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Amsterdam Business School
Master Thesis
The Effect of Source of Financing on Stock Returns of Bidding Firms
--- An Analysis Based on M&A Announcement
Xiaodan Liu (10493484)
MSc Business Economics: Finance Supervisor: Prof. Vladimir Vladimirov 2014. 07
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Abstract
This thesis investigates the effect of source of financing on bidding firms’ stock returns using American data from 1978 to 2013. While most previous literatures studied the
announcement effect of the bidding firm focusing more on the method of payment and the premium, this thesis takes the source of financing into consideration as well. There are two major findings of this thesis. Firstly, event study shows that compared to bidding firms financing with equity, those who finance with internal cash reserves and debt obtain better stock returns. The second finding is that taking into the interaction of premium and source of financing into consideration, whether cash-financing bidders experience better stock returns than equity-financing bidders depends on the premia they pay.
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Content
1. Introduction ... 4
2. Literature Review ... 7
2.1. The takeover motives ... 7
2.2. The method of payment ... 7
2.3. Information asymmetry and the source of financing ... 9
2.4. Source of financing and bidder’s stock return ... 11
2.5. Premium and bidder’s stock return ... 11
3. Methodology ... 14
3.1. The long-term event study ... 14
3.2. The short-term event study ... 15
3.3. Cross-sectional analysis... 17
4. Data and descriptive statistics ... 20
5. Empirical Results ... 23
5.1. Long-term Event Study ... 23
5.2. Short-term Event Study ... 24
5.3. Cross-sectional Analysis ... 27
6. Robustness Test ... 29
7. Conclusion ... 32
8. References ... 34
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1. Introduction
Corporate mergers and acquisitions are among the largest investments that a company ever will undertake (Betton et al., 2008). A successful acquisition can be defined as a contractual agreement which is profitable for both of the acquiring firm and the acquired firm. Two of the important compositions of an M&A agreement are the premium and the method of payment. The effect of the premium and method of payment on merging firms has been extensively researched (Travlos, 1987; Varaiya and Ferris, 1987; Eckbo et al., 2008; Belen et al, 2009). However, there is another factor which is interacting with both of the premium and the method of payment seems to be ignored. This factor is the source of financing. Martynova and Renneboog (2009) investigated plenty of academic papers and found that many previous researches simply proxy the source of financing by the method of payment. Nevertheless, the truth is not that simple. According to their paper, of all-cash-payment acquisitions, one-third is at least partially financed by external funds, including debt issuance and new equity issuance; And of the bidders using hybrid payment to close the deal, 37% opt to borrow to raise cash for the cash component of the offer. Thus
discriminating the source of financing from the method of payment enables a more convincing conclusion on the determinant of bidding firms’ stock returns. Many empirical findings prove that bidders using cash payment experience better stock returns than those who use stock payment (See Eckbo et al. (2008) for an overview). This phenomenon can be explained by signal theory, information asymmetry theory, etc. Similarly, in all-cash
payment bids, bidders’ cash come from different sources including equity issuance, internal cash reserves as well as debt issuance. Do these sources of financing diversely affect bidders’ stock returns? If they do, what theory can be applied to account for the diverse? The other reason that the source of financing matters is the magnitude of premium is influenced by
5 the source of financing. This argument is elaborated by Vladimirov (2014). Bidder’s source of financing depends on their ability of entering competitive credit market. Different credit markets have different degrees of information costs. That is to say, same amount of cash raised from different sources bears different costs. Thus, even if bidders offer the same bid price, their stock returns may react differently. Hence, the analysis of bidder’s stock return solely based on the method of payment or premium could be problematic. It is of both theoretical and practical significance to further looking at the impact of source of financing.
This thesis aims to shed light on the effect of source of financing on bidding firms’ stock return. Whether the bidding firms enjoy rise in their stock prices is examined by event study. The correlation among premium and source of financing and how they jointly affect bidding firms’ stocks is examined by cross-sectional regression. At last, the robustness tests for these effects are implemented by applying longer event windows or a different benchmark. Based on empirical findings, this thesis reaches the conclusion that on average bidders financing with cash and debt experience better stock returns than those financing with equity. But after taking into the interaction of premium and the source of financing into consideration, the conclusion changes a little bit, especially for bidders who finance their bids with internal cash reserves: compared to bidders financing with equity, whether they receive higher abnormal return is influenced by the premia they pay. When they pay low premia, their stock returns are worse; but the higher premia they pay, the higher abnormal return they will obtain.
The remainder of this thesis is set up as follow. Section 2 is literature review, elaborating the fact of M&A as well as corresponding theory; Section 3 explains the methodology; Section 4
6 describes the sample data; Section 5 presents the empirical results; Section 6 is robustness test; Section 7 concludes and discusses the results of this thesis.
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2. Literature Review
2.1. The M&A motives
There are many reasons for corporate M&A, under the rubric of corporate synergy theory, the bidding firm exploits some specialized resource by gaining the control of the target firm and implementing some higher-valued operating strategies including more efficient
management, economies of scale, improved production techniques, increased market power, and so on (Bradley et al., 1983). Basically, these strategies fall into two categories: profit-creating and cost-reducing. Based on these benefits, a successful merger or
acquisition should have a positive impact on the wealth of the bidding company. In addition to this synergy motive, Shleifer et al. (2003) proposed that, on the basis of neoclassical theory, corporate acquisition is driven by the stock market valuation of the merging firms. They take the market-inefficiency and the rational manager as given, explaining that the bidder manger makes the decision to acquire another firm when it is perceived that the firm is overvalued in comparison to the target. Furthermore, in this situation, bidder manager prefers a stock offer to a cash offer because the takeover can be completed at a lower cost using stock as payment. However, from the perspective of psychology, Roll (1986) attributed the corporate takeover motives to the hubris of manager. He assumes that the market is strong-form efficient but the manager is irrational. He argues that the bid price which is higher than the market price of the target is simply a positive valuation error, representing an over-estimation of the economic value of the merging firms. Hubris hypothesis predicts the value of the bidding firm should decrease, the value of the target should increase, and the combined value of the target and bidder firms should fall slightly.
8 Plenty of empirical literatures have verified that the method of payment can affect bidder’s stock return. For instance, Savor (2006) grouped 1335 non-hostile merger bids and grouped them as either all-cash payment bids or all-stock payment bids, and discovered that the 3-day average cumulative abnormal return--- ACAR (-1,1) for all-stock bidders is -3.5% while ACAR(-1,1) for all-cash bidders is 1.0%. Similarly, Moeller et al.(2005) analyzed 4322 all-cash and all-stock bids, reaching the result that the ACAR (-1, 1) for the total sample is 0.8%. When the target is public, the ACAR (-1, 1) is -2.3% in all-stock deals and 0.7% in all-cash deals. Eckbo (2009) stated when the initial bidder is relatively large compared to the publicly listed target firm and the payment method is stock offer, the average three-day
announcement-period abnormal stock return is as low as −2.21%.
