Agreeing to participate or disagreeing to implement it?

Leonidas Barbopoulos and Dimitris Alexakis

Abstract: We present new evidence on the announcement period returns of a sample of UK

mergers and acquisitions (M&As) financed with earnout (contingent) versus non-earnout (non-

contingent) payments and advised by financial advisors. We show that deals financed with

earnouts in the presence of a financial advisor consulting the acquiror yield the highest

announcement period returns to bidders’ shareholders. Such deals consistently outperform other

earnout financed cases without the involvement of financial advisors, as well as non-earnout deals

regardless of the presence of financial advisors. We argue that this result is mainly due to the

ability of financial advisors to extract profitable opportunities, and where necessary structure the

earnout contract’s terms efficiently, leading to a very optimistic market reaction. Overall, earnout

financing provides a more effective payment method in M&As, particularly when interacting with

the presence of financial advisors, than that of other forms of payment methods.

Keywords: Methods of Payment; Earnout; Mergers and Acquisitions; Financial Advisor;

Announcement Period Returns.

JEL Classification: G34

Preliminary Version

Please Do Not Quote

Please address correspondence to Leonidas Barbopoulos, School of Economics and Finance, University of St

Andrews, The Scores, St Andrews, Fife KY16 9AL, UK. Tel: +44133461955. Email: leonidas.barbopoulos@st-

andrews.ac.uk. Dimitris Alexakis, School of Economics and Finance, University of St Andrews, The Scores, St

Andrews, Fife KY16 9AL, UK. Tel: +44133461955. Email: da30@st-andrews.ac.uk.

1. Introduction

There is, by now, an established literature that studies mergers and acquisitions’ (M&As) success

conditional on the choice of method of payment used to finance the deal as well as the

involvement of financial advisors along with its reflection on the excess returns accrued to

merging firms’ shareholders. See for example Myers and Majluf (1984), Travlos (1987), Eckbo,

Giammarino and Henkel (1990), Fuller, Netter and Stegemoller (2002), Kale, Kini and Ryan

(2003), Faccio and Masulis (2005), Eckbo (2009), Bao and Edmans (2011), Golubov, Petmezas

and Travlos (2012). This literature provides convincing evidence that the involvement of skilled

financial advisors and, more specifically, the involvement of top-tier advisors, known for their

ability to identify profitable opportunities and create substantial synergies, interacts with the

payment method in shaping the likelihood of success of the deal and thus the distribution of the

bidding firm’s abnormal returns (Golubov, Petmezas and Travlos, 2012). Extant literature appears

also convincing that earnout financing provides a solution to valuation risk arising in smaller

deals involving mainly unlisted targets and operating in intangible rich sectors (Kohers and Ang,

2000; Barbopoulos and Sudarsanam, 2012). Under the terms of an earnout contract the selling

firm receives additional future payments provided it achieves certain pre-specified performance-

related goals. The earnout payment mechanism often involves two stages. In the first stage, the

payment is delivered to the seller at the time of the deal announcement (in the form of cash, stock,

or mixed payments), while the second (usually in cash) is delivered after a pre-determined period

has elapsed following the deal announcement. Earnout contracts share the risk of possible mis-

valuation between the bidder and the target during the announcement period while they eliminate

moral hazard problems in the post-merger or integration period. Provided that earnouts are

complicated contracts and difficult to be structured, while they also give rise to substantial

monitoring costs in the post-merger period, which can offset the majority of the aforementioned

benefits, the involvement of financial advisor(s) is likely to affect their implementation, improve

the efficiency of their design and estimate its terms more accurately.1 However, we are not

exposed into evidence on whether in deals financed with earnouts, versus non-earnout, the

involvement of financial advisors enhances the likelihood of their success, which ultimately leads

to higher announcement period returns to bidders’ shareholders. In this paper we aim to fill this

void in the literature.

1 Cain, Denis and Denis (2011) provide a thorough discussion on the costs and benefits involved in M&As financed

with earnouts.

Information asymmetry in M&As involving unlisted target firms2 stands as one of the major

sources of valuation risk.3 One way of managing, and in most of the times mitigating this risk is

to make part of the payment contingent upon the future performance of the target firm under

existing management via the utilization of an earnout payment mechanism. Evidence presented in

previous studies shows that earnouts have been used to manage valuation risk in acquisitions of

private targets operating in the hi-tech and service industries (Kohers and Ang, 2000). In such

industries, information asymmetry is high and the value of the firm is often dependent on the

knowledge, skill, creativity, and flair of key personnel. However, the level of complexity

involved when agreeing upon the (threshold) performance goals as well as the size of the deferred

payment and the length of the earnout contract, which are balanced against the current and future

risk exposure of the merging firms, stand as major challenges in earnout financed deals (Cain,

Denis and Denis, 2011).4 Along these lines, skilled financial advisors have been proven to be able

to extract higher synergy gains while negotiating better terms in M&As (Bao and Edmans,

2011).5 Servaes and Zenner (1996) demonstrate that the choice to use a financial advisor is

strongly affected by the complexity of the deal, the type of transaction (takeovers versus

acquisitions of assets), the acquiror acquisition experience and the degree of diversification of the

target firm. As a result, the presence of financial advisors in M&As financed with earnouts is

vital.6

The earnout usage in cases characterized by high valuation risk leads to positive returns

outperforming traditional means of financing, such as cash, stock and mixed ones that are fully

delivered at the announcement time, and mirrors the market’s optimistic perception of such

concentrations. More recent literature confirms that the presence of financial advisors in M&As is

associated with higher short-run gains to bidders while this effect is stronger under top-tier

advisor involvement (Golubov, Petmezas and Travlos, 2012). Therefore, it should be value

2 Faccio and Masulis (2005) show that approximately 90% of UK (and Irish) acquisitions involve unlisted target firms

while Draper and Paudyal (2006) report approximately 87% of the UK acquisitions involved privately held targets.

However, Moeller et al. (2007) show that approximately only 53% of US acquisitions involve unlisted targets. 3 Discussions on the valuation risk of private target M&A can be found in Chang (1998), Fuller et al. (2002), Faccio et

al. (2006) and Officer et al. (2009). 4 Cain, Denis, and Denis (2011) have adderees, via simulations, the complexity involved in ea financed deals while

they provide convincing arguments regarding the size and length of the contracts. 5 Previous literature shows that M&As advisors stand as a very influencing factor affecting the outcome of M&As.

Many aspects of their involvement along with their incentives have been examined in terms of their reputation and top-

tier classification (Bowers and Miller, 1990; Servaes and Zenner, 1996; Kale, Kini and Ryan, 2003; Golubov, Petmezas

and Travlos, 2012) as well as the possible existence of a conflict of interest (Allen, Jagtiani and Peristiani, 2004;

Kolasinski and Kothari, 2008; Bodnaruk, Massa and Simonov, 2009). In a more recent study, Bao and Edmans (2011)

discussed the ‘skilled advice’ hypothesis highlighting that investment banks, acting as advisors, are more capable

of identifying higher synergy gains in target firms and can negotiate better terms. This leads to the

‘investment bank fixed effect’ in bidder announcement returns. 6 Servaes and Zenner (1996) illustrate that the choice to use a financial advisor is positively related to the complexity of

the transaction as is the choice to implement an earnout contract (Kohers and Ang, 2000).

adding in the existing literature to investigate whether the relative outperformance of earnout

financed deals, when compared to non-earnout ones, is due to the ability of the earnout itself to

reduce valuation problems and enhance future synergies or due to the presence of an investment

bank consulting the acquiring firm and influencing the implementation (and structure) of this

payment method, or the association of both. We argue that in complex cases, where synergy gains

are not easily extracted due to information asymmetry problems or difficult to value assets,

financial advisors are likely to propose such instruments in order to combat moral hazard,

enhance the realization of the above-mentioned synergies and hence benefit both parties involved

in the concentration. We test for these effects and provide new evidence in the existing literature.

This paper presents new evidence on announcement period returns using a larger sample,

near exhaustive, of UK M&As financed with various methods of payments (fully delivered at the

announcement period, such as cash, stock, mixed, and contingent such as earnouts) and advised

by M&As financial advisors. We test whether the use of earnouts as a structural payment

mechanism, versus other payments that are delivered fully at the announcement period, increases

the announcement period returns to bidders’ shareholders. As such this paper is the first to

explore the effects of earnout financing on bidders’ short-run returns when M&As financial

advisors are involved.

Using a UK sample of M&As covering the period from 1986 to 2010 we present new

evidence on the determinants of value creation from earnout financed deals. In the presence of

financial advisors, M&As financed with earnouts yield the highest returns to bidders’

shareholders further indicating that the well documented evidence on value creation from deals

financed with earnouts is mainly driven by the presence of financial advisors on the acquiring

side of the deal. We argue that this is the outcome of the interaction between contingent payments

and the involvement of specialised financial advisors, but mainly due to latter’s ability to extract

synergies and thus design such complicated contracts more effectively.

We employ a two stage approach. The first stage comprises a standard univariate analysis of

bidders’ announcement period returns. This involves comparing the risk-adjusted returns of

bidders financing deals using earnouts relative to counterparts using traditional methods of

payment only, such as full-cash (cash), full-stock (stock), and mixed payments (involving only

cash and stock). The second stage of our analysis comprises a multiple regression analysis of the

impact of earnouts on bidders’ announcement period returns, while controlling for the impact of

several transaction- and merging institution-specific features.

The main findings of our analysis indicate that the use of earnouts in M&As involving

financial advisors leads to significantly higher announcement period returns to bidders’

shareholders when compared to earnout deals not involving financial advisors as well as deals

financed with cash, stock or a mixture of cash and stock payments. Earnout interacts with several

transaction- and merging institution-specific characteristics (such as the target firm’s listing

status, the relative size of the transaction), in determining the announcement period returns of

bidders. We show that the higher the size of the earnout contract, as a fraction of the total

transaction value, the lower the announcement period returns accrued to bidders. Overall, the

results presented in this paper suggest that the market reacts favorably to the use of earnout

contracts in M&As involving financial advisors depicting a potential complementarity between

the two.

