Abstract
Purpose
This paper aims to address the question: What is the distribution of value (in pounds) created in a sample of domestic takeovers in the United Kingdom from 2013 to 2020 among acquirer and target stockholders?
Design/methodology/approach
The author employs a traditional event study methodology to calculate the percentage excess returns of companies on the announcement date. These returns are then converted into pound-denominated excess returns using the companies' market capitalizations. This allows the author to estimate the synergies of the mergers and acquisitions (M&As) and how they are allocated between acquirers and targets. This innovative transformation from percentage to pound excess returns establishes a new ratio methodology for addressing the paper's objective.
Findings
This paper reveals that in UK takeovers, 40 percent of the synergies in pounds are allocated to the stockholders of acquiring companies, while 60 percent go to the stockholders of target companies. In other words, acquirers retain a significant portion—more than half—of the synergies generated in these domestic deals. This original finding is statistically significant at the one percent level and strongly contradicts the hypothesis that acquirers, at best, merely break even.
Originality/value
The evidence that UK takeovers distribute value gains nearly equally between domestic deal parties challenges the enduring conventional insight in the M&A literature. This conventional wisdom suggests that the value created by business combinations is entirely distributed to target company stockholders. Consequently, this reexamination may have broader implications, offering an alternative perspective on the motives behind business combinations. This perspective differs from the “managerial hubris hypothesis,” which aligns with the prevailing conventional insight but receives limited support in the original finding reported here.
Keywords
Citation
da Graca, T. (2024), "How do takeovers in the United Kingdom split value gains between domestic deals' parties?", Journal of Business and Socio-economic Development, Vol. 4 No. 2, pp. 97-110. https://doi.org/10.1108/JBSED-05-2023-0035
Publisher
:Emerald Publishing Limited
Copyright © 2023, Tarcisio da Graca
License
Published in Journal of Business and Socio-economic Development. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
This paper provides evidence that the synergies resulting from domestic takeovers in the United Kingdom are roughly equally divided between the stockholders of acquiring companies and target companies from 2013 to 2020. This finding, in conjunction with the recent and growing empirical literature on the subject (discussed in Section 2), suggests the need to reevaluate a long-standing paradigm in takeover literature, potentially establishing a new baseline.
The conventional wisdom in the takeover literature, which posits that, on average, stockholders of target companies benefit from takeovers while stockholders of acquiring companies break even at best (e.g. Betton et al., 2008, p. 405), is deeply ingrained in widely adopted corporate finance textbooks (e.g. Copeland et al., 2005, p. 778; Ross et al., 2008, p. 835; Brealey et al., 2011, p. 813). This reference is henceforth referred to as the conventional insight and can be alternatively stated as a general proposition: any value created by takeovers is entirely distributed to the stockholders of the target company.
In Section 3, we begin by estimating the percentage excess returns on the announcement (or disclosure) days for both acquiring companies' stockholders and target companies' stockholders. These percentage excess returns provide partial statistical evidence that is consistent with the conventional insight.
Next, we calculate pound excess returns from the percentage excess returns by multiplying them by the corresponding market capitalizations. This allows a direct estimation of the distribution of takeover synergies. Astonishingly, the statistical tests performed on the synergy distribution estimation reveal a new perspective, suggesting that UK takeovers nearly halve the synergies between the stockholders of the involved parties, challenging the conventional insight. Section 4 reports this groundbreaking finding, which is highly statistically significant.
Section 5 discusses the methodological features of our approach that underlies this remarkable new finding when compared to the results of papers that support the conventional insight. The approach proposed herein (1) relies on a pairwise analysis (i.e., including deals for which pound excess returns for both parties can be estimated simultaneously) and (2) properly accounts for differences in the sizes of the takeover companies. The proposed ratio methodology standardizes percentage excess returns based on the market capitalizations of the involved companies and estimates pound synergies and their distribution. In doing so, the ratio methodology unequivocally addresses the distribution effect as it includes companies on both sides of a takeover.
Compared to the methodologies of the recent articles criticizing the conventional insight, the ratio methodology, which is an innovation in this context, typically requires less data. This is because these articles often rely on percentage excess returns, just like the methodologies supporting the conventional insight, for their statistical tests. To compensate for this limitation, these articles typically use larger sample sizes and broader preevent and event windows to gather sufficient information to draw their conclusions.
Thus, the ratio methodology broadens the potential applicability of our approach to include researchers at different career stages (from graduate students to tenured faculty members), different periods and different markets where financial data are less abundant.
In addition to these direct effects, our results may have implications for related debates such for example, the one regarding the underlying motivations for corporate takeovers [1]. An explanation frequently associated with the conventional insight is based on the acquirer's management “hubris hypothesis” (Roll, 1986), which suggests that acquirers' managers may engage in merger and acquisition (M&A) deals that, on average, generate no gain for acquirers' stockholders due to their unrealistic beliefs in their superior managerial skills, leaving all the gains to targets' stockholders to the detriment of acquirers. However, the new results presented here indicate that acquirer stockholders gain approximately as much as target stockholders, providing evidence that acquirers' managers make reasonable M&A decisions on behalf of their stockholders rather than succumbing to their hubris.
In conclusion (Section 6), numerous influential articles that support the conventional insight may have done so simply because they rely on percentage excess returns to draw inferences about synergy value distribution among takeover participants. As demonstrated, the percentage excess return approach yields indirect and potentially biased inferences regarding synergy distribution. Hence, it is advisable to maintain a degree of skepticism regarding their support for the conventional insight until they are reassessed using pound excess returns as the focal variables in these studies.
