different components of EBC predict a CEOs acquisition behaviour.
The value of global M&A deals has been increasing in the 21st century, peaking in 2015 with a total value of around 5.8 trillion U.S. dollars (Statista, 2018). In 2016, of the US$3.24 trillion spent on M&As, the United States accounted for US$1.46 trillion, making it the largest market for M&As (Statista, 2017). These transactions are of great economic significance in the global economy. M&As can create wealth for shareholders through synergies, improved efficiency and reduced costs. These are a few of the many economic rationales. Despite the benefits of M&As, previous studies have documented negative stock market reactions to the acquirer’s stock on the announcement of an M&A (Moeller et al., 2004, 2005), as well as negative impacts on long-term performance (Agarwal et al., 1992; Asquith, 1983). Studies have also documented that the market reaction is influenced by the choice of financing and the characteristics of the target (Faccio and Masulis, 2005; King et al., 2004). Cash financing is used when the acquirer’s stock is undervalued, while stock financing is used when it is overvalued (Travlos, 1987). Therefore the market may assume undervaluation in the case of cash financing. The significant impact on shareholder wealth makes M&As a compelling field of research.
Companies often experience a separation of ownership (the shareholders) and control (the CEO). The CEO of a company ultimately takes the decision to acquire. Therefore, the
4 motives behind an M&A may not always be aligned with shareholders’ interests. This
conflict of interest is a version of the principal-agent problem. The most applicable solution to this particular principal-agent problem is the use of a well-designed compensation package for the CEO. Executive compensation is a crucial part of corporate governance and a widely discussed matter. Previous research aims to assess how compensation packages can be designed to align the interests of executives with shareholders’, while sustaining the long-term growth of a firm.
According to an article published in CNBC, in 2016, CEO compensation was 271 times more than the average worker, as compared to 59 times in 1987, with a peak of 376 times in 2000 (Cox, 2017). This drastic change in compensation is due to an increase in EBC without any decreases in cash compensation (Bebchuck and Fried, 2003). Studies have shown that executive compensation has a crucial role to play in the acquisition behaviour of CEOs. In particular the EBC aligns the wealth of shareholders with executives, leading to higher abnormal returns around the announcement date of an acquisition (Datta et al., 2001; Kang et al., 2015).
EBC comes in multiple forms of share and option holdings. Stock options often come with specific vesting conditions. Once the stock options have vested (become exercisable), the executive has the choice to exchange them for cash (cash out), or hold on to them. Logically, the decision to cash out vested options would rely on the CEO’s expectations of future performance of the firm. Negative expectations would lead to cashing out and positive expectations would cause the executive to hold on to the vested stock options. Such a
relationship has been documented by Dezső and Ross (2012). In regards to unvested stock options, Datta et al. (2001) finds a positive impact of the previous year’s stock option grant on M&A performance. The use of cash financing can signal undervaluation of the acquirer, which leads to a better market reaction on announcement of an acquisition (Faccio and Masulis, 2005; Travlos, 1987). Therefore this thesis aims to extend this area of research with the following research question:
Can the market reaction and financing choice of M&A deals be predicted by vested and unvested stock option holdings of the CEO?
This thesis carries out an event study methodology along with ordinary least squares (OLS) and Logit regressions. I use an unbalanced panel dataset of domestic acquisitions in the United States of America - from 1992 to 2016, which consists of M&A deals, CEO
5 compensation, firm financials and stock prices. In doing so, this thesis contributes to the existing literature on acquiring shareholder returns due to mergers and acquisitions, the importance executive compensation on shareholder wealth, and the choice of financing.
The remainder of this thesis is structured as follows: Section 2 outlines the related existing literature. Section 3 describes the data required and methodology used. Section 4 presents the data, data sources and descriptive statistics. Section 5 exhibits the main results and section 6 demonstrates the robustness of the analyses. Finally section 7 contains the concluding remarks, limitations and directions for future research.
2. Literature Review
This section outlines the literature surrounding the main areas of research to which this thesis aims to contribute. I cover the relevant literature on mergers and acquisitions, and executive compensation. Under mergers and acquisitions, the existing literature on market reaction to announcements and choice of financing will be discussed. As for executive compensation, the focus will be on how the use of EBC impacts firm value, particularly through acquisitions. From the results of the existing literature, hypotheses will be drawn, thus concluding the contribution this thesis will make.
2.1. Mergers & Acquisitions
The academic research conducted in the field of M&As has seen a progression in
understanding the reasoning for these transactions. The most common justification is the presence of synergies, which will allow the merged company to create more value than if they were just separate entities (King et al., 2004). On the other hand, M&As can be undertaken for managerial self-interest, which can be value destroying (Haleblian et al., 2009). Other factors such as the industrial environment and firm-specific characteristics also influence M&A activity. The literature review by Haleblian et al. (2009) outlines the
progression from understanding the importance of M&As to determining whether M&As impact firm performance and shareholder value. Previous studies find an overall increase in shareholder value for the combined firms. This often results in a transfer of wealth from the acquirer to the target (Datta et al., 1992). Research has shown that on announcement of an M&A, target shareholders tend to observe positive stock market reactions, while acquirers tend to experience negative stock market reactions (Houston et al., 2001). M&As are
6 important investment decisions often-involving large amounts of money and wealth transfers. Therefore it has a significant impact on shareholder value. This led to the expansion of the existing research into determining why firms acquire despite the lack of positive outcomes.
2.1.1. Market Reaction
Although there is potential value creation from engaging in an M&A deal, previous studies have documented negative stock market reactions to the acquirer’s stock on the
announcement of an M&A (Moeller et al., 2004, 2005; Hackbarth & Morellec, 2008). Using a sample of roughly 12000 M&As, Moeller et al. (2004) find that on announcement,
acquirers observe a 1.10% increase in stock price when using equal weights. When they use value-weighted returns, acquirers experience a negative return of -1.18%. They propose that the reason behind this difference is that the returns depend on the size of the firm. Their findings show that this is indeed the case, as large firms tend to pay higher premiums when acquiring. They further support the evidence by showing that it is robust in the choice of financing the deal, as well as in the choice of target i.e. if the target is a public or private firm. Other studies show that M&A performance can be associated with deal financing and choice of target (Faccio and Masulis, 2005; Faccio et al. 2006).
Moeller et al. (2005) use an identical sample to compare the merger wave of the 1980s with the 1990s. Despite having spent just 6 times more in the 1990s as compared to the 1980s, they find that acquirers experienced a total combined loss of US$ 216 billion between 1991 and 2001, while they lost just US$ 4 billion between 1980 and 1990. The majority of the losses in the 1990s are concentrated in the years of 1998 to 2001. They therefore focus on these large loss deals (greater than $1 billion) to assess why this can occur. Consistent with previous literature, they find that high valuation ratios (such as book-to-market and Tobin’s q) do indeed predict value-destroying deals. They argue that when firms have such high ratios, overvaluation gives executives more power over such decisions. When an acquisition is not a good deal, but just due to the ability of a firm to acquire, the market is able to detect this overvaluation and this can result in large-loss deals.