Our paper contributes to the literature in the following ways. First, this paper is the first to

explore the effects of earnout financing on bidders’ short-run returns when financial advisors are

involved in the valuation process of the deal. This provides the opportunity to incorporate factors

specific to the financial advisor when assessing how the market reacts to M&A announcements.

Second, provided that M&As financed with earnouts and involving financial advisors constitute

cases with additional complexities to the bidding firm regarding the valuation of the target firm

and the planning of the design of the contract, we investigate the announcement period returns to

bidders’ shareholders.

The remainder of the paper is organised as follows. Section 2 examines the incentives

relating to the choice of payment method in M&A transactions, and how such a choice affects

returns to bidding institutions. Section 2 also formulates reviews salient literature and presents

testable hypotheses. Section 3 outlines the methods used to conduct the empirical analysis. This

section also discusses the determinants of bidders’ announcement period returns. Section 4

provides a description of the data employed and discusses the main findings. Finally, Section 5

provides a conclusion.

2. Financial advisor involvement, earnout financing and testable hypotheses

Two streams of M&A literature are combined in this paper. The first deals with the use of

earnouts as a means of financing an acquisition while the second one deals with the role of

financial advisors involved in the acquiring side of the deal.

2.1. Financial advisor involvement

The role of financial advisors and their involvement in corporate takeovers has been

thoroughly examined in the current M&A literature. Bowers and Miller (1990) demonstrate that

the choice of investment banker has wealth implications for the bidding firm’s shareholders by

establishing the “Better Merger” and “Bargaining Power” hypotheses. More specifically, it is

concluded that an investment bank, and especially a top-tier one due to its better expertise, is

able to identify firms with whom an acquisition would result in greater economic benefits.

Nevertheless, it is implied that the market for takeover targets is sufficiently competitive so that

no differential bargaining power between investment banks is observed. Michel, Shaked and

Lee (1991), however, cast doubt upon whether the prestige of a financial advisor affects

acquisition performance by depicting the relative outperformance of deals advised by Drexel

Burnham Lambert, an investment bank from the second most prestigious group.

Within the same context, Servaes and Zenner (1996) investigated the largest takeovers per

year and compared acquisitions completed with and without investment bank advice. They

conclude that transaction costs and, in part, contracting costs and information asymmetries are

related to the choice to hire a financial advisor. More specifically, an investment bank is more

likely to be consulted when the acquisition is more complex, when bidders have less previous

takeover experience as well as when targets operate in an unrelated industry. Considering the

investment bank’s top-tier classification and the announcement period bidder returns, no

significant relationship is identified. On the contrary Kale, Kini and Ryan (2003) report that the

absolute wealth gain as well as the share of the total takeover wealth gain accruing to the bidder

increases as the reputation of the bidder's advisor increases relative to that of the target.

Similarly, Hunter and Jagtiani (2003) indicate that advisor quality and the number of advisors

employed in a given transaction are important in determining the probability of completing a deal

as well as the time required for its completion with top-tier advisors being more efficient.

Recently published studies have shed more light on the influence of financial advisors on

takeover outcomes. In their paper, Bao and Edmans (2011), show that investment banks matter

for takeover outcomes. They establish the “skilled-advice” hypothesis indicating that

investment banks, acting as advisors, are capable of identifying higher synergy gains in

target firms. This consulting superiority of financial advisors results in a significant

investment bank fixed effect in the announcement returns of M&A deals. Within the same

context and contrary to prior studies, Golubov, Petmezas and Travlos (2012), report that top-tier

advisors deliver higher bidder returns than their non top-tier counterparts, but in public

acquisitions only. Their ability to deliver greater announcement period returns is proven to be

sourcing from their reputational exposure in public concentrations along with their larger set of

advisor expertise and capabilities.

Another issue that has been addressed by financial advisor M&A literature relates to the

conflict of interests that may exist between the investment bank and the bidder being consulted by

it. Allen, Jagtiani and Peristiani (2004) address this issue when financial institutions act both

as lenders and advisors of a merging firm. In particular, target firms earn higher abnormal returns

when the target's own bank is hired as merger advisor, consistent with the bank's role as certifier

of the target's value to the acquirer. Within the same context, Kolasinski and Kothari (2008) find

evidence that conflicts of interest arising from mergers and acquisitions relations influence

analysts’ recommendations, corroborating regulators’ and practitioners’ suspicions. Furthermore,

Bodnaruk, Massa and Simonov (2009) study holdings in M&A targets by financial

conglomerates, in which affiliated investment banks advise the bidders, and show that

advisors take positions in the targets before M&A announcements. These stakes are negatively

related to the viability of the deal. Within the same context, Ismail (2009) indicates that

investment banks might have different incentives when they advise on large deals as opposed to

small ones.

Finally, another aspect of the involvement of financial advisors in company takeovers relates

to the fees charged by investment banks when advising merging parties. McLaughlin (1990)

reports an average total fee of 1.29% of transaction value with a remarkable variation,

nevertheless, between comparable deals. Furthermore, it is depicted that in almost 80% of

contracts, the advisory fee is contingent upon the completion of the deal, thus incentivizing the

investment bank to work towards the completion of the deal regardless of potential losses in

synergy gains for the advised merging party. McLaughlin (1992) also demonstrates that bidding

firms using less prestigious financial advisors offer significantly smaller premiums for takeover

targets and enjoy higher announcement period abnormal returns.

Overall, empirical evidence suggests that the presence of financial advisors influences the

outcome of an M&A deal and affects the wealth gains accrued to the bidding firms’ shareholders.

Despite the ambiguity concerning the impact of their reputation as well as the proper alignment of

incentives, investment banks are depicted as skillful experts able to identify synergy gains in

complex deals thus influencing announcement period returns.

2.2. Earnout financing

Information Asymmetry constitutes one of the major issues in Mergers and Acquisitions as it

may lead to an adverse selection effect. In his study, Hansen (1987), demonstrated that

valuation risk, sourced from information asymmetry, can be controlled through the method of

payment used to finance an acquisition. However, none of the payment methods mentioned

above makes the financing of the acquisition conditional upon post-merger performance of

the target firm. In an earnout contract, an acquirer buys the target in two stages. An

upfront payment of a large proportion of the agreed transaction value (in cash, stock or a

mixture of the two) and a relatively smaller performance contingent earnout (usually cash). The

second stage payment is made over a time period varying between three and five years

contingent on the target reaching agreed milestones. Cain et al. (2011) report that the earnout

component can be as high as 33% of the total purchase consideration.

Kohers and Ang (2000) and Cain et al. (2011) for the US as well as Barbopoulos and

Sudarsanam (2011) for the UK, report that earnout deals generate higher returns to acquiring

firms than cash or stock acquisitions. Within the same studies it is pointed out that earnouts are

more likely to be used in acquisitions where targets are more difficult to value (private

companies), there is higher information asymmetry, the target belongs to an unrelated

industry and the target has many intangible assets which are complex to value.

More specifically, Kohers and Ang (2000) illustrate that targets with higher information

asymmetry are suitable for the use of earnout and that this payment method results in

positive event period abnormal returns for the acquiring firm. In their study, Cain et al. (2011)

find that the earnout size is positively related to the uncertainty of target value, the choice of

performance measure and the importance of target manager effort while the earnout length is

negatively related to proxies for the noise in the performance signal. Reuer et al. (2004)

indicate that the likelihood of the use of an earnout contract increases with the uncertainty

faced by the bidding firm concerning the target value. When looking at the effect of earnouts

in cross-border acquisitions, Datar et al. (2001) find that foreign bidders of US targets are less

likely to use earnout than US domestic acquirers. This result is due to differences in

accounting practices and corporate governance techniques between countries. Within the same

context, Mantecon (2009) indicates that the use of earnouts yields positive announcement

returns to domestic bidders while cross-border acquirers do not benefit from the earnout use as

a means of financing a takeover.

Furthermore, Barbopoulos and Sudarsanam (2011) indicate that US bidders enjoy

significant gains from corporate takeovers when they utilize earnouts as an acquisition payment

currency. US bidder gains from cross-border acquisitions appear significantly higher

than gains from domestic acquisitions when bidders employ earnout correctly to finance their

acquisitions. The correct use of earnout in international acquisitions provides a well

calibrated payment technique that deals effectively with the higher level of adverse selection

and moral hazard associated with cross-border acquisitions than with domestic targets. Finally

when examining the valuation effects of mergers of US financial institutions, Barbopoulos and

Wilson (2011) find that bidders enjoy higher announcement period returns when using

earnouts compared to other forms of payment. More specifically, earnout-financed bids

outperform their non-earnout matching counterparts and the higher the size of the earnout

contract, as a fraction of the total transaction value, the higher the announcement period

returns of bidders.

Overall, earnout financing constitutes a payment mechanism that reduces the probability of

overpayment and increases the probability of success during the integration period as part of the

transaction value is dependent on the future performance of the target firm. Despite their

complexity, when properly implemented earnouts are proven to be able to generate greater

announcement period returns outperforming alternative means of payment and offer an intuitive

solution in cases with substantial overpayment risk.

2.3. Testable hypotheses

As mentioned above, earnout contracts do not constitute a simple and easy-to-use method of

payment. They require intense negotiations between bidders and targets in order to agree upon

the performance-related thresholds regarding the second payment. The complexities

regarding the valuation of the target, the uncertainty related to its post-acquisition operating

performance, caused by moral hazard issues, and the avoidance of an adverse selection effect,

related to information asymmetry, render this method of payment appropriate for acquisitions

of targets exposed to the above risks.