The method of payment depends on various factors. According to Betton et al. (2008), there is little doubt that taxes play an important role in the bidder’s choice of payment method. Depending on the country, each jurisdiction has its own tax implications based on the method of payment used during the course of the takeover. As such the bidding firm will seek a method which is most beneficial for their shareholders. Under the U.S. Internal Revenue Code (IRC), target shareholders are supposed to pay capital gains tax after they receive money in the all-cash payment deals, while those shareholders who accept all-stock payments can defer their taxes until they realize the income by selling the shares. Hence, for the bidder, cash deal is more costly compared to stock deals. Empirical studies by Huang and Walkling (1987), Hayn (1980) using U.S. data support this argument. The corporate control structure would also accounts for the choice of payment. Under the threat of control dilution causing by all-stock offer, the bidder tends to use all-cash payment in takeover deal. Amihud,et al. (1990), Martin (1996), and Ghosh and Ruland (1998) examined acquisitions in
9 the U.S. and found that as the number of stocks held by management of the bidding firm increases, the portion of the stock payment used for takeover would decrease. Similar fact is found in European acquisitions; Faccio and Masulis (2005) proved that the more
concentrated the share-ownership is within a business, the more likely that they would choose cash payment. Further evidence from Rhodes-Kropf and Viswanathan (2004) argued that market environment influence the method of payment as well. Whether a target manager accepts offer or not will depend on the assessment of potential synergies between the two businesses. They found in a booming market, the target is more likely to
overestimate the synergies and overvalue the stock offer. Therefore, they concluded that the means of payment would contain a higher fraction of stock being exchanged during economic growth period and vice versa during economic downturn. In addition to all factors stated above, there is another explanation for the choice of payment, that is, the
information asymmetry. Hansen (1985) argued that given one-sided information asymmetry (there is no uncertainty about the true value of the bidder), there is a preference for stock offer because the ex-post payment method such as stock exchange can reduce the
overpayment cost and may increase the deal value. However, if two-sided information asymmetry (the value of the bidder is private information) exists, the bidder may not prefer the stock payment anymore if it is significantly undervalued. The empirical study from Chemmanur and Paeglis (2005) is consistent with this argument i.e. - the probability of stock offer decreases if the bidder’s stock price is undervalued.
2.3. Information asymmetry and the source of financing
Information asymmetry not only affects the method of payment, but also affects the source of fund of a cash bid. Sources of financing consist of debt financing, equity financing and
10 internal cash reserves. Raising cash from different sources have different cost of capital, which is affected by the information asymmetry. A firm may issue new equity at a high price in two situations: 1. there is a good investment project needs to be financed, and investing in this project increase firm value; 2. this firm is overvalued by the market and the
management decides to take this advantage to raise more cash. Myers and Majluf (1984) proclaimed that because information asymmetry exists---the management has private information thus can accurately value the new investment project but market investors cannot. The market investors tend to discount the price they are willing to pay. Therefore, if a firm still wants to raise money from those uninformed market investors, it has to issue new stocks at a price, which is lower than they really worth. That is to say the value of this project will be underestimated by market. However, issuing new equity at a discount will lead to wealth transfer from existing shareholders to new shareholders. Assume that the management acts in the best interest of the existing shareholders, equity issuance is deemed to be the “last resort” for raising cash. In order to avoid the “dilemma of either passing by positive-NPV projects or issuing equity at a low price” (Myers, 1984, p.589), a firm has motive to use internal funds first. External financing should be employed when there is no sufficient cash reserves. According to the pecking order theory (Myers, 1984), with respect to cost of capital, the preference ranking of external funds is safe debt (which has approximately default-free interest rate) first, risky debt or convertibles and then common stock.
Consequently, the first hypothesis of this thesis is: Mergers and acquisitions financed by
internal cash are more than those financed by debt, and fewest mergers and acquisitions are financed by equity issuance.
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2.4. Source of financing and bidder’s stock return
In addition to the financing order, different sources of funds have different impact on bidder’s stock return. According to signal theory, issuing equity signals that the firm is overvalued, hence there will be a downward adjustment in corporate stock price after the equity offering. In contrast to the negative signal of equity issuance, financing mergers and acquisitions payment through internal cash reserves or debt issuance conveys the
information that the firms are probably undervalued, or at least fairly valued. Thus there will be an upward revision of the price of the bidding firms’ stocks. Furthermore, in line with the asymmetric information theory, now that bidders choose to use internal cash reserves instead of issuing new equity, it means that the bidders is sure about the profitability of the investment. Consequently, market will interprets the cash-financing offer as good news. Meanwhile, if bidder uses debt financing and the debt is granted by a bank, the bank will go perform the due diligence before the debt is granted, as such it conveys good information of the profitability of the merging firms as well. Thus, the bidders financing with debt will receive better stock returns than those who finance with equity.
Therefore, the second hypothesis of this thesis is: Bidders financing their M&A bids through
cash or debt receive better stock returns than those who finance through equity issuance.
2.5. Premium and bidder’s stock return
The premium refers to the part which bid price is above the market value of the target stocks to ensure the M&A success and gain control over the acquired organization (Díaz et al., 2009). According to synergy hypothesis, the bid prices in mergers and acquisitions depend on the synergies expected; therefore the premium is supposed to appropriately
12 reflect the future cash flow generated from the target. However, if the bidder overpays for the target, the premium may have a negative influence on abnormal return of the bidder (Belen et al. 2009). Empirically, there is no existing consensus on how premium affect the bidder’s return so far. Varaiya and Ferris (1987) examined the corporate takeovers
completed between 1974 and 1983, and revealed that the winning bid premia overstated the market expectation of merging firms and that the cumulative average excess returns of the bidders were significantly negative. By comparing the American merger waves in 1980s and 1990s, Moeller et al. (2005) suggested that the relationship between the acquisition premium and bidders’ abnormal returns was vague, since the coefficients of premium in the multiple regressions of bidder 3-day announcement returns are insignificant. Díaz et al. (2009) showed a quadratic relationship between premium and the bidder’s return: there is a critical value, when the premium is lower than this value, the premium positively influences the bidder’s return, which reflects the synergy hypothesis; however, if the bidder pays too much for the target, then the relationship between the premium and the bidder’s return becomes negative, which is consistent with the overpayment hypothesis. According to Vladimirov (2014), bid price itself depends on the cost of information asymmetry. When bidders have cash constrains and have no access to competitive capital market, that is, they can only finance their bids through selling levered-equity, which is particularly information-sensitive, taking into consideration of information asymmetry, bidders have to bear the considerably high information costs. Facing this high information asymmetry costs, offering high premium is extremely expensive and high premium may have significant negative impact on bidders’ stock returns. In other words, when bidders do not have cash constrains or have access to competitive market for capital, that it, when information asymmetry problem is mitigated, the negative impact of premium on CAR may be mitigated as well.
13 Therefore the third hypothesis of this thesis is: The impact of high M&A premium on stock
returns varies among bidders using different sources of financing. The negative impact of high premium on bidding firm’s stock price is weaker for bidder using internal cash to finance their bids than those using external financing.