2.1.2. Choice of Financing
Once an acquirer has chosen a target, they must consider the how they will finance the
acquisition. This can be done through the use of cash or an issuance of stock or a combination of multiple instruments. The acquirer may be restricted in their choice for different reasons. Most previous literature find that on average, the use of only cash to finance an acquisition is
7 received more positively by the market than when the financing involves an issuance of stock (Travlos, 1987; Amihud et al, 1990; Faccio and Masulis, 2005).
Due to the problem of asymmetric information, the financing decision can send a signal to the market, and thus influencing the market’s reaction to the announcement of an M&A (Travlos, 1987). The signaling hypothesis follows the assumption that executives who make the financing decision have more information than the market. This information may be about the true value of the firm or the potential outcomes of the M&A or both. CEOs that believe the true value of the firm is below the market value will restrict the issuance of stock because it will not raise as much funds as it would at the true value. In such a case, cash financing is preferred. Therefore when an acquirer announces an M&A financed by cash, the market may assume this is due to undervaluation. This positive signal can cause higher abnormal returns. Within this reasoning, when an acquirer decides to issue stock, it sends a signal of overvaluation. Using a relatively small sample of 167 acquisitions, the findings of Travlos (1987) support the signaling hypothesis. He finds that the use of stock financing results in significant losses to the acquiring shareholders, while returns are expected to be more normal with the use of cash. The findings appear to be robust over whether the deal was a merger or a tender offer and whether or not the deal was successful.
Other studies have hypothesised and found that the level of managerial ownership impacts the choice of financing (Amihud et al., 1990; Martin 1996). Amihud et al (1990) hypothesize that executives, who have a significant amount of ownership, would rather use cash or debt to acquire the equity of another company. This would retain and increase their control over the firm through voting power. If they were to use stock financing, their ownership stake would be diluted by giving voting rights to either blockholders or passive investors. This could threaten their control over the combined firm. By aggregating the ownership stakes of the top 2, top 5, and all directors and officers, they find that there is a positive relationship between managerial ownership and the preference for cash financing of an acquisition. This is important to this study as the granting of stock options to CEOs, can be considered as a grant of ownership.
The analysis of Amihud et al. (1990) suffers from major endogeneity issues. Martin (1996) augments the analysis by controlling for various other firm and economic environment characteristics. Using a much larger sample (of 846 corporate acquisitions) than Travlos (1987) and Amihud et al. (1990), he finds that the relationship of managerial ownership and the choice of financing is non-linear only holding for medium amounts of ownership. He also finds that the economic environment (in terms of investment opportunities) of the acquirer
8 significantly impacts the likelihood of stock financing. Using the measure of Tobin’s Q, the findings indicate that the probability of using stock financing is 2.7 times higher for a firm with a Tobin’s Q of 2 as compared to a firm with a Tobin’s Q of 1.1
One of the most comprehensive studies in terms of financing an M&A, is conducted by Faccio and Masulis. (2005). Most studies in the field use domestic M&As in the U.S. Instead, they focus on M&As in 13 European countries between 1997 and 2000 with a final sample of 3,667 acquisitions by 1,349 acquirers. The use of multiple countries allows for the testing of a wide range of corporate governance structures. They also find a non-linear relationship between ownership and the choice of cash financing, which are consistent with Martin (1996). In addition to this, they find several other determinants. In terms of firm characteristics, they find the financial leverage of a firm to be consistently significant. As for the deal characteristics, they find the relative deal size is a major determinant. In terms of corporate governance, they find that when an executive that is also a part of a bank’s board of directors, there is higher likelihood of cash financing.
2.2. Executive Compensation
2.2.1. Agency Theory
Firms commonly experience a version of the principal-agent problem when hiring executives, i.e. the divide between ownership (i.e. shareholders) and control (i.e. executives). This is formulated under the agency theory. Under the assumption that both executives and
shareholders are value-maximizing parties, it can be justified that executives do not always act in the best interest of the firm and shareholders (Jensen and Meckling, 1976). The agency theory is of significant importance in M&As. Executives may have alternative motives that would benefit them personally, at the expense of destroying firm value. Jensen (1986) studies the agency theory in the corporate finance field, establishing a relationship between cash flows and takeovers. In the case of M&As, cash flow is often where the principal-agent problem begins. Shareholders expect distribution of dividends in cases of high cash flows, which in turn would lead to fewer funds under the control of executives. Executives may engage in M&As in order to utilise high cash flows and to justify not paying out dividends. M&As are associated with growth as the combined firm will have more assets, which are likely to generate higher sales and cash flows. According to Murphy (1985), this growth leads
1 Tobin’s Q is a measure of investment opportunities. It is measured by the market value of the firm scaled to
9 to an increase in executive compensation. Therefore managers may only engage in M&As to gain personal benefits sometimes at the cost of shareholder value. This raises concerns for shareholders. One way to reduce the principal-agent problem in this case is through equity-based compensation (EBC).
2.2.2. Equity Based Compensation
Bebchuk and Fried (2003) consider the different approaches of using executive compensation as a solution to the principal-agent problem. First, there is the “optimal contracting
approach”, where supervisory boards (or compensation committees) construct a compensation package that motivates executives to make decisions that maximise
shareholder value. Under this approach, an effective way to align the interest of executives and shareholders is through EBC. By carefully using EBC, the executive’s wealth can be closely tied to shareholder wealth. Next, there is the “managerial power approach”, which argues that executive compensation may also amplify the principal-agent problem. This can be the case when executives have a say in designing their compensation packages, which allows them to extract rents for their services, rather than align their interests with that of shareholders. Although there has been a drastic increase in EBC since the beginning of the 1990s, it may not always lead to the desired outcome of aligned interests. The grant of stock options to executives allows them to benefit from market and industry trends, even if the firm’s performance worsens; it also protects them from shocks that lead to large decreases as they are not obliged to exercise these options.
Overtime, executive compensation has been linked more and more to stock-prices using stocks and stock options. Since managers’ wealth is more likely to be affected by stock-prices, they are more likely to make investment decisions that increase shareholder wealth (Moeller et al., 2005). EBC has become more important in the 21st century. Federal laws such as Sarbanes Oxley Act (SOX hereafter) and the Dodd-Frank Act have sought to improve shareholder protection through better transparency. This has in turn affected corporate
governance and executive compensation. Chen et al. (2015) show that after the
implementation of the SOX in 2002, pay-for-performance sensitivity (i.e. EBC) significantly increased using both accounting-based and market-based measures. Kang et al. (2010) investigate if SOX had a significant impact on the investment decisions of firms. They find that firms’ managers significantly increased the discount rate at which they value other firms and therefore were more cautious about investment. The Dodd-Frank Act has mandated increased disclosure of executive compensation and increased shareholder power by adopting
10 say-on-pay laws (Bainbridge, 2012). Therefore, shareholders are currently better informed about executive compensation than earlier.