Given the high percentage of the earnout component (up to 33% of the total purchase

consideration according to Cain et al. (2011) along with the willingness of target shareholders to

bind themselves to the post-acquisition performance of the merged entity, it becomes

evident through numerous studies that this financing decision is optimal for acquisitions of

difficult to value targets such as unlisted firms, or firms belonging to industries characterized

by high intangible assets (Kohers and Ang, 2000). Therefore, the implementation of an earnout

provision, especially in cases similar to the above that have been proven to be optimal for its use,

results in acquirors experiencing greater gains than their non-earnout counterparts. Consequently,

our first hypothesis is as follows:

H1: Bidders financing M&A bids with an earnout provision yield higher announcement period

returns to their shareholders, compared to returns generated from M&A bids financed with non-

earnout payment methods.

On the other hand, the role of financial advisors involved in the deal has been thoroughly

examined. Nevertheless, certain conflict of interest issues arise, mostly dealing with whether

these consulting firms have the right incentives when advising a concentration (Allen et al. 2004,

Kolasinski et al. 2008, Bodnaruk et al. 2009). Despite the above, investment banks, acting as

financial advisors have been proven to be better able to distinguish synergy gains in potential

targets and have also been shown to be able to generate greater announcement period returns( Bao

and Edmans, 2011).

More specifically, financial advisors have been established to be playing a significant role in

takeover outcomes. The “skilled advice hypothesis” indicates that investment banks consulting

the acquiring firm are better able to identify synergy gains in targets. Subsequently, this

consulting superiority is reflected through the “investment bank fixed effect” in the

announcement period abnormal returns.

Earnouts, as a means of financing an acquisition, have also been proven to be able to extract

synergy gains from difficult to value targets due to the ability of their design to maintain the

target firm’s management. The performance-related thresholds that have been agreed upon in the

contract incentivize the target’s administration towards the realization of those goals which,

ultimately, benefit both parties. It can therefore be the case that financial advisors, due to their

skillful expertise in identifying synergy gains in target firms and implementing the appropriate

instruments to extract them, are better able to notice such opportunities in high valuation risk

firms. Due to the complexities surrounding such deals, sourced from information asymmetry and

moral hazard, an earnout provision is subsequently implemented, as the investment bank realizes

its appropriation for such cases and is skillful enough to design the contract efficiently. Therefore,

our second hypothesis consists of two parts and is as follows:

H2a: Deals involving an earnout provision and a financial advisor consulting the acquiror yield

greater announcement period returns to the bidding firms’ shareholders than deals involving a

financial advisor consulting the acquiror and not involving an earnout payment.

H2b: Deals involving an earnout provision and a financial advisor consulting the acquiror yield

greater announcement period returns to the bidding firms’ shareholders than deals not involving

a financial advisor and also not involving an earnout payment.

Taking into consideration the above, it can be the case that the announcement period

abnormal returns accrued to the bidding firms’ shareholders in earnout-financed concentrations

are influenced by the presence of financial advisors. Therefore, it needs to be addressed whether

the significant outperformance of deals involving this contingent payment method sources from

the earnout itself, or whether it is also related to the presence of an investment bank consulting

the bidder. Earnouts constitute a complex transaction method that requires intense negotiations

and can easily result in a failure or a legal dispute. Therefore, the acquiring firm alone may not

possess the necessary expertise to properly design and implement this payment method in contrast

to the financial advisor. As a result, the market’s reaction reflects both the investment bank fixed

effect and the risk-mitigating properties of an earnout provision. The latter indicate a potential

complementarity between earnouts and financial advisors which leads to greater announcement

period returns. The market acknowledges the investment bank’s expertise and in addition to the

risk hedging properties of earnouts reacts positively as depicted in the acquiring firms’ wealth

gains.

3. Methods

In this sub-section discussed the methodology used to test the aforementioned hypotheses and

derive the main results of the paper. Methods for calculating abnormal returns around M&As

announcements are therefore presented. Subsequently, the univariate and multivariate methods of

analysis are outlined.

3.1. Measurement of abnormal returns

The commonly used method in estimating abnormal returns in response to an event requires long

estimation period returns series that is free from the effect of the event under analysis.

Nevertheless, the current sample is composed of many bids announced by the same acquiring

firm within a small period of time. Therefore, such method cannot be applied. Alternatively, in

line with numerous studies with similar sample characteristics (Fuller et al. 2002, Faccio et al.

2006) the announcement period abnormal returns are estimated using the market-adjusted model

(equation 1):

(1)

Where: ARi,t, is the abnormal return to bidder I on day t, Ri,t is the return on firm/bidder I at day t,

Rm,t is the value-weighted market return index at day t. The announcement period cumulative

excess return is the sum of the abnormal returns in the 5-day window (t-2 to t+2) surrounding the

bid announcement, day t=0, as outlined in equation 2:

∑ (2)

3.2. Univariate and multiple regression analysis

At first, the announcement period abnormal returns of UK acquirers are analyzed by method of

payment used (cash, stock, mixed, and earnout) and target listing status (private, public, and

subsidiary). The analysis is also divided into sub-categories related to the presence of a financial

advisor for the acquiring firm. Subsequently, differentials between the gains to bidders using

cash, stock or mixed payments for different target listing statuses and the gains to bidders using

earnouts are calculated. To assess the comparative performance of different groups of acquirers,

the difference in means is tested using the t-test along with the difference in medians using the

Wilcoxon test.

Subsequently, we further examine the impact of financial advisors in earnout financed

deals on a multivariate framework where the effects of several other factors in shaping the

announcement period bidders’ returns are simultaneously controlled. Extant literature

demonstrates that a number of control variables influence acquirer’s value gains. Such factors

include the method of payment, bidding firm’s age, the relative size of the deal, the target firm’s

listing status, the industry affiliation of the merging firms and the target’s domicile and operating

legal system. Furthermore, this empirical paper includes certain new factors that aim to explain

the bidding firm’s returns. They consist of the existence of a financial advisor, a further

exploration of the listing status of the immediate parent of subsidiary targets, the legal system in

which the target firm operates, and certain key financial ratios of the bidder such as the cash ratio

(total cash and cash equivalent over total assets) and debt ratio (total debt to common equity). In

particular, the following equation is estimated in a nested form:

∑ (3)

Where: the intercept, α, accounts for the abnormal returns accrued to bidders after accounting for

the effects of all the explanatory variables Xi. The dependent variable, CAR, is the five-day

announcement period cumulative abnormal return of acquirers. The vector of explanatory

variables, X, includes a number of factors that are known to affect bidders’ gains. Such factors

consist of:

Earnout as a method of payment (EA): Previous research indicates that acquisitions of

difficult to value targets, such as private targets operate in the high-tech industry generate greater

bidder announcement period returns when financed with an earnout component (Kohers and Ang,

2000). Therefore to account for the potential implications of the occurrence of an earnout on

bidder gains, a variable taking the value of one when there exists an earnout and zero otherwise is

included in equation (3).

Bidder’s age (BAGE): Information asymmetry between the merging firms influences

heavily the announcement period returns accrued to bidders’ shareholders. Draper and Paudyal

(2008) and Zhang (2006) suggest that investors tend to have more information on firms with

longer trading history which results in lower information asymmetry. Therefore the age of the

acquirer (measured by the log of number of days between the announcement day and the first

record of the company in Datastream) is included in equation (3).

Relative size of the deal (LRS): Current literature (Fuller et al. 2002) depicts that the

bidders’ gains are positively related to the relative size of the bid (measured as the log of the deal

value over the market value of the acquirer). Hence this variable is included in equation (3).

Diversification (CROSSIND): Extant literature (Barbopoulos et al. 2012) shows that if

target and bidder belong to the same industrial sector, the integration of the two firms should be

easier and the synergy gains higher. On the other hand, firms acquiring targets operating in

unrelated sectors may also gain from diversification. Therefore to control for the potential effect

of corporate diversification a dummy variable taking the value of one for cross-industry bids (i.e.

target and acquirer do not have the same 2-digit SIC code) and zero otherwise is included in

equation (3).

Target’s domicile (CROSSB): Domestic and international deals have been proven to be

affecting the bidding firm’s value gains (Conn et al. 2005). Domestic acquisitions can be

perceived as less risky than crossborder acquisitions as there is less information asymmetry about

the target firm, especially in those cases where it is a listed firm. Therefore, in order to control for

the effect of international deals and how they affect bidder returns a dummy variable that equals

one when bidder and target reside in different countries and zero otherwise is included in equation

(3).

Target’s operating legal system: Current literature (Barbopoulos and Paudyal, 2012)

depicts that the target firm’s operating legal system interacts with the bidding firm’s

announcement period returns as the legal tradition of the target's domicile interacts with target's

status and method of payment in shaping the net gains of acquirers. Therefore dummy variables

that equal one when the acquired company’s legal system is the Common Law or the Civil Law

and zero otherwise are introduced in equation (3).

Additional indicator variables: Certain new factors are introduced in this paper that aim

to explain the wealth effects arising to bidding firms’ shareholders. The main variable under

examination consists of the advisors involved in the deal and, more specifically, financial

advisors. Therefore a dummy variable for the existence of financial (AFAE) advisors is included.

Furthermore, the target’s listing status has been proven by empirical studies to be influencing the

announcement period acquirer returns. Dummy variables are hence, created for those cases where

the acquired firm is private (PRIVATE) or subsidiary. Finally, key financial ratios of the

acquiring firm (such as the ratio of total cash and cash equivalents to its total assets,

CASH_RATIO, and the ratio of total debt to its common equity, DEBT) signal information

about the bidder’s financial status and probability of default. Therefore, they are included in

equation (3). A more detailed presentation of all parameters used in this paper is given in the

Table 1.

4. Data and Results

This section presents the data and offers a discussion of the main findings of our empirical

investigation. Section 4.1 outlines the sample of M&As transactions and presents descriptive

statistics. Section 4.2 discusses the results from the univariate analysis. Finally in section 4.3 we

present and discuss the results from the multivariate cross-sectional analysis.