2. Review of the related literature
This section contextualizes this paper's findings. The existing empirical evidence, derived from samples of takeover cases in the United Kingdom, is largely in line with the prevailing literature, which suggests that, on average, stockholders of target companies benefit from takeovers, while stockholders of acquiring companies, at best, break even (i.e., with negligible or slightly negative percentage excess returns), a perspective referred to as the conventional insight.
Draper and Paudyal (1999) explore the impact of information on stockholder wealth and trading activity for acquiring and selling companies in the United Kingdom Their sample spans from 1988 to 1996 and includes 349 bids involving companies traded on the London Stock Exchange. In Table 1, they report that, on the announcement day, the value-weighted market-adjusted excess returns (MAR) are 7.18% for target firms and – 0.66% for bidding firms, both statistically significant at the 5% significance level.
Sudarsanam and Mahate (2003) investigate the effect of different acquirer types and different payment methods on the short and long-term performances of UK acquiring companies. Their sample covers the period from 1983 to 1995 and consists of 519 UK acquirers. In Table 2, they report the “buy and hold” percentage excess returns of acquiring companies using various benchmark models and event windows. They estimate that the MAR of acquirers over the event window (−1, 0, +1) is −1.39%, significant at the one percent level.
Alexandridis et al. (2010) analyze a global sample, including UK takeovers, to determine if public takeovers can benefit the acquiring company's stockholders. Their M&A sample covers the period from 1990 to 2007. They report that the mean cumulative excess return for UK acquirers is −1.58%, statistically significant at the 1% level, over a two-day event window centered on the announcement day. On the other hand, they report that, over the same event window, the mean cumulative excess return for sellers in Canada, the United Kingdom and the United States is 19.65%, statistically significant at the 1% level.
Andriosopoulos et al. (2016) evaluate the impact of institutional ownership monitoring on acquiring companies' performance. Their sample consists of takeovers by publicly traded UK firms from 2000 to 2010. They conclude that value buyers generally outperform glamor buyers on the takeover announcement date and during the short-term postannouncement period. Their estimated excess return on the announcement day is 0.487% (t-stat = 5.281) for acquirers in UK domestic M&As.
Chaudary and Mirza (2017) analyze stockholder returns of UK acquiring banks. Their sample includes domestic bank-to-bank takeovers of UK banks and cross-border acquisitions within the European Union from 2006 to 2013. In their Table 2, they report that the average excess return for acquirers on the announcement day (t = 0) in domestic M&As is −14.321% (t-stat = −1.028).
Overall, published studies on M&As in the United Kingdom over several decades appear consistent with the conventional insight. However, recent empirical evidence from various countries—mostly from the United States—aligns with the main results of our article, suggesting that, on average, stockholders of target companies also benefit from takeovers. Eckbo (2014) states that “econometric advances suggest that bidder takeover gains, traditionally estimated to be small (insignificantly different from zero after transaction costs), may be much greater when the estimation also accounts for how industry dynamics may alter bidder stand-alone values (absent a takeover).” It is worth noting—as we shall see—that even the more recent articles reviewed below rely on percentage excess return (as opposed to pound excess returns) as the primary variable of focus.
Masulis et al. (2010) assess the financial gains of takeover bids by examining both buyers and sellers in successful and unsuccessful acquisition attempts. Their dataset covers takeovers in four countries: the United States, the United Kingdom, Canada and Australia, with 2,963 buyers and 4,606 sellers. They calculate excess returns over (1) the initial announcement of a takeover attempt and (2) the announcement day of the offer result (failure or success). They argue that their approach rectifies signaling bias and revelation bias, providing more accurate results. Their findings indicate that acquirers typically benefit from takeovers, retaining 67% of the net value created in cash offers and 91% in stock offers.
Da Graca and Masson (2017) use a dataset of 262 US takeovers from 1990 to 2008 and conclude that acquirers gain twice as much as targets through a structural approach. However, the related reduced-form approach used on the same dataset aligns with the conventional insight.
Mateev (2017) examines wealth effect differences between the United Kingdom and Continental Europe using a dataset of 2,823 business combinations divulged from 2002 to 2010. By focusing solely on the excess returns of bidding companies, the author concludes that European bidding companies achieve positive excess returns in both cross-border and domestic takeovers, with larger short-term wealth effects in cross-border takeovers.
Wang (2018) employs a “simulated method of moments” in a dataset of US takeovers from 1980 to 2012 to investigate the effects of offer anticipation bias and information revelation bias. The author claims to control for these biases and concludes that takeovers generally create substantial wealth for stockholders of both parties. Acquiring firms' stockholders, rather than target firms' stockholders, captures the majority (about 63%) of the net value created.
Hu et al. (2020) examine the wealth effects of “mega-deals,” defined as deals with a transaction value exceeding $500 million in 2016-dollar terms and exceeding 1% of the acquiring firm's market value of equity.” Their dataset includes 3,544 successful and unsuccessful US takeovers from 1980 to 2016. Their findings suggest that more experienced acquirers generate a mean excess announcement return from their completed “mega-deals,” resulting in a stockholder wealth gain of $50.6 million.