Datta et al. (2001) study how the EBC of the top five executives affects acquisition performance. The authors focus on the stock options granted in the year prior to an
acquisition. By studying 1,719 M&As in the U.S. from 1993 to 1998, they find a positive relationship between EBC and the stock returns to shareholders. They study this particular period as there was a great increase in stock option grants to executives. They find that executives with more EBC, make better acquisition decisions with higher growth, and also pay significantly less bid premiums. Their research is a good example of the “optimal contracting” approach with respect to M&As.
2.2.3. Information Content of Stock Options
The increase in EBC levels alongside improved transparency makes the structure of EBC more important. When managers are granted stock options, they come with certain conditions and a vesting schedule (i.e. when they are allowed to cash out these options). If the options are in-the-money, the executive will profit from selling them. At the same time, the executive has the choice to hold on to the stock options up until they expire, which can lead to higher profits if the firm performs well. Dezső and Ross (2012) acknowledge that executives may have private information about the future performance of the firm, which can influence the timing of exercising stock options. The decision to sell or hold onto vested in-the-money stock options can send a signal about the firm’s future performance. Using data from 2,515 firms over the time period of 1992 to 2010, they find that managers holding onto stock options predict better firm performance. This is measured through greater cash flows and better credit quality.
Huddart and Lang (2003) use a unique dataset of 50,000 employees across seven firms, to determine if the choice to exercise stock options can predict the future performance of a firm. They find that private information is very much spread across employees at
different levels in the corporate hierarchy. Employees use private information to time their exercises such that there is a 10% higher return at times when aggregate stock option exercises are low as compared to when they are high. The results suggest that the private information takes around six months to be incorporated into the prices, which raises the concern for shareholders that should also be informed. This can be done by diligent reporting of aggregate stock exercise decisions by employees on all hierarchical levels.
11 Several previous studies document a positive relationship between stock option
holdings by executives and the likelihood of upward price movements of the company’s stock. This can be the outcome of options being granted just before positive announcements (Yermack, 1997), earnings management/manipulations (Efendi et al., 2007; Bergstresser & Philippon, 2006; Bartov & Mohanram, 2004) or investment decisions (Datta et al., 2001).
2.2.4. CEO Confidence
In a series of studies conducted by Malmendier and Tate (2005; 2008), measures of CEO confidence are developed using their choice to hold vested stock options. The measure is based on: 1) whether the CEO has held stock options up until expiration at least once in their tenure; 2) whether the CEO has held stock options that were more than 67% in-the-money at least twice in their tenure. In their study of 2005, they use a sample of CEOs from 477 large public companies in the U.S. during the time period of 1980 and 1994. The research identifies how CEOs that hold above average amounts of in-the-money stock options seem to be
subject to the “better-than-average” effect. This causes them to consistently miscalculate the benefits of investments. The reasoning follows the false illusion of control over investments. CEOs tend to be overly focused on good outcomes using arbitrary reference points. The findings show that firms with overconfident CEOs do not perform significantly better than the S&P 500 average. This is contradictory to the findings of previous studies, which hypothesize that retaining stock options is due to insider information of positive future outcomes (Dezső and Ross, 2012; Huddart and Lang, 2003).
Malmendier and Tate (2008) further their research by linking overconfidence to merger decisions. It would be expected that a risk averse CEO would exercise in-the-money stock options in order to reduce the company specific risk. Using a similar sample to their previous study, they find that CEOs that are overconfident and retain their stock options, end up engaging in significantly more mergers. The findings indicate that the market reacts more negatively (78 basis points lower) to acquisitions conducted by overconfident CEOs.
This section of behavioural finance literature contradicts previous findings of insider information with evidence suggesting that exercise decisions may represent a character trait that negatively impacts investment decisions.
2.3. Summary & Hypotheses
The existing literature has brought to light that acquirers generally experience negligible or negative abnormal returns around the announcement date. Despite the short-term loss to
12 shareholders, there is still a large market for mergers and acquisitions. The decision to engage in an acquisition is ultimately taken by the CEO. Due to the principal-agent problem, CEOs may not always act in the best interest of shareholders. Compensation packages can be used to align the interest of CEOs and shareholders. Given that the CEO is rational, we can expect his/her decision to (at least partly) rely on how their wealth will be affected by the
acquisition. The extent to which their wealth is affected is determined by the equity-based component of a compensation package. Therefore we can expect higher stock option holdings to result in acquisitions that yield higher announcement returns. Stock option holdings are split into vested stock options (exercisable) and unvested stock options (non-exercisable).
The choice to hold (not exercise) vested stock options may be signal that the CEO is confident, or has some insider information about the future performance of the firm and thus the acquisition. To test the confidence/information content of vested stock option holdings on acquisition performance, the first hypothesis is formulated:
Hypothesis 1: The amount of vested stock options that a CEO chooses to hold is positively related to the announcement returns for acquiring shareholders.
A CEO’s unvested stock option holdings are not by choice, but rather a result of the design of the compensation package. Since stock options will be exercisable in the future, it can influence a CEO to take decisions that are good for the long-term performance of the firm, which is beneficial for shareholders as well. Therefore to test the effectiveness of equity-based compensation on acquisition performance, the second hypothesis is formulated:
Hypothesis 2: The amount of unvested stock options that a CEO holds is positively related to the announcement returns to acquiring shareholders.
The two most basic ways of financing an acquisition is through cash or through the issuance of equity or a combination of both (and other instruments). Assuming a CEO has more information than the market, he/she is unlikely to issue stock if the firm is undervalued by the market. Previous literature has documented that acquisitions financed solely by cash generate higher returns, possibly due to the signaling of undervaluation. It has also been documented that CEOs tend to choose cash financing when they have concerns about losing control of the firm through shareholder votes; when a CEO has higher stock option holdings, they are entitled to a higher level of ownership once they exercise these option. In line with
13 these findings, financing a deal with only cash is a more attractive option. Therefore to test whether CEO’s stock option holdings impact the choice of financing, the third and fourth hypotheses are formulated as follows:
Hypothesis 3: The more vested stock options a CEO chooses to hold, the more likely they are to use cash financing.
Hypothesis 4: The more unvested stock options a CEO holds, the more likely they are to use cash financing.
Researching the stated hypothesis will allow this thesis to contribute to the literature on: factors affecting announcement returns; the effectiveness of equity-based compensation; CEO behavior; and the determinants of the financing choice of an acquisition;.
3. Methodology
This section discusses the procedures carried out in order to assess the relationship between CEO stock options and acquisition decisions made by the respective CEOs. The methodology is split into the following sections: 3.1. Dependent variables, 3.2. Independent Variables, 3.3. Control Variables, 3.4. Econometric Models
3.1. Dependent Variables
The dependent variables discussed in this section will relate to the M&As that firms engage in, from the acquirer’s point of view. The two major aspects that will be discussed are: the abnormal returns experienced around the announcement date and the choice of financing.