4.1. The sample

The sample consists of takeover bids announced by UK public firms between 01/01/1986

and 31/12/2010 and recorded by the Security Data Corporation (SDC). SDC records 31,658 cases

of M&As bids involving UK acquirers within the sample period. In order for a bid to remain in

the sample, it must meet the following criteria: first, the acquirer is a UK public company listed

in the FTSE and has a market value of at least $1 million, measured four weeks prior to the

announcement of the bid. To avoid the insignificant effects of very small deals, the transaction

value needs to be at least $1 million. To ensure that the acquirer enjoys control of the target, only

acquisitions of at least 50 percent of target equity are included in the sample. Targets of all

listings (listed, private and subsidiary) and domicile (UK or non-UK) are included in the

sample. To avoid the confounding effects of multiple bids, bids announced within 5-days

surrounding another bid by the same bidder are excluded. Furthermore, the daily stock price

and market value of the acquirer need to be available from Datastream. Buybacks and

repurchases are excluded from the sample. Cases where either bidder or target firms belong to

regulated industries (Healthcare, Financials, Energy and Power) or to the government are

excluded from the sample. Finally, considering the method of financing the acquisition, the

percentage of unknown, provided by SDC, must be less than 100% so that the sum of cash, stock

and other payments equals 100%. The above criteria are satisfied by 6,432 bids and remain in the

sample. 1,505 bids comprise earnout contracts. 2.053 of these deals involve financial advisors

while only 331 of those belong in the earnout financed deals.

4.2. Sample Characteristics

4.2.1. All Acquisitions

Table 2 depicts the frequency of acquisitions in the UK takeover market according to the acquired

firm’s location and industry as well as the method of payment used, the presence of a financial

advisor for either bidder or target and the acquired firm’s listing status. Earnout financed

acquisitions constitute 23.4% of the sample. The remaining 76.6% involves cash, stock or mixed

payments. Nevertheless, the use of earnouts has increased dramatically since the mid 80’s

reaching 31.73% and 33.72% of total M&As activities in the years 2006 and 2007 respectively

as compared to just 14.05% in 1987. Cash along with mixed payments constitute the two

dominating methods of payment (accounting for 44.37% and 48.94% respectively) followed by

stock which accounts for just 6.69%. A reason for the relatively low percentage of

acquisitions fully financed with stock is the severe regulatory regime in the UK which

generally prohibits acquisitions fully financed with equity.

Almost 32% of the sample deals include a financial advisor for the acquiring firm and

27.16% a financial advisor for the target firm. The above indicate that one third of all acquisitions

is accompanied by a financial advisor rendering its influence substantial in takeover outcomes.

Furthermore 331 deals are characterized by the simultaneous presence of both an earnout and a

financial advisor.

Cross-border acquisitions, i.e. UK bidders acquiring non-UK targets appear

relatively frequently (28.81% of sample) while acquisitions of non-listed targets, i.e. acquisitions

of private and subsidiary targets, seem to be dominating the sample accounting for

90.58% (59.56% and 31.02% respectively). More specifically, 9.2% of all acquisitions

consist of subsidiary targets with a private immediate parent, 13.85% consist of subsidiary

targets with a public immediate parent and 7.85% consist of subsidiary targets with a

subsidiary immediate parent. The remaining 9.42% consists of acquisitions of public firms.

Cross-industry concentrations represent 49.32% of the sample while 49.32% of the deals

involve acquisitions of targets belonging to industries characterized by high intangible assets (i.e.

High-Tec, Consumer Products and Services and Media and Entertainment).

4.2.2. Acquisitions involving earnouts

In this section the sample is restricted to only those deals involving an earnout payment. In

Table 3, deals financed with earnouts are dominated by acquisitions of private targets

accounting for 85.12% and followed by acquisitions of subsidiary targets representing

13.75%. Furthermore, subsidiary targets whose immediate parent is a private firm account

for 5.78%, subsidiary targets whose immediate parent is a subsidiary firm account for 2.26%

and subsidiary targets whose immediate parent is a public firm account for 5.71%.

Acquisitions of public targets, very rarely involve an earnout payment as they account for

merely 1.13%. Cross-border acquisitions represent 20.93% of earnouts indicating their

appropriation for domestic cases (Datar et al. 2001). Considering the target’s industry

classification, almost 50% of earnout financed deals involve targets belonging to a different

industry than the acquiring firm while almost 60% of acquired companies belong to industries

characterized by high intangible assets.

Considering the advisors involved in the deals, almost 22% of acquirers are being

advised by a financial advisor while 25.65% are being advised by a legal advisor Finally,

considering target advisors, almost 17% of targets are being consulted by investment banks. The

use of financial advisors seems to be following the general trend of earnout use. As in the case of

earnout occurrences, the presence of a financial advisor for the acquiring firm increases

dramatically during the ten years between 1991 and 2001 and subsequently drops, in the

aftermath of the dot-com bubble. Subsequently, it once again increases during the years 2004-

2007 only to start dropping again during the credit crunch crisis of 2008.

4.2.3. Deal Characteristics

Table 3 presents mean and median deal values according to target listing status, method of

payment, industry, target firm’s domicile and financial advisor presence. The average deal value

of all deals is around $134 million with a median value of almost $11 million. Deals involving

public targets exhibit the highest average and median deal values ($920 million and $83.45

million respectively) followed by deals involving subsidiary and private targets ($102.4 million

and $13.8 million and $26.4 million and $7.95 million respectively). Earnout financed

acquisitions exhibit average and median deal values of $22.5 million and $8.85 million

respectively which are the lowest when compared to the alternative means of payment (cash,

stock or mixed). Nevertheless, this is somewhat expected as acquisitions financed with an earnout

provision mostly involve small unlisted targets which render the transaction value relatively

small.

Considering the financial advisors involved in the deal process, it is shown that deals

including a financial advisor are much larger in size than those which do not. More specifically,

the presence of a financial advisor for the acquiring firm increases the average deal value from

$21.22 million to $375 million while the median transaction value also increases from $7 million

to $36.17 million. When there exists a financial advisor for the acquiring firm along with an

earnout provision the average and median deal value is greater than when there exists an earnout

provision without an advisor reaching $51.19 million and $17.13 million respectively. The same

observation persists across all different target listing statuses indicating that earnout deals which

include a financial advisor for the bidder are much larger in size than earnout deals without one.

Nevertheless these values are significantly smaller than when there exists a financial advisor for

the bidder without the presence of an earnout. In those cases the average and median deal values

climb to $437.32 million and $43.65 million respectively.

Considering the target firm’s domicile, cross-border acquisitions exhibit much larger

average and median deal values ($301.63 million and $18.88 million) than domestic ones ($66.39

million and $9 million). More specifically, cross-border acquisitions of public targets exhibit an

average deal value of $2.1 billion and median value of $190.16 million. Acquisitions involving

targets in the same industry exhibit a higher average deal value than when the target firm belongs

to a different industry ($187.57 million and $79.27 million respectively). Nevertheless this

difference is not as substantial when looking at the median values ($11.68 million and $10.43

million respectively). Finally acquisitions of firms that belong to a high intangible assets industry

are characterized by lower average and median deal values than crossindustry or same industry

acquisitions ($67.1 million and $10.2 million respectively).

The above simplistic analysis demonstrates that the vast majority of earnout financed

M&As deals is composed of domestic acquisitions of unlisted targets belonging to an industry

characterized by high intangible assets, and hence valuation risk, while almost 22% of them are

accompanied by an investment bank consulting the acquirer. Furthermore, earnout deals are much

smaller in size than non-earnout ones. Nevertheless, when there exists an investment bank

consulting the acquirer, earnout financed acquisitions increase significantly in size across all

different target listed statuses. The above effect of the presence of a financial advisor on the

bidding side of the deal is also present in non-earnout acquisitions verifying the conclusion that

deals including financial advisors are generally larger in size.

4.3. Univariate analysis of announcement period returns

Table 5 reports the findings of our univariate analysis of announcement period returns. Results

are presented according to method of payment used and target listing status. The analysis is also

divided into sub-categories related to the presence of a financial advisor for the acquiring firm.

Subsequently, differentials between the gains to bidders using cash, stock or mixed payments for

different target listed statuses and the gains to bidders using earnouts are calculated as well as the

gains to bidders using a financial advisor and the gains to acquirors not using one.

Panel A reports the mean and median 5-day announcement period returns for all

acquisitions. Earnout financed deals are depicted to be outperforming alternative means of

payment averaging 1.70% with a median return of 0.64% which is also the highest among other

financing methods (consistent with earlier studies such as Kohers and Ang, 2000; Barbopoulos

and Sudarsanam, 2012). Earnout deals involving unlisted targets, which are depicted by literature

to be optimal for their use, illustrate an average and median return of 1.70% and 0.63%

respectively. When compared to alternative means of payment earnout financed deals involving

such targets only outperform cash deals with just the average difference being significant at

1.00%. Among acquisitions involving earnouts, deals involving a subsidiary target with a private

immediate parent demonstrate the greatest average and median abnormal returns (2.83% and

1.22% respectively both significant at 1%). This is somewhat expected as bidders acquiring such

firms are exposed to greater valuation risk due to the complicated status of the target. Therefore

the implementation of an earnout contract should be regarded as more appropriate thus resulting

in a positive market reaction.

In order to assess the impact of financial advisors specifically, Panel B restricts the

sample to only those cases where there exists a financial advisor for the acquiring firm. Earnout

financed deals still depict the greatest average and median abnormal returns (2.48% and 1.18%

respectively, both significant at 1%) which are also much larger than those presented in panel A.

Furthermore, under the presence of a financial advisor bids including this contingent payment

method outperform those that do not by 1%, significant at 5%, while the median difference is

0.54% also significant at 5%. Furthermore, deals involving an earnout provision and unlisted

targets now depict much larger average and median returns than before (2.57% and 1.27%

respectively, both significant at 1%). Finally, once again, deals involving subsidiary targets with a

private immediate parent yield the greatest returns among the earnout group (5.63% and 3.98%

respectively, both significant at 1%) and are also much larger than those in panel A. The above

results indicate that the presence of financial advisors significantly increases the wealth gains

accrued to the bidding firms’ shareholders in earnout financed acquisitions. Especially in those

cases where earnout literature depicts their use to be optimal, i.e. unlisted targets, the average and

median returns corresponding to acquiring firms’ equity owners are significantly increased.