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3. Methodology
3.1. The long-term event study
When studying the stock performance of the bidding firm after M&A, the characteristic-based matching approach which is also known as the buy-and-hold abnormal returns (BHAR) method has been widely used (Kothari and Warner, 2008). This method measures the
influence of M&A on the bidder by the BHAR. This abnormal return is defined as “the
average multiyear return from a strategy of investing in all firms that complete an event and selling at the end of a pre-specified holding period versus a comparable strategy using otherwise similar nonevent firms” (Kothari and Warner, 2008, p. 162). The underlying assumption is that the corporate characteristics perfectly proxy the expected return of nonevent firms and that given same (or similar) corporate characteristics, the difference in stock performance is caused solely by the event. However, according to Kothari and Warner (2008), the takeover event is by no chance “exogenous with respect to past performance and expected returns”. Thus the assumption itself is not solid enough, in other words, even if two firms share similar characteristics, they are systematically different and the possibility that the M&A event taking place in one firm but not in the other one can still occur. Based on the analysis stated above, in this thesis when studying the long term stock performance after M&A announcement, the Calendar-Time Portfolio Regression approach (or also known as Jensen-alpha approach) will be employed. As “the use of daily instead of monthly
security return data permits more precise measurement of abnormal returns and more informative studies of announcement effects”(Kothari and Warner, 2008, p.8), the long-term event study is based on daily calendar-time portfolio regression approach . The
15 calendar-time portfolio regression approach is constructed based on Fama-French three-factor model as follow:
𝑅𝑝,𝑡− 𝑅𝑓,𝑡 = 𝛼𝑖 + 𝛽𝑖(𝑅𝑚,𝑡− 𝑅𝑓,𝑡) + 𝑠𝑖𝑆𝑀𝐵𝑡 + ℎ𝑖𝐻𝑀𝐿𝑡 + 𝜖𝑝,𝑡
where 𝑅𝑝,𝑡 is the daily return of the calendar portfolio which is formed by securities of event
date; 𝑅𝑓,𝑡 is the daily risk free return; 𝑅𝑚 ,𝑡 is the daily return of the value-weighted market
index; 𝑆𝑀𝐵𝑡 is the value-weighted average return on small market-capitalization portfolios
minus the value-weighted average return on three large market-capitalization portfolios; 𝐻𝑀𝐿𝑡 is the value-weighted average return on two high book-to-market equity portfolios
minus the value-weighted average return on two low book-to-market equity portfolios; 𝜖𝑝,𝑡
is the error term. After running the regression described above, the intercept (𝛼𝑖)
represents the average daily abnormal return. The null hypothesis for the intercept (variable of interest) is zero. A significantly negative 𝛼 proves that event firms suffer a drop in stock return in the long run, and a significantly positive 𝛼 proves that event firms experience a rise in their stock returns in the long run. There are two long-term event windows in this thesis --- post---event period (0, 360 days) and (0, 720 days).
3.2. The short-term event study
Fama et.al (1969) examined how common stock prices adjusted to stock split
announcements and found evidences indicating that the information implication of splits were fully reflected in stock prices almost right after the announcement date. Therefore, in this thesis, assuming the M&A is unanticipated and the economic effect of M&A
16 announcement is reflected immediately in stock price, I have constructed the variable measuring this economic effect as
𝐴𝑅𝑖,𝑡 = 𝑅𝑖,𝑡− 𝐸{𝑅𝑖,𝑡 ∣ 𝑋𝑡},
where 𝑅𝑖,𝑡is the actual ex-post stock return for firm i, at event date t, and 𝐸{𝑅𝑖,𝑡 ∣ 𝑋𝑡} is the
expected return estimated by a benchmark. The difference between the actual value and the expected value is the economic effect of M&A, in other word, the abnormal return.
In order to estimate the expected return, Fama-French three-factor model is applied. The Fama-French model (1993) is:
𝑅𝑖,𝑡 = 𝛼 + 𝛽𝑖𝑅𝑚,𝑡 + 𝑠𝑖𝑆𝑀𝐵𝑡+ ℎ𝑖𝐻𝑀𝐿𝑡 + 𝜖𝑖,𝑡
where 𝑅𝑖,𝑡is the rate of return of the common stock of the 𝑖𝑡ℎ firm on date t; 𝑅𝑚 ,𝑡 is the
rate of return of a market index on day t; 𝑆𝑀𝐵𝑡 and 𝐻𝑀𝐿𝑡 are as defined above; 𝜖𝑖,𝑡 is the
error term, which has zero mean and is uncorrelated with 𝑅𝑚 ,𝑡, uncorrelated with 𝑅𝑘,𝑡 for
k≠i, not autocorrelated, and homoscedastic. For every sample firm, daily stock price between 301 days and 46 days before the announcement is collected for estimation.
Then the abnormal return 𝐴𝑅𝑖,𝑡is now defined as:
𝐴𝑅𝑖,𝑡 = 𝑅𝑖,𝑡 − (𝛼 + 𝛽𝑖 𝑅𝑖 𝑚,𝑡 + 𝑠 𝑆𝑀𝐵𝑖 𝑡+ ℎ 𝐻𝑀𝐿𝑖 𝑡) where the coefficients are OLS estimates of 𝛼, 𝛽𝑖, 𝑠𝑖 𝑎𝑛𝑑 ℎ𝑖.
Then the average abnormal return (𝐴𝐴𝑅𝑡) is the sample mean:
𝐴𝐴𝑅𝑡 = 1
𝑁 𝐴𝑅𝑖,𝑡
𝑁
17 where t is defined in trading days relative to the event date, here t=-46, which means 46 days before the announcement.
Over an interval of at least two trading days beginning with 𝑡1and ending with 𝑡2, the
cumulative abnormal return is defined as:
𝐶𝐴𝑅 𝑡1, 𝑡2 = 𝐴𝐴𝑅𝑡 𝑡2 𝑡1 𝑡𝐶𝐴𝑅 = 𝐶𝐴𝑅 𝑡1, 𝑡2 [𝜎2(𝑡 1, 𝑡2)] where, 𝜎2 𝑡1, 𝑡2 = (𝑡2− 𝑡1) 𝜎2(𝐴𝑅𝑡).
If 𝐶𝐴𝑅 𝑡1, 𝑡2 > 0, we can say the takeovers have positive short-term effect, and vice versa
if C𝐴𝑅 𝑡1, 𝑡2 < 0.In this thesis, there are three event windows: (-10, 10), (-5, 5), and (-1, 1),
respectively, while day zero is the date when the bidder makes the public M&A announcement.
3.3. Cross-sectional analysis
According to Kothari and Warner (2008), “cross-sectional tests are a standard part of almost every event study (p.19)”. So the research Hypothesis 2 and Hypothesis 3 in this thesis will be further tested applying a cross-sectional regression. Cross-sectional analysis examines how the stock returns are correlated to corporate or transaction and firm characteristics. These characteristics include the relative size of the bidding firm and the target firm (Relsize), the ratio of cash payment involved (Pct_Cash) as well as the size of bidder (lnTA). Many studies carried out have taken into account the influence of the relative size of the acquiring firm to the acquired firm on the acquiring firm’s post-acquisition stock performance. This
18 variable is one determinant of stock return, and correlated with other explanatory variable. To my best knowledge, Asquith et al. (1983) are the first ones to prove the relative size is relevant to bidder’s stock return: the larger the relative size, the greater CER (cumulative excess return) bidder will gain. Hansen (1985) measured the double asymmetry of
information using the relative size of the target compared to the size of the bidder. As the bidders buy assets with uncertain value, they prefer using stock exchange to share the risk with counterparties. While targets have incomplete information on the value of bidders share and they are risk-adverse, they would insure themselves by accepting cash offer rather than stock exchange. Thus, the relative size between the bidder and target influence the percentage of cash use in the offer. Fuller et al. (2002) considered the stock
performance is associated with the relative size. Cheng and Leung (2004) also added this variable into regression when analyzing the takeover transactions in Hong Kong. According to Vladimirov (2014), lnTA (the logarithm of bidder’s total assets) which represents the size of bidder is a proxy for its access to competitive capital market. As stated above, the ability to raise funds in competitive capital market influence the bid price offered in M&A, as such influence the stock return of the bidder. In the regression testing Hypothesis 2, the variables of interest are Premium, Debt (dummy) and Cash (dummy). In the regression testing
Hypothesis 3, there are two more variable of interest: Premium*Debt and Premium* Cash.
Other variables such as relative size, percentage of cash payment and the total assets of bidder serve as control variables.
