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ORI GINAL RESEARCH
Are good financial advisors really good? Theperformance of investment banks in the M&A market
Ahmad Ismail
Published online: 25 December 2009� Springer Science+Business Media, LLC 2009
Abstract The study examines whether prestigious investment banks deliver quality gains
to their clients in a sample of 6,379 US M&A deals. It finds that acquirers advised by tier-
one advisors lost more than $42 billion, whereas those advised by tier-two advisors gained
$13.5 billion at the merger announcement. The results were mainly driven by the large loss
deals advised by tier-one advisors. The evidence indicates that investment banks might
have different incentives when they advise on large deals vs. small deals. The results imply
that market share based reputation league tables, could be misleading and therefore, the
selection of investment banks should be based on their track record in generating gains to
their clients. The findings were consistent with the superior deal hypothesis as tier-one
target advisors outperformed tier-two advisors and the existence of a prestigious advisor on
at least one side of an M&A transaction resulted in higher wealth gains to the combined
entity. Target advisors were able to extract more wealth gains for their clients, which led to
higher combined gains at the expense of the acquirer.
Keywords Investment banks � Prestigious � Gains � Mergers and acquisitions
JEL Classification G34
1 Introduction
The volume of worldwide announced mergers and acquisitions (M&A) soared to over
$3.8 trillion in 2006. On the other hand, imputed advisory fees on completed transactions
exceeded $32.8 billion, 38.5% of which were earned by ten (prestigious) investment
A. Ismail (&)College of Business and Economics, United Arab Emirates University, P.O Box 17555, Al-Ain, UAEe-mail: ahmadismail@uaeu.ac.ae; phd98ai@yahoo.com
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Rev Quant Finan Acc (2010) 35:411–429DOI 10.1007/s11156-009-0155-6
banks1 only, who advised on most of the announced deals.2 These figures show how
hierarchical the investment banking industry is, since few prestigious investment banks
dominate the M&A advisory services. The selection of M&A financial advisors is mainly
driven by their perceived reputation and quality service. In the context of M&A, high
quality products offered by investment banks are those that have greater positive impact on
the clients’ shareholders wealth.3 Therefore, if financial advisors continue providing such
high quality products to their clients, their reputation is enhanced. In turn, the demand for
their products increases resulting in increased market share.
Building on the above, financial advisors’ reputation (their market share) is mainly driven
by how much value they create for their customers. Hence, a key question comes under the
spotlight, that being, how beneficial have top investment banks been to their clients? In other
words, does the selection of ‘quality’ financial advisors result in ‘quality’ value gains to
bidder or target shareholders? To put it bluntly, are good financial advisors really good?
Part of the literature on the role of investment banks in M&A examined the relation
between advisors’ reputation and client shareholders’ gains, and reached contrasting con-
clusions. While recently Ma (2006) investigated only target adviser performance, most
previous studies have focused their analyses on acquirer adviser performance (Servaes and
Zenner 1996; Rau 2000; Da Silva Rosa et al. 2004). In addition, USA acquirer advisor studies
used old and small samples not extending beyond the early 1990s and excluded the acqui-
sitions of non-public targets. Therefore, their results may not be generalized to the total
population of acquisitions. On the other hand, Moeller et al. (2004) documented that because
cumulative abnormal returns (CARs) are equally-weighted, a sample of M&A transactions
generating positive CARs, in fact, could have resulted in large negative dollar gains.
Recently, only Kale et al. (2003) controlled for this issue, however, their study focused on a
very small and outdated sample of acquisitions of listed target firms (324 deals completed
between 1981 and 1994). Moreover, some merger deals during the 1990s merger wave were
peculiar by all standards (excessive premiums, large acquirer losses and large deal values see
e.g. Moeller et al. 2004 and 2005) adding another attraction to investigating the acquirer
financial advisors performance. Therefore conducting a new study using dollar abnormal
returns to investigate the performance of advisors in the M&A process is worth the effort.
I use a sample of 6,379 US M&A deals, for listed and unlisted targets, completed between
1985 and 2004, for which the financial advisor for one party is publicly known.
I control for deal and firm characteristics and find that prestigious acquirer advisors (tier-one)
underperformed tier-two advisors and destroyed more than $42 billion value for acquiring
firms’ shareholders. But it is also found that these huge losses were the result of 178 large loss
deals, and that if these deals were removed from the sample, tier-one advisors could have
outperformed tier-two advisors. A similar conclusion is reached if the bear market period was
excluded from the sample. A key finding of this study is that investment banks might have
different incentives when they advise on large deals vs. small deals as larger merger pre-
miums are found to have been paid in large deals as compared to small ones.4 In contrast, the
results for target advisors were consistent with the superior deal hypothesis as tier-one
investment banks outperformed tier-two advisors. I also find that even in the presence of a
1 Investment banks and financial advisors are used interchangeably in the paper.2 Source: Thomson Financial SDC database, M&A and Advisors Summary Report, Fourth Quarter 2006.3 This is based on the assumption that managers seek shareholders value maximization as their main goal.4 Other explanations for the lower premiums paid in small deals could be related to the possibility thatsmaller firms are more likely in distress, or their managers might accept lower premiums as part of anagreement with the acquirer management to keep their jobs etc…
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tier-one acquirer advisor, target advisors were able to extract more gains for their clients,
which led to higher combined gains at the expense of the acquirer.