In order to better assess the influence of financial advisors, in Panel C, the sample is

restricted to those cases where there does not exist a financial advisor consulting the bidding firm.

This separation should give us a first glimpse of the impact that investment banks have on

bidders’ wealth gains in earnout financed concentrations. Earnout financed acquisitions now

depict the smallest average and median returns between all Panels (1.48% and 0.53%

respectively, both significant at 1%). When compared to non earnout financed acquisitions, deals

involving this contingent payment are depicted to be outperforming only in terms of average

returns by 0.45%, significant at 5%. Interestingly, and in contrast to the case where there exists a

financial advisor in Panel B, earnout financed deals when compared to stock financed deals do

not exhibit a significant outperformance. As shown by Hansen (1987), stock financing offers

some risk-mitigating advantages, especially in cases with asymmetric information that favor the

acquiring firms’ shareholders. Under the presence of a financial advisor, a significant

outperformance of earnout financed bids is observed whereas when there does not exist an

investment bank advising the acquiring firm the aforementioned outperformance becomes

insignificant. Furthermore, acquisitions of subsidiary targets with a private immediate parent

financed with an earnout now exhibit much lower average and median returns (1.94% significant

at 5% and 0.69% significant at 1% respectively).

Finally, Panel D exhibits the differences in portfolio returns between cases that include a

financial advisor and those that do not. In earnout financed deals, the presence of an investment

bank yields greater mean and median announcement returns by 1% significant at 5% and 0.66%

also significant at 5% respectively. In non earnout acquisitions the presence of a financial advisor

only increases the mean return by 0.44%, significant at 5%, while the median increase is rendered

insignificant. Acquisitions, characterized by literature to be optimal for earnout use, such as those

involving unlisted targets, are also benefited by the presence of a financial advisor in terms of the

wealth gains accrued to the bidding firms’ shareholders. More specifically, the existence of an

investment bank translates to a 1.11% increase in average bidder gains, significant at 1%, and a

0.77% increase in median acquiror returns, significant at 5%. Once again subsidiary targets with a

private immediate parent as well as subsidiary targets with unlisted immediate parents which,

intuitively alone, constitute cases with substantial valuation and overpayment risk are presented to

be benefited the most of financial advisor presence. The existence of an investment bank yields

an excess average return of 3.69%, significant at 5%, and an excess median return of 3.29%,

significant at 1% in the case of private immediate parenthood as well as an excess average return

of 4%, significant at 1%, and an excess median return of 3.48% in the case of unlisted immediate

parenthood.

The above indicate that the presence of a financial advisor on the acquiring side of the

deal significantly benefits the wealth gains accrued to the bidding firms’ shareholders in earnout

financed acquisitions. Financial advisor presence translates to an excess return of 1% in deals

involving this contingent payment method. More specifically, in cases characterized by literature

to be optimal for the use of earnouts, such as deals involving unlisted targets (Kohers and Ang,

2000), the existence of an investment bank along with the occurrence of an earnout payment

significantly increase bidders’ abnormal returns. It is of particular importance to explain this

effect.

Recent literature on financial advisor involvement in M&As transactions depicts their

significant influence on deal outcome and bidder value gains. The ‘skilled advice’ hypothesis,

established by Bao and Edmans (2011), indicates that investment banks, acting as financial

advisors, are more capable of identifying synergy gains in targets and that this superiority of

theirs is reflected through the ‘investment bank fixed effect’ in the announcement period returns.

It can be argued, therefore, that in cases where there exists a substantial synergy gain but cannot

be easily extracted, due to high information asymmetry, financial advisors possess the necessary

skills which enable them to realize the appropriation of an earnout contract. Due to their skillful

expertise, the complex process of designing the contract and negotiating its terms is managed

successfully and the earnout is implemented. The market’s perception of the above process is

positive leading to a substantial wealth gain to the bidding firm’s shareholders. The latter can also

be verified by cases involving unlisted targets and, more specifically, subsidiary targets with an

unlisted immediate parent. Such cases depict a substantial valuation risk, due to the complicated

listing status of the target firm. The presence of a financial advisor along with an earnout

provision translated to a 4% increase in bidders’ stock gains and can be perceived as the

“investment bank fixed effect” complementing the already positive effect of earnout choice on

announcement period equity returns.

Another aspect of financial advisor involvement that can explain the positive effect of

their presence in earnout financed acquisitions relates to McLaughlin (1990, 1992) and his

findings regarding the prestige and the incentives of investment banks towards deal completion. It

is illustrated that in almost 80% of advisory contracts, the fee is contingent upon deal completion

incentivizing the investment bank to focus on completing the deal, increasing the risk of

overpayment, at the expense of synergy gains. In light of the above, he also demonstrates that

firms using less prestigious financial advisors offer significantly smaller premiums for takeover

targets and enjoy higher announcement period returns. The choice to use an earnout in a complex

case under the presence of a financial advisor can be perceived as signaling to the market that the

financial advisor is indeed aiming towards the realization of synergy gains between the merging

parties. Furthermore, as mentioned above, deals involving earnouts are smaller in average and

median transaction value than those that do not and, consequently, do not involve many top-tier

financial advisors which focus mainly on large concentrations. Therefore, along with their skillful

expertise discussed earlier, financial advisors, when involved in earnout financed deals are also

likely to signal to the market that their aims consist of the realization of synergy gains and the

reduction of overpayment risk and not deal completion which can potentially damage their

clients. The market’s perception of the above is positive leading to a substantial excess wealth

gain.

4.4. Multiple regression analysis of announcement period returns

Table 6 reports the findings of our multivariate analysis which means to control for several

factors simultaneously shaping bidders’ returns in the announcement period. In order to deal with

heteroscedasticity in the models, the Ordinary Least Squares estimation outputs are

calculated and standard errors are adjusted using the White heteroscedasticity consistent

standard errors. The results obtained from the cross-section analysis support the findings of the

univariate analysis and also further corroborate the significant impact of the presence of financial

advisors in earnout financed deals.

Models 1-4 illustrate the results of the analysis for the whole sample while, in Models 5

and 6 the sample is restricted to only earnout financed acquisitions. Model 1 depicts the effect of

certain established variables in earnout literature on bidders’ announcement period returns

without taking into consideration the effect of financial advisors. The earnout presence has an

insignificant effect. Nevertheless, deals involving targets operating in industries concentrated in

intangible assets positively influence the market’s reaction as do cases involving unlisted targets

that constitute the vast majority of M&As deals in the UK. Cross-border and cross-industry

acquisitions have an insignificant effect as does the legal system in which the target firms operate.

This is somewhat expected as the vast majority of targets operate in a Common Law legal

framework. The bidding firm’s age has an insignificant effect illustrating the uniqueness of

merger announcements regardless of the life cycle of the firm in contrast to its market value

which has a negative and significant effect depicting that the larger the acquiring firm’s equity

value the smaller the impact of the deal on the bidding firm’s stock. The size of the transaction

positively influences announcement period bidder returns, illustrating that larger deals have a

more positive impact on acquirors’ wealth gains, as does the bidding firm’s cash ratio. The latter,

as a substantial indicator of the firm’s liquidity, strongly influences the market’s assessment of an

acquisition depicting that acquiring firms which are highly liquid enjoy greater announcement

period returns.

Considering the effect of financial advisor involvement on bidders’ gains, it can be seen

in Model 2 that the presence of an investment bank on the acquiring side of the deal has a positive

and significant impact on acquirors’ announcement period returns. This finding relates to current

literature pointing out the positive effect of financial advisor involvement on bidders’ wealth

gains. In order to address a potential endogeneity issue regarding the effect of financial advisors,

the variable corresponding to the deal value was not included in Models 2-6 due to evidence in

current literature that relates the size of the transaction to the financial advisors involved in the

deal process. Furthermore, it can be seen in Models 3 and 4 that the simultaneous presence of an

earnout provision along with a financial advisor as well as the simultaneous presence of an

earnout provision, a financial advisor and an unlisted target positively and significantly influence

bidders’ abnormal returns in contrast to just the presence of an earnout which has a positive but

insignificant effect. The latter provide evidence that in cases involving an investment bank

advising the bidder, the implementation of an earnout and more specifically, the implementation

of an earnout provision along with a high information asymmetry target lead to significantly

positive market reaction. This can be perceived as providing evidence on the complementarity of

earnout contracts and financial advisors illustrating the impact of the “skilled advice” hypothesis

on bidders’ wealth gains.

In order to better assess the influence of the presence of financial advisors on bidders’

announcement period returns, in Models 5 and 6 the sample is restricted to only earnout financed

acquisitions. Furthermore, an additional variable introduced consists of the relative earnout size

compared to the transaction value of the deal. As can be seen in both regression outputs, the

relative earnout size imposes a negative and significant effect on bidders’ value gains. This is

somewhat expected as the latter has been proven to be positively linked to the valuation

uncertainty of the deal (Cain et al. 2011). Therefore, as it increases in size it can be perceived as

signaling to the market the complex character of the concentration thus negatively influencing the

market’s reaction. Considering the impact of financial advisors in earnout financed acquisitions,

as can be seen in Model 5, the presence of an investment bank leads to a positive and significant

effect on acquirors’ announcement period returns as does the simultaneous presence of a financial

advisor and an unlisted target firm in Model 6. The above findings illustrate the significantly

positive effect of investment bank presence in earnout financed acquisitions as well as the

market’s positive assessment of their involvement in complex cases with substantial valuation

risk.

Overall, the above analysis verifies the results of the univariate analysis and depicts the

significance of financial advisor presence in earnout financed deals. Financial advisors can be

perceived as being better able to distinguish when the implementation of an earnout contract is

suitable while also being skillful enough to design this complex payment mechanism efficiently.

The market’s perception of the above process is very optimistic yielding greater gains to the

bidding firms’ shareholders as illustrated in both a univariate and a multivariate context.