3.1.1. Abnormal Returns
I use an event-study methodology to calculate the cumulative abnormal returns (CARs) to an acquiring firm. The value creation of the acquisitions is assessed through the abnormal returns that are generated around the date of announcement. Abnormal returns are defined as the returns generated above the expected return of a particular stock, given its normal
relationship with the market. The normal relationship with the market will be determined using the market model:
14 𝐸𝐸[𝑅𝑅𝑖𝑖𝑖𝑖] = 𝛼𝛼𝑖𝑖 + 𝛽𝛽𝑖𝑖∗ 𝑅𝑅𝑅𝑅𝑖𝑖
Previous studies analysing the relationship between M&As and executive compensation have also used the market model (Lewellen et al. 1985; Yermack 1997; Datta et al. 2001;
Hackbarth and Morellec, 2008). Where 𝐸𝐸[𝑅𝑅𝑖𝑖𝑖𝑖] is the normal return, 𝛼𝛼𝑖𝑖 and 𝛽𝛽𝑖𝑖 are individual parameters that determine the relationship of each firm i’s stock with the market return 𝑅𝑅𝑅𝑅 at time t. The market return is determined using the daily value-weighted return of the stock market on which firm i’s stock is listed. In line with Datta et al. (2001), I estimate these individual parameters using the daily stock returns of a particular acquiring firm from 200 days (t - 200) before, up until 60 days before (t - 60) the announcement of an M&A (t). This prevents the CARs from accounting for any information leakage. Once the parameters are determined, the daily abnormal returns 𝐴𝐴𝑅𝑅𝑖𝑖𝑖𝑖are calculated by observing the difference between the actual return on a particular day (t) for a particular firm (i):
𝐴𝐴𝑅𝑅𝑖𝑖𝑖𝑖 = 𝑅𝑅𝑖𝑖𝑖𝑖− 𝐸𝐸[𝑅𝑅𝑖𝑖𝑖𝑖]
𝐶𝐶𝐴𝐴𝑅𝑅𝑖𝑖(𝑖𝑖1,𝑖𝑖2)= � 𝐴𝐴𝑅𝑅𝑖𝑖 𝑖𝑖2 𝑖𝑖1
For each acquisition announcement the abnormal returns are cumulated around multiple event windows (3, 5 and 21 days surrounding the announcement). The three-day event window is used in the primary analysis. The five-day and twenty-one-day event window is used in the robustness analysis
Previous studies have documented that abnormal returns can be experienced for prolonged periods of time and not just around the announcement window. To minimise the possibility of the CARs being affected by a previous deal, I exclude completed deals that were announced within a year of each other, by the same acquirer.
3.1.2. Choice of Financing
To analyse the relationship between CEO stock options and the choice of financing of an acquisition, logit regression models will be used. Therefore the dependent variable generated will be binary. Cash is equal to 1 when the acquisition was entirely financed by cash (i.e. 100%) and 0 otherwise.
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3.2. Independent Variables
The independent variables constructed in this section aim to measure the extent to which a CEO is entitled to stock options in the company he/she works. This is split into the amount the CEO chooses to hold (i.e. the Confidence) and the amount that the CEO is entitled to in the future (i.e. the Unvestedness).
3.2.1. Confidence
The measure of confidence aims to assess whether the CEO has a positive outlook on the future performance of the firm. This will be estimated using the value of stock options held by the CEO that are vested (exercisable) but have not been exercised. The value of each stock option is estimated by the difference between the exercise price and the year-end closing price of the company’s primary equity issue. This is then multiplied by the total number of vested stock options held by the CEO to give the total value of unexercised stock options in a given year. It represents confidence because it is a choice made by the CEO to hold on to them, not an obligation. This variable will explain whether the CEO chooses specific kinds of acquisitions when they are confident about the future performance of their firm. In line with Dezső & Ross (2012), the total value of these stock options will be scaled to the total annual compensation in that year.2 This is done because the compensation of a CEO is highly correlated with the size of a firm. By scaling the stock options to total compensation, the correlations between the explanatory variables are reduced. This increases the strength of the econometric model by reducing endogeneity concerns.
3.2.2. Unvestedness
The options that are granted to the CEO come with a vesting schedule. Therefore almost every year there is a significant amount of options that remain unvested. This means that the CEO is only entitled to them in the future. The unvested stock options differ from vested stock options because the CEO does not choose to hold these options. Rather they are a part of the compensation package that intends to align the interests of executives with the
performance of the firm. The calculation of the value of unvested options is the same as that
2 Total annual compensation is defined as the salary + bonus + restricted stock grants + long term incentive plan
16 for the vested options (as in Confidence). This variable will explain whether the unvested stock option holdings of a CEO impact their acquisition choices.
3.3. Control Variables
This section contains a detailed list of all the variables that are used to control for the other sources of variation in the respective dependent variables. The relevance will be explained using the findings of previous literature. In doing so, I will hypothesize what outcomes can be expected by including them in the empirical models. The empirical models will be discussed in Section 3.4.
Control variables are included to reduce the omitted variable bias in the regression models. This is necessary to reduce the endogeneity concerns (Stock & Watson, 2011). The outcomes of M&As can be influenced by public as well as non-public information (Roberts & Whited, 2012). It should also be noted that this study is purely based on public
information. Therefore this study cannot completely control for omitted variable bias due to certain important variables being unobservable.
Most of the previous research around these control variables is based on samples before the 21st century. Given the drastic changes in the economic environment, this thesis will also shed light on the consistency and current relevance of these findings.
3.3.1. Corporate Governance
- Managerial Power (Director and Compensation Com.)
Some recent research has focused on how managerial power can influence their
compensation packages and their investment decisions (Grinstein and Hribar, 2003; Harford and Li, 2007). Grinstein and Hribar (2003) find that M&A decisions that are taken by CEOs with high levels of managerial power tend to show lower much lower abnormal returns around the announcement date. They measure the managerial power by whether the CEO was a part of the nominating committee or served as a director in the given fiscal year. I therefore use two control variables: Director and Compensation Com. to control for managerial power.
Director is a dummy variable that is equal to 1 if the CEO also served as a director in the
fiscal year, and is equal to 0 if this was not the case. Compensation Com. is a dummy variable that is equal to 1 if the CEO is listed in the Compensation Committee Interlocks section of the proxy, and is equal to 0 if this was not the case. As outlined by Bebchuk and Fried (2003), this weakens the effectiveness of optimal contracting and adds to managerial power. When
17 either or both of these are equal to 1, we can expect the CEO to have more managerial power, and therefore I expect the coefficient to be negative for abnormal returns.
Faccio and Masulis, (2005) finds that when a CEO is on the board of directors of bank, it is likely that he may have higher accessibility to debt. This makes it easier for the acquirer to obtain cash in order to finance a deal. Therefore in analysing the choice of financing, I expect the coefficient of Director to be positive.
- Executive Ownership
I use Executive Ownership to control for the amount of equity that is owned by all the listed executives on the Execucomp database for a given acquirer. The literature review covers multiple papers that observe a positive relationship between executive ownership and the use of cash financing (Amihud et al., 1990; Martin, 1996). This is mainly due to
managerial control concerns, as issuing equity would deter the control executives have over the firm. I expect a positive coefficient for this variable in analysing the choice of financing.