In the last decade, a consistent theme emerging from these reviewed articles, which is greatly reinforced by our findings, is the need to reassess the conventional insight concerning the partitioning of synergies in takeovers. These recent articles either employ large pre-event windows to incorporate more information or signals (Eckbo et al., 2020) that might have been communicated to financial market participants before takeovers' announcement or utilize more powerful statistical methods to achieve more precise estimates over event windows, or both. The data intensity of these articles (i.e., typically involving thousands of deals) may impose a restrictive condition when applying these methods in less developed markets with limited data availability, making generalization of the results difficult.
3. Sample and methodology
Our sample contains UK domestic takeovers that occurred between 2013 and 2020. Eikon [2] is used to identify M&A deals that meet the following criteria:
Both the acquiring and the target companies are based in the United Kingdom
The stocks of both the acquiring company and the target company are publicly traded on the London Stock Exchange (LSE)
Market capitalization data for all companies in the sample is available on the day immediately preceding the takeover announcement.
These criteria are applied to ensure that the sampling procedure remains unbiased and does not impose any prior preferences. The sole purpose of these criteria is to gather takeovers for which essential statistics required for the analysis can be obtained. Table 1 presents our sample of takeovers:
Percentage excess returns of the companies on the days of the takeover announcements are estimated using a traditional event study methodology (Campbell et al., 1997; Kothari and Warner, 2007). This methodology aims to assess the impact of specific events, such as takeover announcements, on a company's performance. The underlying assumption is that if an event is expected to influence a company's future performance, its announcement will lead market participants to reconsider their expectations regarding the company's market valuation. In cases of good (bad) news, excess returns or changes in valuation are expected to be positive (negative).
In this context, a company's valuation is expected to respond promptly to the announcement of a significant event in an efficiently functioning financial market. Under this assumption, the percentage excess return (
A counterfactual estimate of the predicted percentage returns on days other than those with takeover announcements (
Parameters
The “Market model” equation is as follows:
The estimation window for the “market model” consists of two hundred and fifty business days, with the last day being the sixth business day before the takeover announcement day, which coincides with the event window in our analysis. Hence, there is a five-business-day gap between the estimation and event windows. Once
4. Findings
The percentage excess return (ER % column), as shown in Table 2, represents the difference between the company's actual percentage return and the percentage return that would have occurred if the event's disclosure had not taken place, as calculated by the “market model.” To calculate the pound excess return (ER £), you simply multiply the company's percentage excess return by its capitalization on the previous business day, as indicated in Table 2's ER £ column. In the case of a takeover, the sum of the acquirer's ER £ and the target's ER £ provides an estimate of the pound value of synergies (found in the Synergy £ column in Table 2) that investors anticipate gaining from the takeover upon its announcement.
4.1 Percentage excess return
From Table 2, the average percentage excess return of the acquirers is – 1.03%, with a standard error of 1.09% and a p-value of 0.3521. These results indicate that we cannot reject the null hypothesis that the acquirer's excess return is zero, even at the 10% significance level. However, the average percentage excess return of the targets is 13.52%, with a standard error of 2.11% and an extremely low p-value (3*10–7). As such, we strongly reject the null hypothesis that the percentage excess return of the target is zero at the 1% significance level. These results broadly support the conventional insight and, more specifically, align with the research on the United Kingdom reviewed in Section 2.
A crucial point to note here is that these results endorse the view that there is nothing abnormal in our data. Indeed, in terms of the statistical behavior of the takeovers' percentage excess returns, the data behave in a manner that is not different from numerous articles addressing this subject in the United Kingdom and elsewhere. Nonetheless, as we will argue, these percentage excess return results do not necessarily support the conventional insight.
4.2 Pound excess return
To directly compare the pound synergies of the acquirers and the targets, we apply a statistical test that compares the acquirer's pound excess returns to the target's pound excess returns in pairs. This approach accounts for the relationship between the participants (acquirer and target) in each takeover. A paired t-test is used to assess if there exists a significant difference between these two related groups. Herein, a “paired t-test” is more appropriate than the common “two-sample t-test” (aka “independent or uncorrelated t-test”), which is designed for statistical independence. The “paired t-test” is better suited when dealing with data in the form of matched pairs, which is exactly the feature of our dataset under examination.
The null hypothesis for the “paired t-test” is that “targets' pound excess returns are equal to acquirers' pound excess returns,” that is, Target ER £ = Acquirer ER £. In this context, the conventional insight serves as the basis for the alternative hypothesis, which posits that targets' pound excess returns are greater than acquirers' pound excess returns, that is, Target ER £ > Acquirer ER £.
The results of the “paired t-test” challenge the accuracy of the conventional insight, as the t-statistics equals 1.45 and its associated p-value is 0.156. This p-value is not statistically different from zero, even at a 10% significance level. In other words, we cannot reject the null hypothesis that, on average, the acquirer's pound excess return is equal to that of the targets.
This initial finding diverges remarkably from the conventional insight, warranting further investigation. Figure 1 visualizes the data from Table 2, plotting the pound excess returns of the acquirers and the targets on the vertical axis and the total synergies of the takeovers on the horizontal axis.
The figure above displays the fitted straight lines passing through the origin, with their slopes representing the partitioning of synergies between acquirers (40.09%) and targets (59.91%). Table 3 reports the parameter estimates and related statistics of the regressions conducted on the sample.
The estimates and statistics in Table 3 strongly support the following conclusions:
The average share of synergies for acquirers (α) is positive and significantly different from zero. In other words, acquirers not only avoid losses but also gain some synergies from takeovers.