5. Conclusion

This paper presents new evidence on the announcement period returns of a large sample of UK

M&As involving deals financed with alternative methods of payment (such as cash, stock, mixed

and earnout) and either advised by financial advisors or not. A univariate analysis of bidders’

announcement period returns compared the wealth gains accrued to acquirors financing bids

using earnouts to counterparts using traditional methods of payment. Similarly, a comparison of

announcement period performance of deals advised by investment banks across all payment

methods, but mainly when an earnout is utilized, was also conducted. The results of the above

analysis suggest that bidders enjoy greater announcement period returns when, (a) financing deals

with an earnout provision, (b) there exists a financial advisor consulting them, and (c) when the

latter occur simultaneously.

A multiple regression analysis assesses the interaction effect of earnout involvement,

with or without the involvement of financial advisors on bidders’ announcement period returns,

while controlling for other transaction- and merging institution-specific characteristics. The main

findings of the multiple regression analysis suggest that the interaction of earnout financing with

the presence of financial advisors yields the highest gains to bidders’ shareholders. The results

also suggest that bidders’ returns are sensitive to several other explanatory variables known as

important determinants in shaping bidders’ returns.

Overall, our results suggest that the interaction between earnout financing and financial

advisor presence in M&As involving mainly unlisted target firms provides a more effective

valuation risk treatment. We argue that this interaction leads to a significant reduction of adverse

selection and moral hazard issues arising from asymmetric information problems between the

merging partners and thus increase the odds of M&As success. The above can be perceived as

providing evidence for a potential complementarity between earnouts and financial advisors

which is priced as good news in the marked.

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Reuer, J.J. and Ragozzino, R. (2005): Share Contracts in Corporate Acquisitions: Working Paper,

Kenan-Flagler Business School, University of North Carolina, Chapel Hill, North Carolina. Servaes, H., 1991. Tobin’s q, agency costs, and corporate control: an empirical analysis of firm

specific parameters. Journal of Finance 46, 409–419. Shleifer, Andrei, and Robert W. Vishny, 2003, Stock market driven acquisitions, Journal of

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Financial Economics 70, 313-349. Travlos, N.G., 1987. Corporate takeover bids, method of payment, and bidding firm’s stock

returns. Journal of Finance 52, 943–963.

Table 1: Variable Definitions

The table defines the variables used in the empirical analysis, and indicates the data source used. SDC denotes

Thomson-Reuters SDC M&A database. With a dummy variable, a sample observation without the value of 1 has the

value of 0. Age, MV, DV, EAV, RS and Debt are log transformed in subsequent regressions.

Variable

Type/Name Description

Data

Source

All Refers to the entire sample analysed in this paper. SDC

Age Number of days between day the bidder is first recorded on

Datastream and bid’s announcement day. Datastream

Market Value

(MV)

Bidder’s market value of equity at four weeks prior to bid’s

announcement, in millions dollars. Datastream

Deal Value (DV) Bid’s transaction value, in millions dollars. SDC

Earnout Value

(EAV)

Value of earnout contract, in millions dollars (proxy for size of

earnout). SDC

Relative Size

(RS) Ratio of DV to MV.

SDC &

Datastream

Relative earnout

size (RES) Ratio of EAV to DV SDC

Crossborder

(CROSSB)

Dummy = 1 with a UK bidder and non-UK target, and = 0

when both bidder and target are UK institutions (= Domestic). SDC

Domestic (DOM) Dummy = 1 with a UK bidder and a UK target, and = 0 when

target is not a UK company. SDC

Crossindustry

(CROSSIND)

Dummy = 1 when bidder and target do not share the same two-

digit SIC code and = 0 otherwise. SDC

Same Industry

(SAME)

Dummy = 1 when bidder and target share the same two-digit

SIC code and = 0 otherwise. SDC

Intangible

(INTANG)

Dummy = 1 when target belongs to a high intangible assets

industry (Media and Entertainment, Consumer Products and

Services, High Technology) and = 0 otherwise.

SDC

Cash Dummy = 1 when payment is 100% cash. SDC

Stock Dummy = 1 when payment is 100% stock exchange. SDC

Mixed Dummy = 1 when payment is mixture of cash, stock, and other

methods of payment excluding earnout. SDC

Earnout (EA)

Dummy = 1 when payment includes earnout in addition to

cash, stock, or mixed, and = 0 otherwise (= Non-Earnout)

(NEA).

SDC

Non-Earnout

(NEA)

Dummy = 1 with full-cash, or full-stock, or mixed payment

without EA, and = 0 when EA is included. SDC

Private (PRIV) Dummy = 1 if target is private, and = 0 otherwise. SDC

Public (PBL) Dummy = 1 if target is publicly listed, and = 0 otherwise. SDC

Subsidiary (SUB) Dummy = 1 if target is a subsidiary institution, and = 0

otherwise. SDC

Subsidiary with

private immediate

parent (SUBPRI)

Dummy = 1 if target is a subsidiary institution with a private

immediate parent, and = 0 otherwise. SDC

Subsidiary with

public immediate

parent (SUBPUB)

Dummy = 1 if target is a subsidiary company with a public

immediate parent, and = 0 otherwise. SDC

Subsidiary with

subsidiary

immediate parent

(SUBSUB)

Dummy = 1 if target is a subsidiary company with a subsidiary

immediate parent, and = 0 otherwise. SDC

Subsidiary with

unlisted

immediate parent

(SUBUNLI)

Dummy = 1 if target is a subsidiary company with an unlisted

immediate parent (private or subsidiary), and = 0 otherwise. SDC

Unlisted (UNLI) Dummy = 1 if target is not a listed firm, and = 0 otherwise. SDC

AFAE Dummy = 1 when there exists a financial advisor for the

bidder, and = 0 otherwise. SDC

NAFAE Dummy = 1 when there does not exist a financial advisor for

the bidder, and = 0 otherwise. SDC

TFAE Dummy = 1 when there exists a financial advisor for the target,

and = 0 otherwise. SDC

ALAE Dummy = 1 when there exists a legal advisor for the bidder,

and = 0 otherwise. SDC

TLAE Dummy =1 when there exists a legal advisor for the target, and

= 0 otherwise. SDC

EA_AFAE

Dummy = 1 when there exists a financial advisor for the

bidder and the transaction includes an earnout provision, and =

0 otherwise.

SDC

EA_AFAE_UNLI

Dummy = 1 when there exists a financial advisor for the

bidder, the transaction includes an earnout provision and the

target is unlisted, and = 0 otherwise.

SDC

NEA_AFAE

Dummy = 1 when there exists a financial advisor for the

bidder and the transaction does not include an earnout

provision, and = 0 otherwise.

SDC

Experience Dummy = 1 when the bidder has used and earnout provision at

any time in the past, and =0 otherwise. SDC

Common

Dummy = 1 when the acquisition is crossborder and the

target's nation follows the English Common Law legal system,

and = 0 otherwise.

SDC

Cash_ratio Bidder's total cash and cash equivalents to its total assets Datastream

Debt Bidder's total debt to common equity. Datastream

Table 2: M&A Activity by Location, Industry, Method of Payment and Advisor Presence

The table presents the UK M&A activity according to the target institution’s domicile (Domestic versus Crossborder), industry (Same Industry versus Crossindustry and

Intangible), currency of financing (earnout, and non-earnout which includes cash, stock and mixed payments), advisor presence (afae versus tfae and alae versus tlae as well as

ea_afae versus nea_afae) and target listed status (private, public, subsidiary, subpub, subpri and subsub). Table 1 provides the definitions of variables.

Year ALL DOM CROSSB SAME CROSSIND INTANG EA NEA CASH STOCK MIXED AFAE EA_AFAE NEA_AFAE PRIV PBL DUB SUBPUB SUBPRI SUBSUB

1986 39 25 14 19 20 10 0 39 21 11 7 24 0 24 19 11 9 5 1 3

1987 121 98 23 53 68 33 17 104 50 30 41 47 1 46 60 30 31 16 6 9

1988 286 224 62 108 178 93 81 205 128 23 135 62 13 49 175 43 68 37 14 17 1989 351 262 89 146 205 121 76 275 173 31 147 89 13 76 185 42 123 68 31 24

1990 215 159 56 91 124 70 43 172 110 15 90 76 9 67 97 20 98 53 22 23

1991 138 115 23 56 82 37 28 110 57 16 65 54 6 48 58 20 60 32 16 12 1992 145 113 32 52 93 37 22 123 64 11 70 45 4 41 69 5 71 30 17 24

1993 217 168 49 85 132 62 31 186 97 16 104 81 11 70 101 15 101 45 25 31

1994 272 211 61 130 142 83 42 230 124 24 124 88 12 76 148 20 104 44 29 31 1995 288 209 79 111 177 100 67 221 114 17 157 80 11 69 167 20 101 45 34 22

1996 324 243 81 145 179 114 70 254 142 22 160 91 16 75 206 26 91 40 25 26

1997 398 277 121 173 225 149 88 310 159 23 216 105 22 83 252 31 115 55 29 31 1998 423 293 130 224 199 158 67 356 222 19 182 150 15 135 228 43 152 67 45 40

1999 437 300 137 253 184 188 74 363 200 23 214 192 25 167 233 66 137 55 41 41

2000 418 279 139 236 182 230 95 323 160 37 221 168 23 145 237 42 138 65 45 28 2001 304 208 96 168 136 172 95 209 106 18 180 124 32 92 192 24 88 32 32 24

2002 224 169 55 119 105 121 57 167 115 12 97 74 17 57 145 15 64 32 22 10 2003 191 124 67 123 68 111 47 144 93 7 91 53 13 40 110 17 64 29 21 14

2004 223 157 66 130 93 116 68 155 88 12 123 60 9 51 154 9 60 20 23 17

2005 300 218 82 180 120 173 89 211 131 13 156 89 20 69 213 27 60 24 22 14 2006 312 210 102 187 125 190 99 213 132 9 171 81 12 69 223 18 70 26 27 17

2007 347 232 115 207 140 188 117 230 135 13 199 102 24 78 249 26 71 29 29 13

2008 188 115 73 111 77 109 59 129 90 9 89 41 10 31 143 9 36 17 13 6 2009 100 67 33 60 40 60 26 74 45 12 43 31 6 25 61 16 22 8 4 10

2010 171 103 68 93 78 91 47 124 98 7 66 46 7 39 106 11 54 17 19 18

Total 6432 4579 1853 3260 3172 2816 1505 4927 2854 430 3148 2053 331 1722 3831 606 1988 891 592 505

% 100 71.19 28.81 50.68 49.32 43.78 23.40 76.60 44.37 6.69 48.94 31.92 5.15 26.77 59.56 9.42 30.91 13.85 9.20 7.85

Table 3: Earnout M&A Activity by Location, Industry, Method of Payment and Advisor Presence

The table presents the UK M&A activity involving earnout-financed according to the target institution’s domicile (Domestic versus Crossborder), industry (Same Industry versus

Crossindustry and Intangible), currency of financing (earnout, and non-earnout which includes cash, stock and mixed payments), advisor presence (afae versus tfae and alae versus

tlae) and target listed status (private, public, subsidiary, subpub, subpri, subsub). Table 1 provides the definitions of variables.