3.3.2. Deal Characteristics
- Deal Size (Relative Size)Previous studies that use cumulative abnormal returns as the dependent variable control for the size of the deal (Hackbarth and Morellec, 2008; Moeller et al., 2004). I control for this using Relative Size, which is the total amount paid to the target for the acquisition scaled to the market value of the target. The outcome for is expected to be positive for abnormal returns.
Faccio and Masulis (2005) find an extremely large difference in between the value of cash-financed deals and stock-financed deals. They find that stock-financed deals are 17 times larger on average. Therefore I expect a negative coefficient for Relative Size in analysing the choice of financing.
- Target Type (Public)
The literature that was reviewed seems to consistently find positive returns for privately listed targets but negative or insignificant returns for a public target (Faccio et al., 2006; Capron and Shen, 2007). Thus I control for this with a dummy variables. Public is equal to 1 if the chosen target is a publicly listed company and is equal to 0 is the target is private. The coefficient of Public is expected to be negative for abnormal returns.
When analysing the choice of financing, Chang (1998) discusses the monitoring hypothesis. Acquiring privately held firms with stock often leads to outside blockholdings.
18 This can cause the blockholders to monitor executives. By using cash, executives can
increase their level of entrenchment. Faccio and Masulis (2005) find cash financing to be more likely for private targets, thus supporting the entrenchment view. Therefore I expect the coefficient of Public to be negative.
- Choice of Financing (Cash)
I control for choice of financing for the analysis of abnormal returns. Cash is equal to 1 for deals that are financed with 100% cash and 0 otherwise. Previous literature leads us to believe that acquirers use cash due to an undervaluation of their stock (Travlos, 1987). Therefore the market will react more positively, leading to a positive coefficient for this control variable.
- Diversification (Diversifying)
Diversifying is a dummy variable that is equal to 1 when there is a difference in the
acquirer’s and target’s 4-digit SIC code. The asymmetric information (AI) in the acquisition process is expected to be higher in the case of diversifying M&As because the acquirer may not have expertise in the industry or segment of the target (Capron and Shen, 2007). This leads to a skeptical attitude of the market towards diversifying deals. The coefficient is therefore expected to be negative for abnormal returns.
As for the choice of financing, the reasoning includes the monitoring hypothesis and asymmetric information. Chang (1998) uses the information hypothesis to argue that target shareholders will only accept stock financing when they believe the combined firms will actually create value. The acquirer can reduce the asymmetric information by using stock financing, when considering a diversifying deal. Therefore I expect the coefficient to be negative in the choice of financing.
3.3.3. Firm Characteristics
- Firm Size (Ln (Total Assets))From the literature that is reviewed, it appears to be necessary to control for firm
characteristics of the acquirer, as they can affect abnormal returns. Ln (Total Assets) is used to control for firm size. It is the natural logarithm of the total assets reported by the firm at the end of the fiscal year prior to the year the M&A was announced. Previous studies find that the CARs are negatively related to firm size (Moeller et al., 2004; Faccio et al., 2006)
19
Tobin’s Q is used to assess the market’s evaluation of the investment opportunities of
a firm. It is defined as the market value of the company divided by the book value of total asset. Previous studies have documented a negative relationship between Tobin’s Q and CARs (Moeller et al., 2004; Masulis et al., 2007). We can expect the investment
opportunities (measured by Tobin’s Q) to predict lower chance of pure cash deals (Martin, 1996).
- Market Valuation (Book-to-Market Ratio)
I use Book-to-Market Ratio to control for the market's evaluation of the acquirer. A low ratio implies that the firm is highly valued by the market. Moeller et al. (2005) posits that higher valuations lead to more value destroying deals, as there is more managerial discretion. Therefore I expect a negative coefficient for abnormal returns. Higher valuations also
increase the likelihood of stock financing (Travlos, 1987). Therefore the coefficient is expected to be negative for choice of financing as well.
- Leverage
As we move on to the Choice of Financing analysis, there are additional controls required. I use Leverage to control for the ease with which the acquirer can finance a deal with cash. It is measured using the total liabilities scaled to total assets at the end of the fiscal year prior to the M&A announcement. Faccio and Masulis, (2005) find a negative
relationship between Leverage and the probability of cash financing. This is because the possibility of using cash to finance an M&A can be heavily reliant on the accessibility of borrowed funds. Therefore I expect a negative coefficient for this control variable.
3.4. Empirical Models
So far, Section 3 has constructed the main variables that will be of interest in this study. This subsection is dedicated to the construction of empirical models to test the Hypotheses
formulated in Section 2.3 using the variables constructed in Section 3. This thesis borrows certain methodologies from previous papers, with alterations to certain elements when necessary. The empirical models will be divided into Abnormal Returns and Choice of Financing.
3.4.1. Abnormal Returns
The study of abnormal returns will be modeled through a univariate regression analysis using ordinary least squares (OLS) with a panel dataset. The dependent variable of focus in this
20 subsection is 𝐶𝐶𝐴𝐴𝑅𝑅 ( −1, +1 )𝑖𝑖𝑖𝑖, which is the three-day cumulative abnormal returns around the announcement date (t) of firm i. The main explanatory factors are formulated around the stock options of the compensation package. I use unexercised vested stock options (as reported by Execucomp) to formulate the variable Confidence and unvested stock options to formulate Unvestedness. Using a methodology similar to Dezső and Ross (2012) and Datta et al. (2001), both are scaled to the total compensation of the CEO. Therefore the main
coefficients of interest are 𝛽𝛽1 and 𝛽𝛽2.
𝐶𝐶𝐴𝐴𝑅𝑅𝑖𝑖(−1 , +1) = 𝛽𝛽1∗ 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖+ 𝛽𝛽2∗ 𝑈𝑈𝐶𝐶𝑈𝑈𝐶𝐶𝑈𝑈𝑈𝑈𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝑈𝑈𝑖𝑖𝑖𝑖+ 𝛴𝛴𝛽𝛽𝑔𝑔
∗ (𝐺𝐺𝐶𝐶𝑈𝑈𝐶𝐶𝐺𝐺𝐶𝐶𝐺𝐺𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝐺𝐺𝐶𝐶𝐶𝐶𝑈𝑈𝑖𝑖𝑖𝑖) + 𝛴𝛴𝛽𝛽𝑑𝑑∗ (𝐶𝐶𝐶𝐶𝐺𝐺𝐶𝐶 𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝐺𝐺𝐶𝐶𝐶𝐶𝑈𝑈𝑖𝑖𝑖𝑖) + 𝛴𝛴𝛽𝛽𝑓𝑓
∗ (𝐶𝐶𝐶𝐶𝐺𝐺𝑅𝑅 𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝐺𝐺𝐶𝐶𝐶𝐶𝑈𝑈𝑖𝑖𝑖𝑖) + 𝐹𝐹𝐸𝐸𝑈𝑈 + 𝜀𝜀𝑖𝑖𝑖𝑖
The results of this study will be based on the interpretation of 𝛽𝛽1 and 𝛽𝛽2. In order to generate unbiased and consistent coefficient estimates, the assumptions of a multiple OLS and fixed effects regression should be considered (Stock and Watson, 2011). The first assumption assumes that the error term 𝜀𝜀𝑖𝑖𝑖𝑖 has a mean of 0. This is satisfied if there is no correlation between the explanatory variables and the error term. Omitted variable bias is the major reason why this assumption may be violated. Therefore, I use control variables and fixed effects to minimize omitted variable bias. Governance controls include executive ownership, a dummy for whether the CEO is also a director, and a dummy for whether a CEO is also on the Compensation Committee. Deal controls include deal size, ownership status of target firm, payment method and whether it is a diversifying merger or not. Firm controls include firm’s market capitalization, total assets, Tobin’s Q ratio and book-to-market ratio. The relevance of these is explained in the previous subsection. For multiple reasons, we cannot account for all omitted factors that influence CARs. Therefore, fixed effects are used over time and across industries, first individually, and then together. Time fixed effects allow the model to account for any variation in CARs, caused by omitted variables - that are variant across time but invariant across firms and industries. Industry fixed effects allow to account for omitted variables that vary across industries, but are time-invariant.