The average share of synergies for targets (τ) is positive and statistically less than one, indicating that targets retain a portion of the synergies but entirety.
The hypothesis that α and τ are equal is rejected at the 5% significance level but not at the 1% significance level, suggesting that the extent to which acquirers and targets share synergies in UK takeovers depends on the chosen significance level.
The hypothesis that α = 0.4 and τ = 0.6 cannot be rejected.
The statistical tests rely on t-distributions, which have heavier tails for lower degrees of freedom (sample size – 1, herein) compared to the normal distribution. Consequently, rejections of the null hypothesis under t-distributions are less likely to occur under normal distributions, addressing any concerns about sample size from a statistical perspective.
Examining the pound excess returns of participants in UK takeovers offers a significantly different perspective on the distribution of takeover synergies between acquirers and targets compared to the conventional insight. By considering the pairs of participants in UK takeovers, we directly address the question of synergy distribution, which can be only indirectly examined, if at all, in studies where this pairing is not the primary focus.
The crux of the argument is that while excess returns expressed as percentages may align with the conventional insight, expressing the same excess returns in pounds leads to an inference in line with recent emerging literature that challenges the conventional insight. This argument also suggests a path to reconcile these seemingly opposing views. More importantly, this article highlights that analyzing the partitioning of synergies between takeover participants is incomplete or inadequate when relying solely on unpaired percentage excess returns or conducting partial analyses (i.e., examining only the results of targets or acquirers separately, but not both simultaneously). This point is further examined in the next section.
5. Discussion
This section elaborates on how—from the same dataset—divergent perspectives on a single issue can emerge. Three key factors merit attention: pairwise (acquirer-target) analysis, the comparison between pound and percentage excess returns, and the consideration of the relative sizes of the parties involved in these pairs.
5.1 Pairwise analysis
The fundamental premise for the ratio methodology to function effectively is to account for the pairs of parties in a deal, ensuring that both the acquirer and the target of a given transaction are included in the sample. This may not be the case in many previous studies that examined this issue. These earlier studies focused on the percentage excess returns of a sample of acquirers and/or targets, without necessarily pairing them in the same deals. A disadvantage of sampling only transactions that estimate the excess returns of both firms in the pair is that it reduces the sample size compared to what could be achieved without this requirement.
5.2 Pound excess returns vs percentage excess returns
Despite the reduction in potential sample size, the significant advantage of the ratio methodology lies in its ability to directly estimate (and test) the distribution of pound gains between the parties involved, which is the central focus of our discussion. For instance, consider the following scenario:
The acquirer's percentage excess returns are only one-tenth of the target's percentage excess returns and
The acquirer's market capitalization is tenfold that of the target.
Due to point 1, when relying on the default procedure, which focuses on percentage excess returns, one might conclude that the targets' stockholders predominantly benefit from M&A synergies. Let us examine the conclusion reached by the ratio methodology, which estimates the sharing of pound gains. Let a be the percentage excess return of the acquirer, t be the percentage excess return of the target, MCacq be the market capitalization of the acquirer and MCtgt be the market capitalization of the target. Then, the ratio of the pound gain of the acquirer (r) can be expressed as:
Due to points 1 and 2, we can write:
This simplifies to:
Hence, r = ½.
So, the ratio methodology correctly concludes that the stockholders of both the acquirer and the target equally share the pound gains from the takeover. This is in stark contrast to the conclusion one might reach by applying the default procedure, which underlies the conventional insight when working with the same dataset.
5.3 Relative size
While the ratio methodology accounts for the “relative size” effect between participants and focuses on pound synergies, the methodology behind the conventional insight often does not [3].
Assumptions 1 and 2 above imply a negative correlation between firms' market capitalization and their excess returns, given a certain level of synergies. This is consistent with business reality: for instance, a windfall of £ 1 million represents a 10% percentage excess return for a £10-million firm, but only a 1% percentage excess return for a £100-million firm [4]. Moeller et al. (2004) and Oswal and Goel (2020) corroborate this by reporting that larger acquirers obtain lower excess returns than smaller acquirers.
The issue of relative size also affects the precision of excess return estimates. To illustrate this point, consider the following example:
The acquirer's capitalization is £1 billion, and the target's capitalization of the target is £100 million.
The percentage excess return of the acquirer is 0.1%, and the percentage excess return of the target is 1%.
The standard deviation of the percentage excess return is 0.1% for both cases.
In this example, the acquirer's excess return is not statistically different from zero (t-stat = 1), while the target's excess return is highly statistically significant and positive (t-stat = 10), aligning with the conventional insight, supporting the perception that target stockholders gain while the acquirers break even.
However, when multiplying the percentage excess returns by the corresponding market capitalization, both parties realize estimated gains of £1 million each. That implies a total estimated synergy of £ 2 million, with both parties equally sharing the gains. The ratio of the gains of the acquirers' stockholders is 50%, statistically significant at the 1% significance level (t-stat = 1.99). Indeed, da Graca and Masson (2017) refer to this effect as the signal-to-noise ratio, which can impact the inferences drawn from the data, depending on whether one fully exploits the data's efficiency.
The main point of this discussion is to illustrate how the results presented herein can reconcile with the conventional insight: (1) using pairs of takeover parties, (2) computing pound excess returns from percentage excess returns, as estimated in papers adhering to the conventional insight, by multiplying the latter by market capitalizations and (3) to directly estimate the distribution of pound synergies in M&As. The contention is that if some of the papers that support the conventional insight had applied these steps (1, 2 and 3), they would likely have reached conclusions similar to those reported in this study.