Year ALL DOM CROSSB SAME CROSSIND INTANG AFAE PRIV PBL SUB SUBPUB SUBPRI SUBSUB

1986 0 0 0 0 0 0 0 0 0 0 0 0 0

1987 17 16 1 9 8 8 1 14 0 3 3 0 0

1988 81 70 11 32 49 35 13 66 6 9 5 4 0

1989 76 63 13 29 47 37 13 60 3 13 6 4 3

1990 43 36 7 17 26 24 9 32 1 10 5 4 1

1991 28 22 6 5 23 9 6 20 1 7 3 4 0

1992 22 20 2 7 15 3 4 15 0 7 5 2 0

1993 31 27 4 13 18 10 11 19 1 11 4 3 4

1994 42 32 10 16 26 16 12 38 1 3 2 1 0

1995 67 54 13 27 40 34 11 57 1 9 5 3 1

1996 70 57 13 30 40 29 16 63 0 7 5 2 0

1997 88 68 20 39 49 48 22 70 0 18 5 6 7

1998 67 52 15 36 31 32 15 57 0 10 1 6 3

1999 74 57 17 40 34 45 25 61 1 12 3 8 1

2000 95 79 16 45 50 70 23 78 0 17 6 8 3

2001 95 74 21 50 45 71 32 85 0 10 0 6 4

2002 57 44 13 28 29 47 17 46 1 10 4 3 3

2003 47 35 12 26 21 32 13 40 0 7 5 1 1

2004 68 55 13 39 29 39 9 59 0 9 4 5 0

2005 89 69 20 61 28 68 20 85 1 3 1 2 0

2006 99 77 22 56 43 73 12 89 0 10 5 4 1

2007 117 90 27 70 47 76 24 106 0 11 4 6 1

2008 59 42 17 36 23 39 10 56 0 3 2 1 0

2009 26 20 6 15 11 20 6 23 0 3 1 2 0

2010 47 31 16 28 19 27 7 42 0 5 2 2 1

Total 1505 1190 315 754 751 892 331 1281 17 207 86 87 34

% 100 79.07 20.93 50.10 49.90 59.27 21.99 85.12 1.13 13.75 5.71 5.78 2.26

Table 4: Summary Statistics

The table presents mean and median deal values according to target listed status (Private versus Subsidiary and Public), method of payment

(Earnout, Cash, Stock and Mixed), industry (Intangible, Crossindustry, Same Industry), location (Domestic versus Crossborder) and advisor

presence (Afae, Non_Afae, Ea_Afae, Nea_Afae). Table 1 provides definitions of the variables.

ALL EA NON EA CASH STOCK MIXED INTANG CROSSIND SAME CROSSB DOM AFAE NAFAE EA_AFAE NEA_AFAE

ALL N 6432 1505 4927 2854 430 1644 2816 3172 3260 1853 4579 2053 4379 331 1722

% of All - 0.23 0.77 0.44 0.07 0.26 0.44 0.49 0.51 0.29 0.71 0.32 0.68 0.05 0.27

Mean of DV 134.161 22.503 168.272 78.557 209.108 313.237 67.104 79.267 187.574 301.633 66.390 375.066 21.218 51.192 437.321

Median of DV 10.965 8.855 12.110 11.325 15.015 12.955 10.225 10.430 11.680 18.880 9.000 36.170 7.040 17.130 43.665

PRIV N 3831 1281 2550 1299 195 1056 1885 1891 1940 1060 2771 866 2965 265 601

% of All 0.60 0.20 0.40 0.20 0.03 0.16 0.29 0.29 0.30 0.16 0.43 0.13 0.46 0.04 0.09

Mean of DV 26.409 18.668 30.298 24.818 34.316 36.297 21.897 23.895 28.860 40.855 20.883 64.594 15.256 35.926 77.235

Median of DV 7.950 8.450 7.555 7.010 6.650 8.940 8.010 7.500 8.435 12.845 6.840 19.730 6.460 16.560 21.910

SUB N 1995 207 1788 1290 77 422 686 968 1027 605 1390 662 1333 58 604

% of All 0.31 0.03 0.28 0.20 0.01 0.07 0.11 0.15 0.16 0.09 0.22 0.10 0.21 0.01 0.09

Mean of DV 102.370 36.490 109.997 84.500 45.586 199.443 74.182 93.792 110.455 197.575 60.932 248.175 29.960 90.813 263.286

Median of DV 13.830 9.630 14.910 14.155 9.080 17.425 11.905 13.500 14.140 28.970 10.490 47.470 8.950 21.015 49.710

PBL N 606 17 589 265 158 166 245 313 293 188 418 525 81 8 517

% of All 0.09 0.00 0.09 0.04 0.02 0.03 0.04 0.05 0.05 0.03 0.06 0.08 0.01 0.00 0.08

Mean of DV 920.006 140.163 942.515 313.056 504.524 2364.260 395.107 368.878 1508.750 2106.850 386.212 1047.200 95.600 269.609 1059.230

Median of DV 83.450 15.670 87.720 84.720 38.560 226.895 82.250 70.710 119.820 190.165 59.535 108.390 17.340 35.745 113.300

Table 5: Univariate Analysis

The table presents mean and median announcement period 5-day (t-2, t+2) abnormal returns for all acquisitions divided by target listing status. The

analysis is further categorized for those cases where there exists an advisor for the acquiring firm (financial or legal), where there exists a financial

advisor for the acquiring firm, where there exists a legal advisor for the acquiring firm and where there does not exist an advisor for the acquiring firm.

Statistical significance of difference in returns between two groups of bidders is tested using the T-test of equality of means and the Wilcoxon rank sum

test for equality of medians.

Panel A: All Acquisitions

All Cash EA Stock Mixed NEA NEA VS

EA

Cash VS

EA

Stock VS

EA

Mixed VS EA

All Mean 1.30*** 1.08*** 1.70*** 0.73* 1.47*** 1.18*** -0.52*** -0.62*** -0.97** -0.23

Median 0.49*** 0.40*** 0.64*** -0.35 0.7105*** 0.45*** -0.19* -0.2415* -0.99*** 0.07

Number 6432 2854 1505 430 1644 4927

PRIV Mean 1.40*** 0.85*** 1.61*** 1.26** 1.86*** 1.30*** -0.31 -0.76*** -0.35 0.26

Median 0.55*** 0.24*** 0.60*** -0.35 0.98*** 0.52*** -0.08 -0.3655** -0.95* 0.3735*

Number 3830 1299 1280 195 1056 2550

SUB Mean 1.56*** 1.38*** 2.25*** 3.09*** 1.47*** 1.48*** -0.78 -0.87* 0.84 -0.78

Median 0.55'*** 0.52*** 0.76*** 1.32*** 0.35*** 0.53*** -0.23 -0.24 0.56 -0.41

Number 1995 1290 207 77 422 1788

SUBPUB Mean 1.32*** 1.25*** 1.89** 3.21** 0.97* 1.27*** -0.60 -0.62 1.34 -0.90

Median 0.48*** 0.48*** 0.56** 1.87** 0.12 0.45*** -0.11 -0.08 1.31 -0.44

Number 891 586 86 32 188 805

SUBPRI Mean 1.77*** 1.38*** 2.83*** 3.57** 1.78*** 1.59*** -1.24 -1.45* 0.74 -1.06

Median 0.531*** 0.38*** 1.22*** 1.15** 0.60** 0.41*** -0.81 -0.84 -0.07 -0.62

Number 592 353 87 25 127 505

SUBSUB Mean 1.70*** 1.65*** 1.76 0.71 2.00*** 1.70*** -0.06 -0.11 -1.05 0.25

Median 0.704*** 0.85*** 0.40 0.73 0.56** 0.73*** 0.33 0.45 0.33 0.16

Number 505 347 34 17 107 471

SUBUNLI Mean 1.74*** 1.51*** 2.53*** 2.41* 2.10*** 1.64*** -0.89 -1.01 -0.12 -0.43

Median 0.60*** 0.55*** 0.99*** 0.86** 0.70*** 0.60*** -0.40 -0.45 -0.13 -0.29

Number 1097 700 121 42 355 976

UNLI Mean 1.46*** 1.11*** 1.70*** 1.78*** 1.75*** 1.37*** -0.32 -0.58*** 0.08 0.06

Median 0.55*** 0.412*** 0.63*** 0.06** 0.86*** 0.52*** -0.11 -0.22 -0.57 0.22

Number 5825 2589 1487 272 1478 4338

PBL Mean -0.16 0.80* 2.04 -1.08* -1.06* -0.23 -2.27 -1.24 -3.11* -3.1*

Median -0.40 0.18 0.92 -1.15** -0.71 -0.43 -1.34 -0.74 -2.07** -1.63*

Number 606 265 17 158 166 589

Panel B: Acquiror Financial Advisor Exists

All Cash EA Stock Mixed NEA NEA VS

EA

Cash VS

EA

Stock VS

EA

Mixed VS EA

All Mean 1.63*** 1.55*** 2.48*** 0.44 1.72*** 1.47*** -1.01** -0.93** -2.04*** -0.76