The regression model is built as below:
𝐶𝐴𝑅𝑖 = 𝛽0+ 𝛽1𝑃𝑟𝑒𝑚𝑖𝑢𝑚𝑖+ 𝛽2𝑃𝑟𝑒𝑚𝑖𝑢𝑚 ∗ 𝐶𝑎𝑠ℎ𝑖+ 𝛽3𝑃𝑟𝑒𝑚𝑖𝑢𝑚 ∗ 𝐷𝑒𝑏𝑡𝑖+ 𝛽4𝑅𝑒𝑙𝑠𝑖𝑧𝑒𝑖 + 𝛽5𝑃𝑐𝑡_𝑆𝑡𝑜𝑐𝑘𝑖 + 𝛽6𝑙𝑛𝑇𝐴𝑖 + 𝛽7𝐶𝑎𝑠ℎ𝑖 + 𝛽8𝐷𝑒𝑏𝑡𝑖 + 𝑒𝑖
19 where,
CAR is the three-day cumulative abnormal return of bidding firms; Premium is the ratio of the bid price to the market price of target 4 weeks before the announcement; Cash is a dummy variable. Cash=1 if a transaction has internal cash financing; Debt is also a dummy variable. Debt=1 if a transaction has debt financing; Relsize is the ratio of market value of the bidder to the target; Pct_cash is the portion of cash payment involved in the M&A; lnTA is the logarithm of bidder’s total assets. Premium*Cash and Premium* Debt are applied to examine the effect of premium on CAR taking the financing source into account. That is, if there is no difference in the effect of premium on CAR among bidders, 𝛽2 and 𝛽3 will be
equal to zero. According the Hypothesis 3, 𝛽1 is supposed to be negative, which indicated
that negative impact of high premium on equity-financed bidders’ stock. 𝛽2 and 𝛽3 are
supposed to be positive, which indicates that the weakening negative or even positive effect of premium on CAR when bidders using internal cash reserves or debt financing.
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4. Data and descriptive statistics
The sample includes the acquisitions announced between 1978 and 2013 satisfying the following set of conditions. First, bidder and target are both public American firms. Second, following Schlingemamn (2004), bidders and targets with Standard Industrial Classification (SIC) codes within the ranges 6000–6999 (financial firms) and 4900–4999 (regulated utility firms) are excluded from the sample. Third, exclude acquisitions without information about the method of payment and the source of funds. The method of payment includes all-cash payment, all-stock payment and the combination of cash and stock payment. The sources of financing include debt financing, equity financing and cash financing. Furthermore, debt financing contains the funds from borrowings, debt securities, foreign lenders, junk bonds, line of credit, and mezzanine loans. Equity financing contains the funds from common stock offerings, preferred stock offerings or rights offerings. Cash financing refers to the internal corporate fund. All information can be collected from Thomson One database and CRSP.
After the initial screening, there are 4490 observations left in the sample. The distribution of acquisitions can be seen from Table 1 below, there are three clusters of mergers and
acquisitions taking place in 1980s, 1990s and during the 2007-2008 financial crisis,
respectively. In 1980s, the methods of payment used in the mergers and acquisitions mainly consist of all-cash payment. 54.52% of the deals were paid with cash only, while 27.40% and 18.08% of the deals are paid with stock and a combination of cash and stocks, respectively. The preference of payment method changes significantly in 1990s. Almost half (49.75%) of mergers and acquisitions are paid with stock only. Only 29.97% of the deals are paid with cash only, decreasing by 45% compared to last decade. The other 20.28% of the deals are finalized by hybrid payment. According to Rhodes-Kropf and Viswanathan (2004), it is the
21 booming stock market in this period gives rise to this change. However, in the financial crisis period, cash payment overwhelms the other two payment methods as: all-cash payment account for 76.99% of all the mergers and acquisitions. Based on the work performed on the entire sample, most of deals are financed by debt (1416) and cash (1612). Only 116 deals are financed by equity. Internal cash-financing reach an unprecedented peak during financial crisis--- 71.15% of bidders use cash reserves to fund the deal. Given the chaos of macro-economy during crisis period, it should not come as a surprise that the uncertainty of financial market increases, which resulted with higher market risks and thus higher required return of risks. The rising cost of capital cause the shrink of corporate net present value, which used to be collateral and help to relieve adverse selection and moral hazard in
financing process. In other words, facing the economic downturn in financial crisis, problems caused by information asymmetry are exacerbated, which makes external financing are more difficult and expensive. As a result, more bidders choose to use internal cash reserves in this period. This information verifies the first hypothesis of this thesis: in the case of severe information asymmetry, mergers and acquisitions financed by internal cash are more than those financed by debt, and fewest mergers and acquisitions are financed by equity issuance.
INSERT TABLE 1 ABOUT HERE
Table 2 presents detailed information about the source of financing. As can be seen from the table, most of debt-financed deals raise money from borrowings (743) and line of credit (654). The peaks to finance through borrowing and line of credit are consistent with the merger waves: in late 1980s, in 1990s and in 2005-2008: 318 out of 743 borrowing-financed acquisitions and 514 out of 645 line of credit-financed acquisitions happen during one of
22 these three periods. Issuing debt to raise cash are uses more commonly in late 1980s and late 1990s, compared to other periods. 72, 55, 28 deals are financed by bridge loans, foreign funds and junk bonds, respectively. Only 4 deals are financed by mezzanine loans during the sample period, this is because of the extreme information-sensitivity and high interest rate of mezzanine loan. As for the equity-financed M&A transactions, 62.05% of the acquisitions are financed through common stock issue, and other 34.34% are financed through preferred stock issue. Only 6 deals are financed through right issue.
INSERT TABLE 2 ABOUT HERE
Table 3 presents the statistics of premium and the number of deals with different financing sources in two sub-samples: 25% high premium group and 25% low premium group. The premium is defined as the ratio of stock price paid by bidder to the target to the stock price of target four weeks prior to the acquisition. As shown in Table 3, the average premium in high premium group is 2.44, approximately three times the average of the low premium group, which is 0.88. In addition, the sources of financing are different in two premium group. In high premium group, debt financing are more common than cash financing. The number of deals financed through debt –(277),cash – (225) and equity –(17). However, in low premium group, there are more cash-financed deals than debt-financed deals. There are 310 deals have cash-financing employed, 21 deals have equity-financing employed and 193 deals have debt-financing employed.
23
5. Empirical Results
5.1. Long-term Event Study
Table 4 presents the estimation of calendar-time portfolio model. The first column presents the intercept together with other three variables in Fama-French three-factor model. The intercept is the variable of interest --- abnormal return. The second column contains the estimated coefficients. And the third column lists the OLS t-statistics indicating the significance of the estimation. R-square, adjusted R-square and the F-statistics are presented at the bottom of every panel.
As shown in Table 4 Panel A, bidding firms financing through equity underperform. Although this underperformance is not significant in the second year following the M&A, in the first year after the announcement, the average daily abnormal returns of bidding firms with equity financing is -0.04% and it is significant at 10% level (t=-1.30).
As can be seen from Table 4 Panel B, bidders financing through internal cash reserves exhibit positive daily average abnormal return in the long run. The daily abnormal return in 1 year following the M&A announcement is 0.03%, significant at 1% level; and the abnormal return in 2 years following the M&A announcement is 0.02%, also significant at 1% level.
Table 4 Panel C presents the long term stock performance of bidding firms using debt
financing in M&A. The daily abnormal returns shown are positive in both two periods: 0.02% and 0.02%, and they are both significant. The long-term event study preliminarily verifies
Hypothesis 2: Bidders financing their M&A bids through cash and debt perform better than
those financing through equity issuance.