The second assumption is that the explanatory variables should be independently and identically distributed. With the use of fixed effects, observations can be identically
distributed at the firm level, but have to be independent of observations of other firms. This is the major source of endogeneity in this thesis, due to the sample selection process.
21 Observations are only used when all data are available, making the sample non-random. The implications of violating this assumption will be discussed in Section 7.
The third assumption relies that there are no large outliers. Truncating extreme observations controls for this. The main independent variables (CARs) and main dependent variables (Confidence and Unvestedness) are truncated at the 0.1% level. Finally, the fourth assumption that must hold is that there is no perfect multicollinearity between any of the independent variables. To check for multicollinearity, a correlation matrix is generated for all the independent variables used in the OLS and Logit (see next subsection) models. This is reported in Table 8 of the Appendix. Mela and Kopale (2002) document different studies that have different thresholds at which collinearity becomes a problem. The thresholds vary between 0.35, 0.7 and 0.9. Most of the correlation coefficients reported in Table 8 remain below 0.35, and none of them pass the threshold of 0.7. Therefore it can be safely concluded that perfect multicollinearity is not a problem.
Lastly, using robust standard errors in the models with no fixed effects, and using clustered standard errors in the models with fixed effects control for the issue of
autocorrelation. Autocorrelation is an issue as many of the independent variables are correlated across time. For example a firms assets in one year are likely to depend on the assets of the previous. This is also the case for CEO compensation.
3.4.2. Choice of Financing
The second analysis conducted in this thesis involves assessing the relationship between CEO stock option holdings and the choice of financing. Deals are separated into deals that
involved 100% cash financing and deals with less than 100% cash financing. Therefore I use a logit model similar to Malmendier and Tate (2008). The model predicts the likelihood of pure cash financing using 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖 to measure the effect of vested stock options
and 𝑈𝑈𝐶𝐶𝑈𝑈𝐶𝐶𝑈𝑈𝑈𝑈𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝑈𝑈𝑖𝑖𝑖𝑖 to measure the effect of unvested stock options. LOG assumes a logistic distribution. The control variables used are almost identical to the model in 3.4.1, with
additions and removals as stated below.
Pr{𝐶𝐶𝐺𝐺𝑈𝑈ℎ 𝐹𝐹𝐶𝐶𝐶𝐶𝐺𝐺𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐹𝐹𝑖𝑖𝑖𝑖 = 1|𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖, 𝑈𝑈𝐶𝐶𝑈𝑈𝐶𝐶𝑈𝑈𝑈𝑈𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝑈𝑈𝑖𝑖𝑖𝑖, 𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝐺𝐺𝐶𝐶𝐶𝐶𝑈𝑈𝑖𝑖𝑖𝑖}
22 Given the Logit model, we can predict the probability of cash financing for specific levels of Confidence/Unvestedness using the following formula given by Stock and Wantson (2011):
1
1 + 𝐶𝐶−(𝛽𝛽0+𝛽𝛽1∗𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈+𝛽𝛽2∗𝑈𝑈𝐶𝐶𝑈𝑈𝐶𝐶𝑈𝑈𝑈𝑈𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝑈𝑈𝐶𝐶𝑈𝑈+𝛽𝛽𝐶𝐶∗𝐶𝐶𝐶𝐶𝐶𝐶𝑈𝑈𝐺𝐺𝐶𝐶𝐶𝐶𝑈𝑈𝐶𝐶𝑈𝑈)
To align the model with the findings of previous literature, I remove certain control variables and add others. An analysis by Martin (1996) indicates that firm size does not influence financing decisions. Therefore ln (Total Assets) is removed. I add executive
ownership as this is proven to increase the likelihood of cash financing (Amihud et al., 1990; Martin, 1996). In line with Faccio and Masulis (2005), Leverage is added to control for the cash accessibility.
4. Data & Summary Statistics
This section is dedicated to the sample characteristics and collection process. The aim is to augment the replicability of this thesis as well as provide initial evidence of the difference between M&As conducted by CEOs holding different amounts of stock options.
4.1. Sample Collection
The data collection begins using the Thomson ONE (SDC Platinum) database for information on mergers and acquisitions. Deals are collected based on the following criteria: 1) The deal was announced between the 1st of January 1992 and the 31st of December 2016; 2) Both the Acquirer Nation and Target Nation are located in the United States of America; 3) The Acquirer's Public Status is Public 4) The Deal Value is at least $1 million; 5) The Deal Status is Completed.
The timeframe of the study is chosen in line with the availability of data on CEO compensation, which is only widely available in the U.S. Deals in the years 1991 and 2017 are collected as well to ensure there is no overlap in the announcement effect of two deals by the same acquirer. This study does not extend to foreign targets as previous research shows that cross-border M&As have quite different characteristics that determine their performance (Rossi and Volpin, 2004). I limit the acquirers to publicly listed firms in order to retrieve the relevant information about its executive compensation packages, firm characteristics, and its
23 stock prices. A transaction value of $1 million is chosen to ensure an economically
significant deal size. In line with previous research, the deal must be completed. It has also been found that completed deals can impact the compensation as well as the future of an executive at the acquiring firm (Datta et al., 2001; Agarwal and Walkling, 2004). In addition to these criteria, deal characteristics such as the payment method, public status of the target and the industrial classification codes of acquirer and target are included in the dataset.