5.4 M&A motivation
Beyond their direct implications, our new results and insights may have far-reaching consequences, particularly in the ongoing debate surrounding the underlying motivations for corporate takeovers. The “hubris hypothesis” posits that takeovers occur when acquiring company managers are excessively optimistic about their ability to create and build up synergies, resulting in overbidding for their targets (Roll, 1986). This hypothesis implies, at best, negligible net gains for the acquiring company. As a general proposition, the “hubris hypothesis” posits that the target's valuation should increase, while the acquirer's valuation should remain stagnant, or even decrease, due to managerial miscalculation, essentially representing a wealth reallocation. The conventional insight and the “hubris hypothesis” share a close relationship.
Our new insights and empirical results, when considered alongside recent empirical literature, compel a re-assessment of the “hubris hypothesis” as a driving force behind takeovers. This is because our evidence indicates that, in reality, both the acquirers' and targets' stockholders roughly share the value generated by UK takeovers. In other words, the findings from the ratio methodology applied to this UK sample reject the occurrence of significant wealth transfer from acquirers' stockholders to targets' stockholders. This contradicts a central tenet of the “hubris hypothesis” and diminishes its explanatory power. On the other hand, these ratio methodology findings align with the hypothesis that rational criteria, such as net present value analysis (NPV), influence acquirers' decision-making processes in UK takeovers. In this context, the impetus for takeovers lies in their positive NPV propositions (Ahern and Weston, 2007).
6. Conclusion
This article uses a sample of domestic takeovers in the United Kingdom spanning from 2013 to 2020 to estimate the distribution of synergies between acquiring company stockholders and target company stockholders. The main finding is that acquirers receive a share of the synergies in pounds nearly equal to that of target stockholders. This original result is both surprising and compelling for two reasons.
First, the conventional insight, which remains prevalent in the literature, including articles on the United Kingdom, is that, on average, synergies are completely absorbed by the targets to the detriment of acquirers, who at best do not suffer losses. Therefore, the main finding could potentially instigate a paradigm shift in the takeover literature or, at the very least, prompt a critical review of this conventional insight.
Second, the percentage excess returns obtained from this UK sample are consistent with previous findings that support the conventional insight. This alignment serves as validation for the sample and our preliminary results. Furthermore, given the article's main finding, this aspect necessitates a reexamination of the standard approach that underpins the conventional insight.
The ratio methodology proposed here, which is innovative in this context, is based on the excess returns in pounds, calculated by multiplying the percentage of excess returns by the firm's market capitalization. The sum of the pound excess returns of the acquirer and the target estimates the total synergy expected from the takeover. Dividing the pounds excess return of one party by the total synergy in pounds directly and unequivocally estimates the fraction of synergy held by that party. This highlights a weakness in the approach underpinning the conventional insight, which inappropriately infers, as we have seen, the distribution of synergies from the percentage excess returns of each group (acquirers and targets) separately.
Compared to recent approaches that have also challenged the conventional insight, the ratio methodology is technically less demanding and provides a direct inference about the distribution of synergies from smaller samples, suggesting its high statistical power. In our sample, the article demonstrates an impressive yet credible reversal of conclusions using a narrow event window and a number of takeovers smaller than those used in recent approaches critical of the conventional insight. This leads us to propose the following research sequence: Initiate the investigation with the ratio methodology. If the conventional insight is not rejected, proceed with the inquiry using more data-intensive approaches and statistical techniques proposed by recent approaches critical of the conventional insight. This road map, starting with the ratio methodology and extending to transactions in other countries and different time intervals, could support the generalization of the article's results.
Finally, the novel results presented here suggest a careful re-examination of the conventional insight in the United Kingdom and elsewhere, which could have profound implications. For example, it could shift the equilibrium of takeover dynamics from the “hubris hypothesis” (Roll, 1986) to a neoclassical theory in which acquirer managers make takeover decisions that benefit their shareholders as much as the shareholders of target companies.