24
5.2. Short-term Event Study
Table 5 presents results of the average daily abnormal return and cumulative abnormal return of bidding firms’ stocks around the initial announcement. The first column presents the days relative to the announcement day, in terms of the trading days. The second column presents the number of observations in equity-financing group. The third column presents the daily average abnormal return for each event day for the bidders using equity financing. The forth column presents the t-statistics corresponding to the average abnormal return. Columns (5), (6), (7) depict the number of observations, average abnormal return, and t-statistics for bidders using internal cash reserves to finance M&A. Columns (8), (9), (10) present the number of observations, average abnormal return, and t-statistics for bidders using debt-financing. As shown in Table 5, bidding firms issuing new equity to finance their cash bids experience a slightly positive rise in their stock prices at announcement. The average abnormal return at announcement is slightly positive (0.78%) and significant at 1% level. The 3-day cumulative abnormal return is 1.27%, which is significant at 5% level. The positive announcement effect is much more obvious on bidding firms that use internal reserves to finance their bids. The portfolio abnormal return at announcement is 1.40% with t-statistics equals to 18.069, which is significant at 1% level. In addition, the portfolio
abnormal returns on the first day after the announcement and on the second day after the announcement are also significantly positive: 1.13% (with t=14.573) and 0.22% (with
t=2.780). As shown in Panel B, for internal cash-financing bidders, the cumulative abnormal returns for all of three event windows are positive and significant at 1% level. The 3-day (between day=-1 and day=1) cumulative abnormal return is 2.50%, the 11-day (between day=-5 and day=5) cumulative abnormal return is 2.58% and the 21-day (between day=-10
25 and day=10) cumulative abnormal return is 2.02%. Similar to bidding firms using internal cash reserves to finance their bids, in general, bidding firms using debt financing also experience an increase in their stock prices. The portfolio average abnormal return at announcement is 1.10% (t=13.304) and the one-day after announcement average abnormal return is 1.06 (t=12.805), both of which are significant at 1% level. The 3-day cumulative abnormal return is 2.27%, the 11-day cumulative abnormal return is 2.10% and the 21-day cumulative abnormal return is 1.62%.
INSERT TABLE 5 ABOUT HERE
Table 6 presents the abnormal stock returns of different premium groups. Panel A depicts the stock returns of bidders who issue new equity to raise cash for M&A payment. The first column presents the days relative to the announcement day, in terms of the trading days. Columns (2), (3), (4) present the number of observations, average abnormal return, and t-statistics for bidders who pay the highest 25% premium, and columns (5), (6), (7) present the similar information but for bidders who pay the lowest 25% premium. Panel B and Panel C have the same structure as Panel A. The only difference is that Panel B provides
information of cash-financing bidders and Panel C provides information of debt-financing bidders. Among bidders using equity financing and pay lowest 25% premium, the average abnormal return is 2.22%, which is significantly different from zero at 1% level. However among bidders using equity financing but pay highest 25% premium, the average abnormal return is insignificantly different from zero (t=-0.587). That is, among bidders issuing new equity to raise cash, those who pay low premia outperform the market while those who pay high premia just gain “normal return”. The announcement-date average abnormal return of bidders’ stocks in low premium group are 2.66% (for bidders using internal cash) and 2.10%
26 (for bidders financing with debt), higher than those in high premium group: 1.26% (for bidders using internal cash) and 0.71% (for bidders financing with debt).
As for the cumulative abnormal return of equity financing bidder, either in high premium group or in low premium group, the cumulative abnormal return is still insignificantly
different from zero, which means bidder use equity financing do not outperform the market no matter how much premium they pay. In contrast to bidder financing M&A through equity issuance, the three-day cumulative abnormal return of bidders using debt financing confirm the statement that: the lower premia bidders pay, the better stock returns they experience. The three-day cumulative abnormal return of bidders who use debt financing is 1.87% in high premium group and 3.55% in low premium group, increasing 95.65%. And the eleven-day cumulative abnormal return also sees a significant increase (87.30%) when bidders pay low premia. However, this “better stock returns” is not well proved within bidders who use internal cash reserves. Although the three-day cumulative abnormal return of bidders who use internal cash is 2.86% in high premium group and 3.77% in low premium group,
increasing 31.82%, the eleven-day cumulative abnormal return and twenty-one-day
cumulative abnormal return see an opposite trend: 11-day cumulative abnormal return and 21-day cumulative abnormal return increase when bidders pay high premia. The eleven-day cumulative abnormal return and twenty-one-day cumulative abnormal return in high premium group are 3.49% and 2.52%, while these two cumulative abnormal returns are 3.10% and 1.79% in low premium group. This phenomenon can be explained by free cash flow theory together with information asymmetry theory, and it will be further examined by cross-sectional regression.
27
5.3. Cross-sectional Analysis
Table 7 report results of different versions of regression model. In all these regressions, bidders using equity issuance as source of funds are deemed to be benchmark group and the dependent variable is 3-day cumulative abnormal return: CAR(-1,1). In regression 1, only variables of interest: Premium, Cash and Debt are included. It shows that the intercept is insignificantly different from zero, that is, the bidding firms financing their bids with equity do not outperform the market. Cash and Debt are both have significantly positive
coefficients, which means bidding firms using internal cash reserves and issuing debt experience positive abnormal stock returns. The negative coefficient of Premium proves that the higher premium bidder pays the lower return they will obtain. From regression 2 to regression 4, one more control variable is added in each regression. And in regression 5, year fixed effects are considered. However, as shown in Regression 5, the abnormal return of cash-financed bidders ia not significantly different from zero. That is, the bidders
financing their cash payment with internal cash reserves obtain only “normal” market returns. Only debt-financed bidders have positive abnormal returns as the coefficient is significantly larger than zero. As shown in Table 6, the effect of premium on CAR varies among bidders using different source of financing, thus in Regression 6, the interaction terms of premium and financing source: Premium*Cash and Premium*Debt are added. Given the insignificant intercept, the difference on CAR between cash group and benchmark group is (-0.053+0.036*Premium), which means if the premium is not high enough, bidders financing with internal cash gain worse stock returns than those who use equity-financing. As for bidding firms that use debt-financing, the coefficient of interaction term is not significant, which means the effect of premium on debt-financing bidders’ CAR is not
28 significantly different from that of equity-financing bidders. But as the coefficient of Debt is 0.038 and it is significant, it means that overall bidders who borrow to finance their M&A obtain better stock returns than those who issue equity to raise money.
The coefficients for Cash and Cash-Premium interaction term are in accord with the information provided in Table 6: 11-day CAR and 21-day CAR are lower in low premium group than in high premium group. This seemingly abnormal phenomenon can be explained by applying free cash flow theory and information asymmetry. Jensen (1986) defined free cash flow as “free cash flow is cash flow in excess of that required to fund all projects that have positive net present values when discounted at the relevant cost of capital.(p.323)” He also stated the agency problem will be especially severe when there is substantial free cash flow kept within company. As a bidder has plenty of free cash flow within the company, the risk of overinvestment increases. As discussed above, for bidding firms, managers use cash to finalize their deals are aware of the value of the merging firms, if they are not willing to pay high premia, it can be reasonably infer that managers do not have high valuation for the synergy of merging firms. That is to say, the low-premium mergers or acquisitions are not profitable and they are conducted simply out of managers’ “empire building motives”. Instead, paying high premia is a positive signal indicating that the valuation for merging firm is high, thus bidders will experience a rise in their stock prices.
29
6. Robustness Test
To robust-rest the results from cross-sectional regression, different event windows and different specification of CAR is hereby employed. Firstly, run regressions using 11-day CAR and 21-day CAR as dependent variable, respectively. When running regression, author found that adding variable lnTA significantly decrease the goodness of fit. Thus in these two
regressions, variable lnTA is dropped. CAR and premium are winsorized at 1% level. The regression results are presented in Table 8. Empirical evidence again confirms that the effect of premium on CAR differs across bidders using different source of financing. For bidder using internal cash reserves to pay for the target, the effect premium on 11-day CAR +0.020, while for bidder using debt-financing and equity-financing, the effect is -0.015 and -0.056, respectively. The effect of premium on 21-day CAR is-0.024 for equity-financing bidders and is +0.041 for cash-financing bidders. All these results prove that, for bidders using internal cash reserves to finalize M&A transaction, high premium is no longer necessarily indicating the overpayment, but instead signaling a high valuation of merging firms, as such bring better stock returns to bidders.