After collecting the acquisitions data, the Wharton Research Data Services (WRDS) was used for the remaining data on stock prices, executive compensation and firm
characteristics. Historical stock prices and daily returns of all available companies were collected from The Center for Research in Security Prices (CRSP). Additionally, the daily returns on a value-weighted market portfolio index (including all distributions) are also collected. The market portfolio is generated based on all public companies listed on the same stock exchange as the acquirer (i.e. NYSE/AMEX/NASDAQ/ARCA). Using this dataset, cumulative abnormal returns CARs were calculated over 3, 5 and 21 days surrounding the announcement dates. To identify the data for each individual company, NCUSIP and
PERMCO are used. CRSP uses an 8-digit CUSIP (a unique identifier for each security issued by a company), which can change over time as companies’ change their name or capital structure. Therefore the historical CUSIP (NCUSIP) is collected, which preserves all CUSIPS in one single identifier. Thomson ONE on the other hand uses a 6-digit CUSIP. By using the Compustat Capital IQ CUSIP Converter, all historical 8-digit CUSIPs are converted into 6 digits. This allows the merging of the cumulative abnormal returns from CRSP with the acquisitions from Thomson ONE.
Once the CARs have been merged with all the deals, each acquirer is provided with a PERMCO company identifier from the CRSP database. WRDS Compustat on the other hand uses the GVKEY to identify individual companies. In order to combine these two databases, the CRSP/Compustat Merged Database - Linking Table is used to assign a GVKEY to every acquirer. Next, using the GVKEY, I collect the various aspects of executive compensation data that is required. Information regarding the current CEO, his/her salary, bonus, total direct compensation, the number and values of different stock options granted, percentage of stock owned and two measures of corporate governance (Director and Compensation Com. as defined in Table 9 of the Appendix).
Finally, I collect firm specific control variables from Compustat - Capital IQ: North America - Annual Updates. This includes information about firm size (total assets and market
24 value), the book value per share, shares outstanding and stock price at the end of the calendar year. The final sample contains 2,594 acquisitions taken by 1,502 CEOs.
4.2. Summary Statistics
Table 1 provides the descriptive statistics of the various deal, compensation and firm
characteristics. Panel A exhibits the main dependent (and control) variables of this empirical study. The summary statistics indicate on average, acquirers experience a 0.68% gain over the 3 days surrounding the announcements. Previous studies document negative or
insignificant abnormal returns to acquirers of public targets (Hackbarth & Morellec, 2008), while they tend to be positive in the case of private targets (Faccio et al., 2006). The findings of positive CARs is possibly due to 68% of the sample containing acquisitions of private firms. The average transaction value is US$857 million, which is considerable higher than the median of US$125 million. The largest deal is valued at $130 billion, displaying the vast range of M&As considered in this sample, adding to the credibility of this study.
Panel B contains the relevant information on the annual compensation package of CEOs in the sample. These components are used to create the main independent variables of interest in this study. There is a visible difference between the Total Compensation and the sum of Salary plus Bonus. A large portion of this difference is accounted by the stock options granted to CEOs. These stock options are either vested (exercisable) or unvested
(non-exercisable). The portions of vested stock options (that have not been exercised) are scaled to the total compensation to yield the Confidence of the CEO. CEO’s on average are invested in the company by choice by 140% of their annual salary. This is significantly higher than the median of 36% due to the extreme cases where CEO’s chose to stay invested in the company with large sums of money. The portion of unvested stock options (Unvestedness) is also scaled to Total Compensation represents a part of the compensation package that is yet to be earned. This portion of equity-based compensation seeks to motivate the CEO to enhance the firm’s performance and thus market valuation. The compensation packages keep CEOs invested in the company by about 46% of their annual compensation. The natural logarithms of Confidence and Unvestedness are reported because these are used as the main explanatory variables in the regression equation.
Panel C and D contains corporate governance and firm-level control variables. Executives on average hold 3% of the outstanding shares. It appears that 88% of CEOs are also a part of the Board of Directors, enhancing their ability to make an acquisition decision.
25 Table 1: Summary Statistics
This table summarizes the characteristics of the sample used in this study. The sample consists of 2,549 deals made by 1,812 CEOs in 1,509 acquiring firms over a time period from 1st January 1992 to 31st December 2016. Each panel displays the variables according to a defining group. Panel A outlines the deal
characteristics. The main dependent variables of this study are CAR(-1 , +1) and Cash. CAR (-1 , +1) is the three-day cumulative abnormal returns around the day of announcement. It is calculated using the market model for normal returns. The estimation window used for normal returns begins 260 days before and ends 60 days before the announcement date. Cash is a binary variable that is equal to 1 if the deal was financed with 100% cash, and is equal to 0 otherwise. Panel B contains the components of executive compensation that are important to this study. Confidence is the estimated value of all the CEO’s vested stock option holdings that have not been exercised, scaled to Total Compensation. Unvestedness is the estimated value of all the CEO’s stock option holdings that remain unvested, scaled to Total Compensation. Total Compensation is the retrieved for the fiscal year ending before the year of the acquisition; it consists of salary, bonus, other annual compensation, total value of restricted stock granted, total value of stock options granted (using the Black-Scholes model), long-term incentive payouts, and all other total. ln (1+Confidence)/ln (1+Unvestedness) are the main independent variables; it is constructed using the natural logarithm. Panel C and Panel D contain other control variables used in the econometric models formulated in Section 3.4.
Variable Observations Mean Median Standard Deviation
Minimum Maximum
Panel A: Deal Characteristics
CAR ( -1 , +1 ) 2,549 0.68% 0.34% 6.35% -40.22% 42.25% CAR ( -2 , +2 ) 2,549 0.64% 0.35% 7.01% -46.51% 44.20% Deal Value (US$ Million) 2,549 857 125 3882 1 130298 Public 2,549 0.32 0 0.47 0 1 Cash 2,549 0.43 0 0.50 0 1 Diversifying 2,549 0.55 1 0.50 0 1 Panel B: CEO Compensation
Salary (US$ Thousand) 2,549 673.24 600.00 388.79 0.00 3967.50 Bonus (US$ Thousand) 2,549 357.88 0.00 1,258.18 0.00 28,500.00 Total Compensation (US$ Thousand) 2,549 5,056.78 3,096.10 6,565.24 0.00 151,221.10 Confidence 2,549 1.40 0.36 2.66 0.00 22.71 Unvestedness 2,549 0.46 0.09 0.94 0.00 8.59 ln ( 1 + Confidence ) 2,549 0.57 0.31 0.68 0.00 3.17 ln ( 1 + Unvestedness ) 2,549 0.28 0.09 0.40 0.00 2.26 Panel C: Corporate Governance
Executive Ownership (%)
2,549 3.09 0.60 7.21 0 100
Director 2,549 0.88 1 0.33 0 1
26 Only about 1% of CEOs are on the Compensation Committee, which is likely to allow these CEOs to influence their compensation packages around the time of the acquisition. As for the firm size, it appears that the average acquirer is valued at around US$15.5 million. Once again, this sample contains a wide range of acquirers’, with asset value ranging from US$9 thousand to US$2.5 billion. Compensation and firm data is provided on an annual basis and therefore represents the figures in the year prior to the announcement of an acquisition.