Figures
Sample of UK companies with takeovers from 2013 to 2020
| Match | Acquirer | Target | Announcement day |
|---|---|---|---|
| 1 | PARKMEAD GROUP PLC | LOCHARD ENERGY GROUP LTD | 05–23–13 |
| 2 | PETARDS GROUP PLC | WATER HALL GROUP PLC | 07–01–13 |
| 3 | STANLEY GIBBONS GROUP PUBLIC LIMITED COMPANY | NOBLE INVESTMENTS (UK) PLC | 09–26–13 |
| 4 | FALKLAND OIL & GAS PLC | DESIRE PETROLEUM PLC | 10–03–13 |
| 5 | IP GROUP PLC | FUSION IP PLC | 01–23–14 |
| 6 | BRAEMAR SHIPPING SERVICES PLC | ACM SHIPPING GROUP PLC | 05–20–14 |
| 7 | ROCKHOPPER EXPLORATION PLC | MEDITERRANEAN OIL & GAS PLC | 05–23–14 |
| 8 | GREENE KING PLC | SPIRIT PUB COMPANY PLC | 09–23–14 |
| 9 | INTERNATIONAL PERSONAL FINANCE PLC | MCB FINANCE GROUP PLC | 11–18–14 |
| 10 | AVIVA PLC | FRIENDS LIFE GROUP LTD | 11–21–14 |
| 11 | J SAINSBURY PLC | HOME RETAIL GROUP PLC | 01–05–16 |
| 12 | VECTURA GROUP PLC | SKYEPHARMA PLC | 03–16–16 |
| 13 | RPC GROUP PLC | BRITISH POLYTHENE INDUSTRIES PLC | 06–09–16 |
| 14 | TESCO PLC | BOOKER GROUP LTD | 01–27–17 |
| 15 | LEARNING TECHNOLOGIES GROUP PLC | NETDIMENSIONS (HOLDINGS) LIMITED | 02–03–17 |
| 16 | HANSTEEN HOLDINGS LTD | INDUSTRIAL MULTI PROPERTY TRUST PLC | 02–17–17 |
| 17 | STANDARD LIFE ABERDEEN PLC | ABERDEEN ASSET MANAGEMENT PLC | 03–04–17 |
| 18 | JOHN WOOD GROUP PLC | AMEC FOSTER WHEELER PLC | 03–13–17 |
| 19 | IP GROUP PLC | TOUCHSTONE INNOVATIONS PLC | 05–23–17 |
| 20 | ENTAIN PLC | LADBROKES CORAL GROUP PLC | 12–07–17 |
| 21 | CLINIGEN GROUP PLC | QUANTUM PHARMA PLC | 08–16–17 |
| 22 | MELROSE INDUSTRIES PLC | GKN LTD | 01–12–18 |
| 23 | INFORMA PLC | UBM PLC | 01–16–18 |
| 24 | TT ELECTRONICS PLC | STADIUM GROUP PLC | 02–15–18 |
| 25 | VIRGIN MONEY UK PLC | VIRGIN MONEY HOLDINGS (UK) PLC | 05–07–18 |
| 26 | PRIMARY HEALTH PROPERTIES PLC | MEDICX FUND LTD | 01–24–19 |
| 27 | TREMOR INTERNATIONAL LTD | RHYTHMONE PLC | 02–04–19 |
| 28 | JD SPORTS FASHION PLC | FOOTASYLUM PLC | 03–15–19 |
| 29 | LONDONMETRIC PROPERTY PLC | A & J MUCKLOW GROUP P L C | 05–23–19 |
| 30 | PREMIER MITON GROUP PLC | MITON GROUP PLC | 09–04–19 |
| 31 | MERCIA ASSET MANAGEMENT PLC | NORTHERN VENTURE TRUST PLC | 12–03–19 |
| 32 | ANGLO AMERICAN PLC | SIRIUS MINERALS LTD | 01–08–20 |
| 33 | BAHAMAS PETROLEUM COMPANY PLC | COLUMBUS ENERGY RESOURCES PLC | 06–11–20 |
| 34 | DEEPVERGE PLC | MODERN WATER PLC | 08–28–20 |
Source(s): Eikon
Companies' excess returns, capitalization and takeovers' synergies (in 1,000 £)
| Acquirers | Targets | Total | |||||
|---|---|---|---|---|---|---|---|
| Match | MKTCAP | ER % | ER £ | MKTCAP | ER % | ER £ | Synergy £ |
| 1 | 126,341 | −0.0134 | −1692.9694 | 14,196 | −0.1125 | −0.0134 | −3290.0194 |
| 2 | 7,479 | −0.1273 | −952.0767 | 1,972 | 0.1747 | −0.1273 | −607.5683 |
| 3 | 13,448 | 0.05 | 672.4 | 42,168 | 0.0402 | 0.05 | 2367.5536 |
| 4 | 45,350 | −0.0266 | −1206.31 | 54,765 | 0.2841 | −0.0266 | 14352.4265 |
| 5 | 1,228,081 | −0.0215 | −26403.7415 | 1,001,35 | 0.1909 | −0.0215 | −7287.97 |
| 6 | 70,443 | −0.0469 | −3303.7767 | 48,481 | 0.0266 | −0.0469 | −2014.1821 |
| 7 | 44,381 | −0.0115 | −510.3815 | 27,499 | 0.1655 | −0.0115 | 4040.703 |
| 8 | 2,649,504 | 0.0167 | 44246.7168 | 762,038 | 0.1688 | 0.0167 | 172878.7312 |
| 9 | 180,059 | 0.0117 | 2106.6903 | 21,670 | 0.2078 | 0.0117 | 6609.7163 |
| 10 | 14,208,032 | −0.0005 | −7104.016 | 6,033,929 | 0.0037 | −0.0005 | 15221.5213 |
| 11 | 5,029,878 | −0.0603 | −303301.6434 | 1,299,072 | 0.3455 | −0.0603 | 145527.7326 |
| 12 | 674,573 | 0.0346 | 23340.2258 | 476,605 | 0.0445 | 0.0346 | 44549.1483 |
| 13 | 3,220,637 | 0.0386 | 124316.5882 | 269,752 | 0.305 | 0.0386 | 206590.9482 |
| 14 | 17,380,875 | 0.0846 | 1470422.025 | 4,026,939 | 0.1455 | 0.0846 | 2056341.65 |
| 15 | 1,205,382 | −0.0883 | −106435.2306 | 51,352 | 0.2115 | −0.0883 | −95574.2826 |
| 16 | 499,914 | 0.005 | 2499.57 | 26,700 | 0.2227 | 0.005 | 8445.66 |
| 17 | 7,051,719 | −0.0085 | −59939.6115 | 4,185,696 | 0.008 | −0.0085 | −26454.0435 |
| 18 | 2,048,654 | 0.0112 | 22944.9248 | 2,131,205 | 0.1079 | 0.0112 | 252901.9443 |
| 19 | 1,228,081 | −0.0031 | −3807.0511 | 507,793 | 0.0293 | −0.0031 | 11071.2838 |