Secondly, comparison period mean adjusted returns are alternatively used to calculate CAR. The abnormal return for one firm is defined as:
𝐴𝑖,𝑡 = 𝑅𝑖,𝑡− 𝑅 𝑖
where 𝑅 is the arithmetic mean return over the estimation period (between 301 and 46 𝑖
days prior to the M&A announcement). And analogously, average abnormal return and cumulative abnormal return are defined as:
30 𝐴𝐴𝑅𝑡 = 1 𝑁 𝐴𝑅𝑖,𝑡 𝑁 𝑖=1 and 𝐶𝐴𝑅 𝑡1, 𝑡2 = 𝐴𝐴𝑅𝑡 𝑡2 𝑡1
respectively. CAR and premium are winsorized at 1% level. The results are presented in Table 9. In Regression 1, no interaction term is taken into consideration. In this case, premium has significant negative impact on CAR. Bidders financing with debt significantly outperform the market, while the CARs of bidders financing with cash and equity are insignificantly different from zero. Taking the interaction of premium and financing source into account, the CAR for equity-financing bidders is still insignificant. The total difference on CAR of internal cash financing on bidder’s CAR is -0.054 +0.018*Premium, both
coefficients are significant. To illustrate, when premium is high (larger than 3), the CAR of cash-financing bidders is significantly higher than the benchmark ---equity-financing bidders; and when premium is low, their CAR is lower than equity-financing bidder. This robustness test is coincident with the primary results. The effect of debt financing on bidder’s CAR is 0.003-0.011*Premium. But they are not significant. This insignificance is not necessarily denying the conclusion drawn before. According to Kothari and Warner (2008), across various model for estimating expected return, the bias or precision of expected return measures differ. As such the properties of abnormal return and the corresponding cross-sectional analysis are affected. To ensure the validity of benchmark model, a joint test of whether abnormal return is zero and of whether the underlying model for expected return
31 estimation is required. There are some sophisticated tools, such as stimulation procedure can be applied. But they are out of the scope of this thesis.
32
7. Conclusion
Whereas previous researches studying bidder’s stock performance focus more on the method of payment and the premium, this thesis contributes to the extensive list of literatures by including source of financing as well. This thesis investigates the effect of bidder’s source of financing in American mergers and acquisitions. The results of this thesis reveal a differential-return relationship across different source of financing for bidding firms announcing M&A.
The results on equity-financing bidding firms show that their stock prices do not abnormally increase reacting to the M&A announcement. The evidence is supported by long-term event study, the short-term event study, as well as cross-sectional regression. This finding is consistent with the signaling theory, which implies that equity issuance is a negative signal to market; even if the deal is finalize through cash payment, shareholders cannot experience the rise in stock prices. For bidding firms using debt-financing and internal cash reserves, they receive better stock returns compared to equity-financing bidders. Firstly, as can be seen from event study results, the cumulative abnormal returns for debt-financing bidders and cash-financing bidders are significantly positive, no matter in short term or in long term. Secondly, when running cross-sectional regression, the significant coefficients of source of financing dummies also confirm this argument. As using internal cash or debt financing conveys the information regarding the fair valuation of bidder or the profitability of merging firms, stock price increase in these two situations.
As premium itself is influenced by the source of financing, the effect of source of financing is further examined taking premium and source-of-financing interaction terms into
33 among bidders. As premium is one of the determinant for bidders’ CAR, thus whether
bidders’ stocks outperform the market depends not only on the financing sources but also on the premia paid by bidders using different sources of financing. In contrast to equity- or debt-financing bidders, for cash-financing bidders, premium positively affects bidders’ CAR. There is a critical premium value, if bidders pay higher premia than this value, they obtain better stock returns than the benchmark group, and otherwise they perform worse. This finding can be explained by free cash flow theory. And this result passes the robustness tests applying different event windows and alternative specification of CAR.
34
8. References
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36
9. Appendix
Table 1
Year Distribution of M&A Transactions
*One transaction can be financed by more than one source. Number of M&A Number of all-cash payment deals Number of all-stock payment deals Number of hybrid payment deals Number of debt-financing deals Number of equity-financing deals Number of cash-financing deals 2013 128 109 10 9 41 1 110 2012 90 66 10 14 35 2 64 2011 108 82 14 12 39 3 71 2010 64 35 22 7 21 2 36 2009 96 47 33 16 17 2 52 2008 190 154 23 13 44 4 151 2007 162 117 26 19 56 1 108 2006 101 61 26 14 51 2 43 2005 98 43 40 15 31 2 42 2004 102 42 42 18 20 0 42 2003 93 31 50 12 15 0 27 2002 114 52 46 16 33 2 46 2001 199 55 105 39 37 3 52 2000 259 55 150 54 59 5 55 1999 309 90 159 60 75 1 81 1998 334 94 163 77 101 7 65 1997 293 72 140 81 90 3 53 1996 219 60 108 51 66 2 46 1995 220 62 124 34 65 7 42 1994 187 65 101 21 52 8 41 1993 120 41 55 24 28 11 34 1992 88 33 43 12 20 0 27 1991 102 25 50 27 24 3 29 1990 110 52 43 15 34 4 49 1989 172 100 48 24 93 14 68 1988 154 89 37 28 80 9 60 1987 129 75 28 26 70 3 46 1986 135 78 28 29 77 11 47 1985 92 37 40 15 40 4 25 1984 13 1 8 4 2 0 0 1983 0 0 0 0 0 0 0 1982 0 0 0 0 0 0 0 1981 1 0 1 0 0 0 0 1980 1 0 1 0 0 0 0 1979 1 0 1 0 0 0 0 1978 6 0 6 0 0 0 0 Total 4490 1923 1781 786 1416 116 1612
37
Table 2 Year Distribution of M&A Financing sources
Panel A: Debt-Financed M&A Transactions Borrowing Bridge
Loan
Debt Issue
Foreign
Funds Junk Bond
Line of Credit Mezzanin e Loans 2013 19 4 5 3 0 15 1 2012 17 4 4 4 0 23 0 2011 23 4 4 3 0 18 1 2010 11 4 2 0 0 7 0 2009 12 1 2 1 0 8 0 2008 30 3 1 2 0 21 0 2007 34 4 4 4 0 22 0 2006 31 4 6 2 0 19 0 2005 18 1 3 3 0 15 0 2004 8 1 1 2 0 8 0 2003 7 0 1 0 0 9 0 2002 12 3 6 0 0 15 0 2001 22 0 5 0 0 6 0 2000 31 2 10 0 0 22 0 1999 25 2 7 0 0 44 0 1998 53 3 14 0 1 36 0 1997 44 1 10 0 0 42 0 1996 26 0 9 0 0 33 0 1995 32 1 12 0 1 28 0 1994 23 0 7 0 0 24 0 1993 15 3 9 0 1 11 0 1992 12 1 3 0 0 10 0 1991 4 0 4 0 0 15 0 1990 13 0 7 1 0 19 0 1989 59 7 25 9 6 36 2 1988 56 11 20 7 8 32 0 1987 42 6 16 3 5 43 0 1986 41 2 23 8 3 45 0 1985 21 0 11 3 3 19 0 1984 2 0 0 0 0 0 0 Total 743 72 231 55 28 645 4
38
Table 2—Continued
Panel B: Equity-Financed M&A Transactions
Common Stock Issue Preferred Stock Issue Rights Issue
2013 1 0 0 2012 2 0 0 2011 3 0 1 2010 2 0 0 2009 2 0 1 2008 3 0 1 2007 1 1 0 2006 2 0 0 2005 1 2 0 2004 0 0 0 2003 0 0 0 2002 2 1 0 2001 3 1 0 2000 5 2 0 1999 1 1 0 1998 7 2 1 1997 3 1 0 1996 2 1 0 1995 7 1 0 1994 8 2 0 1993 11 6 1 1992 0 0 0 1991 3 3 0 1990 4 3 0 1989 10 10 1 1988 4 9 0 1987 1 3 0 1986 11 5 0 1985 4 3 0 Total 103 57 6
39
Table 3 Statistics and deal information of two premium groups
The total sample consists of 1416 American public bidders that acquired public targets between 1970 and 2013. The M&A premium is defined as the ratio of stock price per share paid by acquirer to the target to the stock price of target four weeks prior to the acquisition. The 25% high premium group comprises firms which pay the highest 25% premium, and the 25% low premium group comprises firms which pay the lowest 25% premium. The statistics contain the average, minimum and maximum. The deal information contains the number of deals of different sources of financing.