Table 2: Non-Parametric Test for Main Dependent Variables
This table contains a mean-comparison t-test by grouping the main dependent variables into two categories i.e. Low Confidence/Unvestedness and High Confidence/Unvestedness. In Panel A, Low
Confidence includes observations that are below or equal to the median of the ln (Confidence) measure. Observations above the median are considered High Confidence. Panel B separates the sample into Low and High Unvestedness, once again based on whether it is lower than/equal to or greater than the median of ln (Unvestedness). All variable are defined in Table 9 of the Appendix. *,
**, and *** indicate significance levels of 10%, 5%, and 1% respectively. Panel A:
All
Firms Low Confidence High Confidence t-statistic of Difference CAR ( -1 , +1 ) 0.68% 0.50% 0.86% -1.44 Cash Financing 0.43 0.42 0.45 -1.71* Panel B: All Firms Low Unvestedness High
Unvestedness t-statistic of Difference CAR ( -1 , +1 ) 0.68% 0.30% 1.07% -3.07*** Cash Financing 0.43 0.41 0.45 -1.93*
To provide initial evidence that the measures of Confidence and Unvestedness impact mergers and acquisitions, I use a non-parametric test of the difference in the equality of the sample mean. This is reported in Table 2. Panel A reports the difference between high and low confidence, while Panel B reports the difference between high and low unvestedness. High confidence/unvestedness occurs when the measure is greater than the sample median,
Table 1 Continued Panel D: Firm Characteristics
Total Assets (US$ Thousand) 2,549 15,580.42 2,260.18 86,864.88 9.28 2,490,972.00 Leverage 2,549 0.53 0.53 0.23 0.04 1.03 Market Value (US$ Thousand) 2,549 9,938.07 1,846.92 35,867.46 4.73 626,550.40 Tobin's Q 2,549 1.34 0.98 1.61 0.01 40.40 Book-to-Market Ratio 2,549 0.53 0.45 0.40 0.00 4.73
27 and low occurs when it is below or equal to the sample median. The initial tests show that
Confidence doesn’t affect the CARs experienced by acquirers, while the amount of
Unvestedness positively impacts CARs. There is weak initial evidence that Confidence and Unvestedness impacts the choice of financing a deal, making the likelihood of a cash
financed deal higher.
5. Results
This section applies the proposed empirical methodology of Section 3 on the sample created in Section 4 to provide evidence for the hypotheses developed in Section 2. The results are split into Abnormal Returns and Choice of Financing.
5.1. Abnormal Returns
First, to study Hypothesis 1 and Hypothesis 2, the research assesses the impact of CEO stock options (independent variables) on abnormal returns (dependent variable) for shareholder through M&As. The results are reported in Table 3. Abnormal returns are measured by the cumulative abnormal returns (CARs) over three days (from t - 1 to t + 1) surrounding the announcement date (t) of an M&A. The amount of stock options that a CEO is entitled to is split up into the measures of Confidence (vested stock options) and Unvestedness (unvested stock options). The coefficients of these measures are of primary interest to this study. Table 3 displays the regression model constructed in section 3. The model is split into 4 separate models, using different fixed effects and standard errors. The results will be interpreted using Model 5.4 as this controls for variation over time and within industries using fixed effects. Consistent with the initial tests in the descriptive statistics, the findings indicate that
Confidence does not significantly influence the three-day CARs, while Unvestedness does.
First, the significant results of Unvestedness are discussed. Since the variable is constructed using a log distribution, the coefficient is interpreted through percentage changes. Increasing the Unvestedness of a CEO by 10% leads to an increase in CARs by
approximately 0.12 percentage points. The coefficient for Unvestedness is initially significant at the 1% level in all models except Model (3), where it reduces to the 5% level. Although the significance reduces, the magnitude of Unvestedness remains relatively stable. CARs
fluctuate between 0.10 and 0.12 percentage points for a 10% increase in unvested stock options. Datta et al. (2001) finds that large amounts of equity-based compensation (EBC) in
28 Table 3: Impact of Stock Options on Abnormal Returns
This table contains the Ordinary Least Square (OLS) regressions conducted to assess the effect of CEO stock options on three-day cumulative abnormal returns CAR ( -1 , +1 ) surrounding the announcement date. CAR ( -1 , +1 ) is the dependent variable in all models. CAR ( -1 , +1 ) is calculated using the market
model, with an estimation window beginning 260 days prior and ending 60 days prior to the announcement. The values of the stock options are differentiated by whether they are vested (Confidence)
or unvested (Unvestedness). Confidence/Unvestedness is scaled to the Total Direct Compensation of the CEO in the fiscal year prior to the acquisition. ln((Confidence)/ln(Unvestedness) is the natural logarithm of 1 + Confidence/Unvestedness. All other variables are defined in Table 9 of The Appendix. The sample
includes 2,549 deals between 1992 and 2016. Models (1) to (4) report this effect using levels of fixed effects. Standard errors are reported in parentheses. Model (1) has robust standard errors. Models (2), (3) and (4) have standard errors clustered at the level for which fixed effects are used. *, **, and *** indicate
significance levels of 10%, 5%, and 1% respectively.
(1) (2) (3) (4) ln (Confidence) 0.0008 0.0007 0.0015 0.0012 (0.0021) (0.0022) (0.0020) (0.0021) ln (Unvestedness) 0.0110*** 0.0123*** 0.0103** 0.0116*** (0.0041) (0.0039) (0.0040) (0.0039) Director -0.0015 -0.0025 -0.0002 -0.0009 (0.0035) (0.0039) (0.0039) (0.0040) Compensation Committee 0.0020 0.0051 -0.0032 -0.0007 (0.0087) (0.0117) (0.0086) (0.0086) ln (Deal Value) 0.0023** 0.0022** 0.0023* 0.0022* (0.0010) (0.0010) (0.0012) (0.0012) Relative Value -0.0070 -0.0070* -0.0056 -0.0056 (0.0067) (0.0042) (0.0071) (0.0070) Public -0.0163*** -0.0157*** -0.0181*** -0.0178*** (0.0031) (0.0030) (0.0033) (0.0033) Cash 0.0125*** 0.0116*** 0.0131*** 0.0123*** (0.0025) (0.0026) (0.0031) (0.0031) Diversifying -0.0056** -0.0053** -0.0051 -0.0048 (0.0026) (0.0026) (0.0031) (0.0031) ln (Assets) -0.0045*** -0.0045*** -0.0045*** -0.0045*** (0.0010) (0.0010) (0.0014) (0.0014) Tobin's Q -0.0046*** -0.0045*** -0.0040*** -0.0039*** (0.0012) (0.0009) (0.0015) (0.0015) Book-to-Market Ratio 0.0000 0.0009 -0.0013 -0.0010 (0.0045) (0.0037) (0.0054) (0.0054) Year Fixed Effects No Yes No Yes Industry Fixed Effects No No Yes Yes Observations 2549 2549 2499 2499 Adj. R-squared 0.0337 0.0369 0.0469 0.0502 the year prior to the M&A, causes executives to engage in acquisitions with higher value creation than executives with low amounts of EBC. One of the drawbacks of Datta et al. (2001) is the negligence of the value of previously granted options. The findings in Table 3 support Datta et al. (2001), with an insight into the EBC awarded in all years prior to the