| 20 | 9,497,295 | 0.0484 | 459669.078 | 3,286,570 | 0.255 | 0.0484 | 1297744.428 |
| 21 | 949,162 | 0.0023 | 2183.0726 | 142,862 | 0.1108 | 0.0023 | 18012.1822 |
| 22 | 8,059,845 | 0.0559 | 450545.3355 | 8,285,113 | 0.2317 | 0.0559 | 2370206.018 |
| 23 | 8,273,775 | 0.0023 | 19029.6825 | 4,256,152 | 0.0514 | 0.0023 | 237795.8953 |
| 24 | 333,120 | 0.035 | 11659.2 | 46,196 | 0.3477 | 0.035 | 27721.5492 |
| 25 | 2,644,100 | −0.0028 | −7403.48 | 1,558,113 | 0.0155 | −0.0028 | 16747.2715 |
| 26 | 1,999,712 | −0.0272 | −54392.1664 | 420,770 | 0.1065 | −0.0272 | −9580.1614 |
| 27 | 766,841 | 0.1189 | 91177.3949 | 133,316 | 0.1342 | 0.1189 | 109068.4021 |
| 28 | 8,081,728 | 0.0156 | 126074.9568 | 85,147 | 0.01 | 0.0156 | 126926.4268 |
| 29 | 1,987,431 | −0.0058 | −11527.0998 | 405,087 | 0.1592 | −0.0058 | 52962.7506 |
| 30 | 205,708 | 0.0051 | 1049.1108 | 94,949 | 0.2226 | 0.0051 | 22184.7582 |
| 31 | 105,186 | −0.1461 | −15367.6746 | 105,349 | −0.0001 | −0.1461 | −15378.2095 |
| 32 | 37,792,449 | −0.0031 | −117156.5919 | 385,409 | 0.3138 | −0.0031 | 3784.7523 |
| 33 | 13,661 | −0.2023 | −2763.6203 | 15,481 | −0.1388 | −0.2023 | −4912.3831 |
| 34 | 35,166 | −0.0901 | −3168.4566 | 13,221 | 0.2063 | −0.0901 | −440.9643 |
Source(s): Eikon and authors’ own calculations of excess returns
Regression analysis
| Equation | Parameter | Parameter estimate | Std. error | t Stat | p-value |
|---|---|---|---|---|---|
| Acquirer ER £ = α × Synergy £ | α | 0.4009 | 0.0467 | 8.5778 | 7E-10 |
| Target ER £ = τ × Synergy £ | τ | 0.5991 | 0.0467 | 12.820 | 2E-14 |
Source(s): Authors’ own calculations
Notes
More broadly, studies examining the extent to which managerial procedures contribute to favorable takeover outcomes (Tampakoudis et al., 2022; Delis et al., 2022) and investigations into the impact of a country's economic policies on takeover gains (Shams et al., 2022) typically rely on percentage excess returns as their dependent variables. These papers might reach different conclusions if their focal variables were based on the monetary (pound, in the UK context) excess returns acquired by the M&A parties instead.
Eikon is a suite of software products provided by Refinitiv, offering access to a wide range of tools, including market data, news and fundamental data, among others.
In some conventional studies, size variables appear as explanatory (or independent) variables in regressions where percentage excess returns are the dependent variables. This approach fundamentally differs from the one proposed here. Instead of elucidating the phenomenon, the sizes of the parties are inherent components of the definition of variable of interest in this context, namely, the ratio of the M&A pound synergy accumulated to the parties.
The size effect could also be affected by differences in the information environments between small and large acquirers (Bhushan, 1989; Dempsey, 1989).
References
Ahern, K.R. and Weston, J.F. (2007), “M&As: the good, the bad, and the ugly”, Journal of Applied Finance, Vol. 17 No. 1, pp. 5-20, available at: https://ssrn.com/abstract=2085006
Alexandridis, G., Petmezas, D. and Travlos, N.G. (2010), “Gains from mergers and acquisitions around the world: new evidence”, Financial Management, Vol. 39 No. 4, pp. 1671-1695, doi: 10.1111/j.1755-053X.2010.01126.x.
Andriosopoulos, D., Yang, S. and Li, W.A. (2016), “The market valuation of M&A announcements in the United Kingdom”, International Review of Financial Analysis, Vol. 48, pp. 350-366, doi: 10.1016/j.irfa.2015.05.022.
Betton, S., Eckbo, B.E. and Thorburn, K.S. (2008), “Corporate takeovers”, in Eckbo, E. (Ed.), Handboook of Corporate Finance: Empirical Corporate Finance, Elsevier, North Holland, Amsterdam, Vol. 2, pp. 291-429, doi: 10.1016/B978-0-444-53265-7.50007-X.
Bhushan, R. (1989), “Firm characteristics and analyst following”, Journal of Accounting and Economics, Vol. 11 Nos 2-3, pp. 255-274, doi: 10.1016/0165-4101(89)90008-6.
Brealey, R., Myers, S. and Allen, F. (2011), Principles of Corporate Finance, 10th ed., McGraw-Hill/Irwin, Boston, MA.