Table 4 Fama-French Calendar-Time Portfolio Regression (Value Weighted Index)
This sample consists of 4490 American public bidders that acquired public target between 1970 and 2013. Calendar-time portfolio regression is performed in different financing source groups and the results are presented in Panel A, B and C. The monthly abnormal return is measured by the intercept (𝛼𝑖) in
Fama-French three-factor model:
𝑅𝑝,𝑡− 𝑅𝑓,𝑡 = 𝛼𝑖+ 𝛽𝑖(𝑅𝑚,𝑡− 𝑅𝑓,𝑡) + 𝑠𝑖𝑆𝑀𝐵𝑡+ ℎ𝑖𝐻𝑀𝐿𝑡+ 𝜖𝑝,𝑡
where 𝑅𝑝,𝑡 is the monthly return of the calendar portfolio which is formed by securities of event months; 𝑅𝑓,𝑡 is the monthly risk free return; 𝑅𝑚 ,𝑡 is the
monthly return of the value-weighted market index; 𝑆𝑀𝐵𝑡 is the weighted average return on small market-capitalization portfolios minus the
value-weighted average return on three large market-capitalization portfolios; 𝐻𝑀𝐿𝑡 is the value-weighted average return on two high book-to-market equity
portfolios minus the value-weighted average return on two low book-to-market equity portfolios; 𝜖𝑝,𝑡 is the error term.
Average Premium Minimal Premium Maximal Premium Number of Debt Financing Number of Equity Financing Number of Cash Financing All sample 1.44 0.00 75.00 1416 116 1612 25% High premium 2.24 1.59 75.00 277 17 225 25% Low Premium 0.88 0.00 1.08 193 21 310
40
Panel A: The long term stock performance of equity financing bidders Average (0-360 days after
announcement)
OLS t-statistic Average (0-720 days after announcement)
OLS t-statistic
Intercept (Abnormal Return) -0.0004* -1.30 -0.0002 -0.70
(𝑅𝑚,𝑡− 𝑅𝑓,𝑡) 0.9101*** 34.59 0.9244*** 43.94 𝑆𝑀𝐵𝑡 0.5789*** 11.52 0.5128*** 12.71 𝐻𝑀𝐿𝑡 0.3718*** 7.06 0.3016*** 7.03 R-squared 16.59% 22.21% Adjusted R-squared 16.55% 22.17% F-statistic 408.49*** 84.17***
Panel B: The long term stock performance of cash financing bidders Average (0-360 days after
announcement)
OLS t-statistic Average (0-720 days after announcement)
OLS t-statistic
Intercept (Abnormal Return) 0.0004*** 5.88 0.0003*** 5.35
(𝑅𝑚,𝑡− 𝑅𝑓,𝑡) 0.9111*** 137.32 0.9413*** 170.22 𝑆𝑀𝐵𝑡 0.4365*** 34.36 0.4539*** 42.99 𝐻𝑀𝐿𝑡 0.0250* 1.85 0.0579*** 5.15 R-squared 73.29% 80.74% Adjusted R-squared 73.28% 80.73% F-statistic 6655.4*** 10164***
Panel C: The long term stock performance of debt financing bidders Average (0-360 days after
announcement)
OLS t-statistic Average (0-720 days after announcement)
OLS t-statistic
Intercept (Abnormal Return) 0.0002*** 2.59 0.0002** 2.04
(𝑅𝑚,𝑡− 𝑅𝑓,𝑡) 0.9537*** 120.76 0.9885*** 139.53 𝑆𝑀𝐵𝑡 0.4796*** 31.82 0.4892*** 36.26 𝐻𝑀𝐿𝑡 0.1993*** 12.05 0.2749*** 19.10 R-squared 67.04% 72.91% Adjusted R-squared 67.03% 72.90% F-statistic 5019.1*** 6641.7***
41
Table 5 Average Abnormal Returns and Cumulative Abnormal Returns in different source of financing groups
This sample consists of 4490 American public bidders that acquired public target between 1970 and 2013. There are 98 deals with equity-financing involved, 1233 deals with debt-financing involved and 1410 deals are financed with internal cash reserves. The benchmark return is estimated by Fama-French time-series model and the average daily abnormal returns (AAR) is defined as
𝐴𝐴𝑅𝑡 = 1
𝑁 (𝑅𝑖,𝑡− (𝛼 + 𝛽𝑖 𝑅𝑖 𝑚,𝑡+ 𝑠 𝑆𝑀𝐵𝑖 𝑡+ ℎ 𝐻𝑀𝐿𝑖 𝑡)) 𝑁
𝑖=1 ,
where 𝑅𝑖,𝑡is the return of the common stock of the 𝑖𝑡ℎ firm on date t; 𝑅𝑚,𝑡 is the return of a market index on day t; 𝑆𝑀𝐵𝑡 is the value-weighted average
return on small market-capitalization portfolios minus the value-weighted average return on three large market-capitalization portfolios; 𝐻𝑀𝐿𝑡 is the
value-weighted average return on two high book-to-market equity portfolios minus the value-weighted average return on two low book-to-market equity portfolios; ; 𝜖𝑖,𝑡 is the error term. The estimation window is between 301 and 46 days prior to the M&A announcement. And the cumulative abnormal
return is defined as:
𝐶𝐴𝑅 𝑡1, 𝑡2 = 𝐴𝐴𝑅𝑡2 𝑡
𝑡1 ,
42
Panel A: Daily Average Abnormal Returns (AAR) in Different Financing Groups
M&A with equity-financing involved M&A with cash-financing involved M&A with debt-financing involved
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Day N AAR(%) t-statistic N AAR(%) t-statistic N AAR(%) t-statistic
-10 98 -0.06 -0.193 1410 -0.11* -1.432 1233 -0.03 -0.416 -9 98 0.22 0.661 1410 -0.14** -1.860 1233 -0.07 -0.904 -8 98 -0.08 -0.246 1410 -0.06 -0.837 1233 0.02 0.217 -7 98 0.10 0.300 1410 -0.02 -0.197 1233 -0.02 -0.242 -6 98 -0.13 -0.377 1410 -0.12* -0.541 1233 -0.12* -1.393 -5 98 0.17 0.492 1410 0.08 0.993 1233 -0.01 -0.143 -4 98 -0.04 -0.113 1410 -0.06 -0.829 1233 -0.01 -0.135 -3 98 0.44 1.317 1410 -0.12* -1.610 1233 0.09 1.059 -2 98 -0.13 -0.394 1410 -0.19*** -2.401 1233 -0.11* -1.364 -1 98 0.28 0.833 1410 -0.03 -0.323 1232 0.11* 1.306 0 98 0.78*** 2.337 1407 1.40*** 18.069 1231 1.10*** 13.304 +1 97 0.21 0.631 1410 1.13*** 14.573 1233 1.06*** 12.805 +2 98 -0.33 -0.995 1410 0.22*** 2.780 1233 -0.05 -0.554 +3 98 -0.46* -1.385 1410 -0.02 -0.264 1233 -0.08 -0.927 +4 98 -0.41 -1.208 1410 0.13* 1.642 1233 0.02 0.280 +5 98 0.41 1.219 1410 0.06 0.761 1233 -0.02 -0.218 +6 98 -0.64** -1.896 1410 0.03 0.436 1233 -0.15** -1.817 +7 98 -0.32 -0.952 1410 -0.06 -0.749 1233 0.02 0.247 +8 98 -0.06 -0.178 1410 0.08 1.005 1233 -0.02 -0.295 +9 98 0.35 1.053 1410 -0.03 -0.411 1233 -0.05 -0.602 +10 98 -0.46* -1.371 1410 -0.13** -1.736 1233 -0.05 -0.607
Panel B: Cumulative Abnormal Returns (CAR) in Different Financing Groups
M&A with equity-financing involved M&A with cash-financing involved M&A with debt-financing involved
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Event Window N CAR(%) t-statistic N CAR(%) t-statistic N CAR(%) t-statistic
(-1,1) 98 1.27** 2.181 1410 2.50*** 18.637 1233 2.27*** 15.815
(-5,5) 98 0.91 0.817 1410 2.58*** 10.056 1233 2.10*** 7.655
43 *, **, *** denote statistical significance at 10%, 5% and 1% levels, respectively.