Median 0.73*** 0.76*** 1.18*** -0.64 0.96*** 0.64 -0.54** -0.43 -1.83*** -0.22

Number 2053 870 331 225 627 1722

PRIV Mean 2.18*** 1.24*** 2.16*** 2.74** 2.90*** 2.19*** 0.03 -0.92 0.58 0.73

Median 1.10*** 0.77*** 1.08*** -0.04 1.94*** 1.16*** 0.08 -0.32 -1.12 0.86

Number 866 251 265 58 292 601

SUB Mean 2.39*** 2.16*** 4.41*** 2.38 2.23*** 2.19*** -2.22** -2.25** -2.02 -2.18*

Median 1.17*** 1.02*** 2.95*** -0.06 0.99* 0.92*** -2.03*** -1.94*** -3.02* -1.96***

Number 662 388 58 28 188 604

SUBPUB Mean 1.98*** 2.00*** 3.20** 2.18 1.51** 1.87*** -1.33 -1.20 -1.02 -1.69

Median 0.90*** 0.86*** 1.89*** -0.74 0.76** 0.78*** -1.12* -1.04 -2.63 -1.13*

Number 342 210 28 14 90 314

SUBPRI Mean 2.62*** 2.06*** 5.63*** 2.97 2.21*** 2.17*** -3.46* -3.57* -2.66 -3.42*

Median 1.00*** 0.39** 3.98*** 0.12 0.68** 0.38*** -3.6*** -3.59** -3.86 -3.3**

Number 162 82 21 9 50 141

SUBSUB Mean 3.02*** 2.62*** 5.32 1.17 3.58*** 2.88*** -2.44 -2.72 -4.15 -1.74

Median 1.74*** 1.33*** 3.82* 1.60 2.97*** 1.74*** -2.08 -2.49 -2.22 -0.84

Number 157 96 9 4 48 148

SUBUNLI Mean 2.81*** 2.35*** 5.54*** 2.42 2.88*** 2.54*** -3.00* -3.18* -3.12 -2.65

Median 1.31*** 1.13*** 3.90*** 0.81 1.54*** 1.10*** -2.8** -2.76** -3.08 -2.36**

Number 319 178 30 13 98 289

UNLI Mean 2.27*** 1.80*** 2.57*** 2.62** 2.63*** 2.19*** -0.37 -0.77 0.06 0.07

Median 1.12*** 0.82*** 1.27*** -0.05 1.44*** 1.00*** -0.27 -0.44 -1.31 0.17

Number 1528 639 323 86 480 1205

PBL Mean -0.23 0.87* -0.92 -0.90 -1.28** -0.22 0.70 1.79 0.01 -0.36

Median -0.5 0.4 -0.89 -1.26** -0.77* -0.51 0.38 1.29 -0.37 0.12

Number 525 231 8 139 147 517

Table 5 (Continued)

Panel C: Acquiror Financial Advisor Does Not Exist

All Cash EA Stock Mixed NEA NEA

VS

EA

Cash

VS EA

Stock

VS EA

Mixed

VS

EA All Mean 1.15*** 0.88*** 1.48*** 1.04* 1.32*** 1.03*** -

0.45** -0.6*** -0.44 -0.16

Median 0.39*** 0.31*** 0.53*** 0.03 0.56*** 0.37*** -0.16 -0.21 -0.50 0.03

Number 4378 1984 1173 205 1017 3205

PRIV Mean 1.10*** 0.75*** 1.46*** 0.63 1.47*** 1.03*** -0.43* -

0.71*** -0.83 0.01

Median 0.38*** 0.15*** 0.56*** -0.51 0.82*** 0.35*** -0.21 -0.41* -1.06** 0.26

Number 1414 1048 1015 137 764 1949

SUB Mean 1.15*** 1.04*** 1.42*** 3.49*** 0.87** 1.12*** -0.30 -0.37 2.08* -0.55

Median 0.39*** 0.40*** 0.3 2.00*** 0.06 0.40*** 0.10 0.10 1.7*** -0.24

Number 1333 902 149 49 234 1184

SUBPUB Mean 0.92*** 0.83*** 1.22 4.01*** 0.47 0.88*** -0.35 -0.40 2.78 -0.76

Median 0.27*** 0.36** 0.11 3.36*** -0.1 0.33*** 0.23 0.25 3.25*** -0.21

Number 549 376 58 18 98 491

SUBPRI Mean 1.45*** 1.18*** 1.94** 3.91** 1.49* 1.36*** -0.58 -0.76 1.97 -0.45

Median 0.49*** 0.39*** 0.69*** 2.03*** 0.6 0.47*** -0.22 -0.31 1.34 -0.10

Number 430 271 66 16 77 364

SUBSUB Mean 1.11*** 1.29*** 0.48 0.57 0.73 1.16*** 0.68 0.81 0.09 0.25

Median 0.47*** 0.60*** 0.39 0.5 -0.06 0.50*** 0.10 0.21 0.10 -0.45

Number 348 251 25 13 59 323

SUBUNLI Mean 1.30*** 1.23*** 1.54** 2.41 1.16** 1.27*** -0.27 -0.31 0.87 -0.38

Median 0.48*** 0.49*** 0.42 1.15* 0.28 0.49*** 0.07 0.07 0.74 -0.13

Number 778 522 91 29 136 687

UNLI Mean 1.17*** 0.89*** 1.45*** 1.39** 1.33*** 1.06*** -

0.39**

-

0.57*** -0.07 -0.12

Median 0.40*** 0.33*** 0.50*** 0.12* 0.61*** 0.38*** -0.12 -0.17 -0.38 0.10

Number 4297 1950 1164 186 998 3133

PBL Mean 0.26 0.34 4.66* -2.34 0.65 -0.29 -

4.95** -4.33* -7.00** -4.02

Median -0.2 -0.28 4.34 -0.82 0.15 -0.39 -

4.73** -4.62* -5.16** -4.19

Number 81 34 9 19 19 72

Panel D: Acquiror Financial Advisor Exists VS Acquiror Financial Advisor Does Not

Exist

All Cash EA Stock Mixed NEA

All Mean

Diff. 0.48*** 0.67*** 1.00** -0.6 0.4 0.44**

Median

Diff. 0.34** 0.44*** 0.66** -0.67** 0.4 0.27

PRIV Mean

Diff. 1.08*** 0.49 0.7 2.1 1.43*** 1.16***

Median

Diff. 0.72*** 0.62 0.53 0.47 1.13*** 0.81***

SUB Mean

Diff. 1.24*** 1.12*** 2.99*** -1.11 1.36** 1.08***

Median

Diff. 0.78*** 0.62*** 2.65*** -2.06 0.93* 0.52***

SUBPUB Mean

Diff. 1.06*** 1.17*** 1.98 -1.82 1.05 0.99**

Median

Diff. 0.63** 0.50** 1.79** -4.09* 0.86 0.44*

SUBPRI Mean

Diff. 1.17** 0.88 3.69** -0.94 0.72 0.81

Median

Diff. 0.51 0.01 3.29*** -1.91 0.08 -0.09

SUBSUB Mean

Diff. 1.91*** 1.31** 4.84* 0.6 2.85** 1.72***

Median

Diff. 1.27*** 0.73* 3.42 1.1 3.03 1.24**

SUBUNLI Mean

Diff. 1.52*** 1.12** 4.00*** 0 1.72* 1.27***

Median

Diff. 0.83*** 0.65* 3.48*** -0.34 1.26* 0.61**

UNLI Mean

Diff. 1.10*** 0.91*** 1.11*** 1.24 1.31*** 1.13***

Median

Diff. 0.72*** 0.50*** 0.77** -0.16 0.84*** 0.62***

PBL Mean

Diff. -0.49 0.53 -5.58* 1.43 -1.93 0.07

Median

Diff. -0.31 0.68 -5.23* -0.44 -0.92 -0.11

Table 6: Multivariate Analysis

The table presents announcement period 5-day (t-2,t+2) excess returns of bidders are regressed against a set of explanatory variables. Regression outputs

(based on equation 3) are estimated using ordinary least squares with the coefficients adjusted for possible heteroscedasticity using White

heteroscedasticity-consistent standard errors and covariance. The intercept measures the excess returns to bidders after accounting for the effects of all

explanatory variables.

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Constant 0.0083 0.0068 0.0148*** 0.0149*** 0.0284 0.0320

EA 0.0007 0.0013

AFAE 0.0108*** 0.0084*

EA_AFAE 0.0088*

EA_AFAE_UNLI 0.00961** 0.0097**

INTANGIBLE 0.0032* 0.0031* 0.0028 0.0028 0.0052 0.0051

BAGE 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

MV -0.0053*** -0.0036*** -0.0035*** -0.0035*** -0.0057*** -0.0057***

DV 0.0041***

RES -0.00416* -0.0041*

MTBV 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001

UNLISTED 0.0188*** 0.0181*** 0.0115*** 0.0114*** 0.0036 -0.0003

CROSSB 0.0037 0.0037 0.0039 0.0039 0.0050 0.0048

CROSSIND -0.0002 -0.0008 -0.0011 -0.0011 0.0028 0.0028

COMMON -0.0010 -0.0004 -0.0004 -0.0004 -0.0012 -0.0011

CASH_RATIO 0.01946** 0.0202** 0.0214** 0.0214** 0.0176 0.0173

DEBT -0.0004 -0.0001 0.0001 0.0001 -0.0006 -0.0007

F-Test 11.18*** 10.85*** 9.48*** 9.57*** 3.12*** 3.21***

R2 (adjusted) in % 2.26 2.19 1.73 1.75 2.04 2.12

N 6432 6432 6432 6432 1505 1505