Campbell, J., Lo, A. and MacKinlay, A. (1997), The Econometrics of Financial Markets, Princeton University Press, Princeton, NJ.
Chaudary, S. and Mirza, N. (2017), “Domestic and cross-border returns to bidders in acquisitions into the EU”, Economic Research, Vol. 30 No. 1, pp. 1021-1032, doi: 10.1080/1331677X.2017.1311228.
Copeland, T., Weston, J. and Shastri, K. (2005), Financial Theory and Policy, 4th ed., Pearson, New York, NY.
da Graça, T. and Masson, R. (2017), “Acquirers gain twice as much as targets in M&As: a different perspective on a longstanding perception”, Quantitative Finance Letters, Vol. 4 No. 1, pp. 71-76, doi: 10.1080/21649502.2017.1286089.
Delis, M.D., Iosifidi, M., Kazakis, P., Ongena, S. and Tsionas, M.G. (2022), “Management practices and M&A success”, Journal of Banking & Finance, Vol. 134, doi: 10.1016/j.jbankfin.2021.106355.
Dempsey, S.J. (1989), “Predisclosure information search incentives, analyst following, and earnings announcement price response”, Accounting Review, Vol. 64 No. 4, pp. 748-757, available at: https://www.jstor.org/stable/247859.
Draper, P. and Paudyal, K. (1999), “Corporate takeovers: mode of payment, returns and trading activity”, Journal of Business Finance & Accounting, Vol. 26 Nos 5-6, pp. 521-558, doi: 10.1111/1468-5957.00266.
Eckbo, B.E. (2014), “Corporate takeovers and economic efficiency”, Annual Review of Financial Economics, Vol. 6 No. 1, pp. 51-74, doi: 10.1146/annurev-financial-110112-120938.
Eckbo, B.E., Malenko, A. and Thorburn, K.S. (2020), “Strategic decisions in takeover auctions: recent developments”, Annual Review of Financial Economics, Vol. 12, pp. 237-276, doi: 10.1146/annurev-financial-012720-013903.
Hu, N., Li, L., Li, H. and Wang, X. (2020), “Do mega-mergers create value? The acquisition experience and mega-deal outcomes”, Journal of Empirical Finance, Vol. 55, pp. 119-142, doi: 10.1016/j.jempfin.2019.11.004.
Kothari, S. and Warner, J. (2007), “Econometrics of event studies”, in Eckbo, E. (Ed.), Handbook of Corporate Finance: Empirical Corporate Finance, North Holland, Amsterdam, Vol. 1, pp. 3-36, doi: 10.1016/B978-0-444-53265-7.50015-9.
Masulis, R.W., Swan, P.L. and Tobiansky, B. (2010), “Do wealth creating mergers and acquisitions really hurt acquirer shareholders?”, Paper Presented at the AFA 2012 Chicago Meetings Paper and at the 24th Australasian Finance and Banking Conference 2011. doi: 10.2139/ssrn.1787605.
Mateev, M. (2017), “Is the M&A announcement effect different across Europe? More evidence from continental Europe and the U.K”, Research in International Business and Finance, Vol. 40, pp. 190-216, doi: 10.1016/j.ribaf.2017.02.001.
Moeller, S.B., Schlingemann, F.P. and Stulz, R.M. (2004), “Firm size and the gains from acquisitions”, Journal of Financial Economics, Vol. 73 No. 2, pp. 201-228, doi: 10.1016/j.jfineco.2003.07.002.
Oswal, S. and Goel, K. (2020), “The impact of merger and acquisition announcements on acquirer's share price: an analytical study using random effects”, IUP Journal of Applied Economics, Vol. 19 No. 3, pp. 8-25.
Roll, R. (1986), “The hubris hypothesis of corporate takeovers”, Journal of Business, Vol. 59 No. 2, pp. 197-216, available at: http://www.jstor.org/stable/2353017
Ross, S., Westerfield, R. and Jordan, B. (2008), Essentials of Corporate Finance, 6th ed., McGraw-Hill/Irwin, New York, NY.
Shams, S., Gunasekarage, A. and Velayutham, E. (2022), “Economic policy uncertainty and acquisition performance: australian evidence”, International Review of Economics & Finance, Vol. 78, pp. 286-308, doi: 10.1016/j.iref.2021.12.004.
Sudarsanam, S. and Mahate, A.A. (2003), “Glamour acquirers, method of payment and post-acquisition performance: the U.K. Evidence”, Journal of Business Finance & Accounting, Vol. 30 Nos 1‐2, pp. 299-342, doi: 10.1111/1468-5957.00494.
Tampakoudis, I., Nerantzidis, M., Artikis, P. and Kiosses, N. (2022), “The effect of board size on shareholder value: evidence from bank mergers and acquisitions”, European Management Journal, Vol. 40 No. 6, pp. 883-894, doi: 10.1016/j.emj.2022.09.002.
Wang, W. (2018), “Bid anticipation, information revelation, and merger gains”, Journal of Financial Economics, Vol. 128 No. 2, pp. 320-343, doi: 10.1016/j.jfineco.2018.02.010.
Further reading
Hossain, M.S. (2021), “Merger & Acquisitions (M&As) as an important strategic vehicle in business: thematic areas, research avenues & possible suggestions”, Journal of Economics and Business, Vol. 116, doi: 10.1016/j.jeconbus.2021.106004.