Table 6 Average Abnormal Returns and Cumulative Abnormal Returns in different premium groups
This sample consists of 4490 American public bidders that acquired public target between 1970 and 2013. The 25% high premium group comprises firms which pay the highest 25% premium. In high premium groups, 12 firms use equity financing, 203 firms use internal cash reserves, and 236 firms use debt financing. The 25% low premium group comprises firms which pay the lowest 25% premium. In low premium group, 17 firms use equity financing, 282 firms use internal cash reserves and 177 firms use debt financing. The benchmark return is estimated by Fama-French time-series model and the average daily abnormal returns (AAR) is defined as
𝐴𝐴𝑅𝑡 =𝑁1 𝑁𝑖=1(𝑅𝑖,𝑡− (𝛼 + 𝛽𝑖 𝑅𝑖 𝑚,𝑡+ 𝑠 𝑆𝑀𝐵𝑖 𝑡+ ℎ 𝐻𝑀𝐿𝑖 𝑡)),
where 𝑅𝑖,𝑡is the return of the common stock of the 𝑖𝑡ℎ firm on date t; 𝑅𝑚,𝑡 is the return of a market index on day t; 𝑆𝑀𝐵𝑡 is the value-weighted average
return on small market-capitalization portfolios minus the value-weighted average return on three large market-capitalization portfolios; 𝐻𝑀𝐿𝑡 is the
value-weighted average return on two high book-to-market equity portfolios minus the value-weighted average return on two low book-to-market equity portfolios; ; 𝜖𝑖,𝑡 is the error term. The estimation window is between 301 and 46 days prior to the M&A announcement. And the cumulative abnormal
return is defined as:
𝐶𝐴𝑅 𝑡1, 𝑡2 = 𝐴𝐴𝑅𝑡2 𝑡
𝑡1 ,
44
Table 6 Average Abnormal Returns and Cumulative Abnormal Returns in different premium groups
*, **, *** denote statistical significance at 10%, 5% and 1% levels, respectively.
Panel A: Daily Average Abnormal Returns (AAR) of Bidders with Equity Financing
25% High Premium 25% Low Premium
(1) (2) (3) (4) (5) (6) (7)
Day N AAR(%) t-statistic N AAR(%) t-statistic
-10 12 0.22 0.149 17 -0.36 -0.486 -9 12 0.65 0.442 17 -0.33 -0.436 -8 12 -1.09 -0.740 17 0.31 0.420 -7 12 0.23 0.157 17 0.09 0.114 -6 12 -0.95 -0.643 17 -0.67 -0.897 -5 12 -0.99 -0.671 17 -0.10 -0.131 -4 12 -0.17 -0.117 17 -0.16 -0.219 -3 12 0.45 0.308 17 -0.12 -0.157 -2 12 -0.70 -0.475 17 -0.85 -1.132 -1 12 -1.50 -1.017 17 0.10 0.136 0 12 -0.87 -0.587 17 2.22*** 2.977 +1 12 0.31 0.211 17 -1.29** -1.728 +2 12 -0.22 -0.148 17 0.23 0.309 +3 12 -0.52 -0.354 17 -1.16* -1.552* +4 12 0.10 0.065 17 -0.44 -0.592 +5 12 -0.60 -0.404 17 0.87 1.161 +6 12 -0.84 -0.567 17 -0.58 -0.780 +7 12 -0.30 -0.200 17 0.09 0.114 +8 12 -1.46 -0.986 17 -0.23 -0.313 +9 12 0.12 0.083 17 0.71 0.955 +10 12 -0.26 -0.178 17 0.93 1.250
25% High premium 25% Low Premium
(1) (2) (3) (4) (5) (6) (7)
Event Window
N CAR(%) t-statistic N CAR(%) t-statistic
(-1,1) 12 -2.05 -0.804 17 0.90 0.699
(-5,5) 12 -4.70 -0.961 17 -0.82 -0.332
45
Table 6 Average Abnormal Returns and Cumulative Abnormal Returns in different premium groups
Continued
*, **, *** denote statistical significance at 10%, 5% and 1% levels, respectively.
Panel B: Daily Average Abnormal Returns (AAR) of Bidders with Cash Financing
25% High Premium 25% Low Premium
(1) (2) (3) (4) (5) (6) (7)
Day N AAR(%) t-statistic N AAR(%) t-statistic
-10 203 -0.03 -0.153 282 -0.21 -0.633 -9 203 -0.31* -1.381 282 -0.54*** -3.080 -8 203 0.31* 1.382 282 -0.17 -0.979 -7 203 0.33* 1.466 282 -0.52*** -2.915 -6 203 -0.20 -0.875 282 -0.26 -1.443 -5 203 0.28 1.251 282 0.08 0.458 -4 203 0.32* 1.447 282 -0.68*** -3.835 -3 203 0.00 0.016 282 -0.43*** -2.437 -2 203 0.02 0.109 282 -0.34** -1.902 -1 203 0.05 0.228 282 -0.20 -1.108 0 203 1.26*** 5.620 282 2.66*** 15.035 +1 203 1.55*** 6.898 282 1.31 7.420 +2 203 0.23 1.066 282 0.02 0.130 +3 203 -0.18 -0.804 282 0.24* 1.368 +4 203 -0.13 -0.591 282 0.30** 1.690 +5 203 0.08 0.346 282 0.13 0.727 +6 203 -0.10 -0.448 282 0.11 0.640 +7 203 -0.16 -0.696 282 0.34** 1.899 +8 203 -0.13 -0.591 282 0.10 0.565 +9 203 -0.31* -1.395 282 0.07 0.390 +10 203 -0.37* -1.629 282 -0.32** -1.821
25% High premium 25% Low Premium
(1) (2) (3) (4) (5) (6) (7)
Event Window
N CAR(%) t-statistic N CAR(%) t-statistic
(-1,1) 203 2.86*** 7.359 282 3.77*** 12.325
(-5,5) 203 3.49*** 4.681 282 3.10*** 5.291