The multivariate regressions show that acquirers’ gains are not associated with the
acquirer advisor tier, but they are smaller when the target advisor is tier-one. Conversely,
target gains are positively related to the target advisor’s reputation and to the relative
reputation of the target to the acquirer’s advisor. Combined gains were found to be pos-
itively associated with the high reputation of either party’s advisor and apparently driven
by the target firms’ gains.
The implications of these results are that advisors’ reputation league tables, based on
market share, could be misleading and hence do not necessarily suggest that top-tier banks
will generate high gains to their clients; rather the selection of investment banks should be
based on the performance of those banks in prior acquisitions.
The paper is organized as follows: the relevant literature is reviewed in section two, and
section three presents the methodology and data set. The empirical findings are presented
in section four and the conclusion is drawn in section five.
2 Literature review
Some of the research on the role of investment banks in M&A has examined the effect of
the banks’ reputation on their clients’ returns and found mixed results. The findings
responded to two main conflicting hypotheses, these being namely: the superior deal or the
better merger hypothesis and the deal completion hypothesis. The superior deal hypothesis
argues that more prestigious investment banks, due to their superior expertise in the M&A
market, have the ability to identify better merger partners for their clients and determine
ways to create greater operational and financial synergies. If investment banks’ advice
results in greater wealth to their clients, then their reputation is enhanced. Therefore, this
hypothesis predicts a positive relationship between the reputation of investment banks and
their client’s wealth gain. The deal completion hypothesis, on the other hand, predicts no
such association between reputation and customers’ gain. Because their fees are partially
contingent on the completion of the deal, financial advisors have strong deal completion
incentives. In such case, the financial advisors market share (reputation) will depend on the
number of deals they complete (Rau 2000). However, McLaughlin (1990) argued that even
if investment banks were motivated by fee income, they might not want to increase the
acquisition prices, because this type of behaviour would reduce the value of their repu-
tation capital. On the other hand, Bowers and Miller (1990) found that the combined
wealth gain accruing to both acquirers and targets was larger when either the bidder or the
target employed a first-tier financial advisor. Nevertheless, the authors found that acquirer
shareholders do not generate higher gains if they use a first-tier advisor. On the other hand,
Michel et al. (1991) found that some of the Bulge-bracket advisors outperformed less
prestigious ones but, in general, the degree of prestige of an advisor does not vary directly
with the abnormal returns earned by acquired and acquiring firms. Recently, Rau (2000)
found that, in tender offers, but not in mergers, acquirers advised by first-tier investment
banks earned higher abnormal returns than those advised by second and third-tier banks.
On the other hand, McLaughlin (1992) reported a lower abnormal return for acquirers
with more prestigious investment banks, whereas Servaes and Zenner (1996) did not find
any relation between the acquirer’s abnormal return and the tier of its investment bank.
Rau (2000), for merger deals, and Rau and Rodgers (2002) document a lower
announcement return for deals involving top tier advisors. Similar findings were reported
Are good financial advisors really good? 413
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by Da Silva Rosa et al. (2004) for the Australian market. On the other hand, Kale et al.
(2003) found that the total dollar wealth gain as well as the share of the total wealth
accruing to the bidder (target) increases (decreases) as the reputation of the bidder’s
advisor increases relative to that of the target. They also found that the total dollar wealth
gain is positively related to the reputation levels of both acquirer and target advisors.
McLaughlin (1992) found that the quality of the target investment banks had no sig-
nificant effect on the premium received by target firms; however, the author also reported
that bidders using the services of low-quality investment banks offered substantially lower
premiums. Rau (2000) found no evidence that acquisition premiums and deal completion
rates differed across the tier of the acquirer’s advisor in merger deals. Nevertheless, in
tender offers, Rau (2000) confirmed the findings of McLaughlin (1992) and showed that
using a third-tier investment bank resulted in paying a significantly lower premium and in a
lower deal completion rate than using the services of second or first-tier advisors. The latter
findings are consistent with the deal completion hypothesis, which stems from the agency
conflict between acquirers and their investment banks who may be purely motivated by fee
income.
3 Sample and research methodology
3.1 Sample selection
The sample was collected searching the Thomson Financial SDC Database for all the
M&A deals completed by US public acquirers between Jan 1, 1985 and April 22, 2004.5
Financial institutions were excluded from the sample and only deals with at least
$1 million of disclosed value were selected. The sample included deals that resulted in a
transfer of control where the acquirer’s ownership in the target firm increased above 50%
as a result of the acquisition. The target firm is either a public, private or a subsidiary firm.
Other filtering criteria necessitated that acquirers and public targets had share price data
available on the Center for Research in Security Prices (CRSP) database and on Data-
Stream (for non-US target firms) and that the financial advisors for either party are publicly
disclosed. The final sample consists of 6,379 completed deals.
3.2 Research methodology
Bowers and Miller (1990) and Carter and Manaster (1990) inferred the reputation from the
advisors’ position in tombstone advertisement. Other researchers classified advisors into
various tiers (usually two or three) based on their market share in the takeover market
during the sample period (e.g. Rau 2000; Saunders and Srinivasan 2001; and Kale et al.
2003).6 This research adopts the second approach and uses the investment bank’s market
share as a proxy for its reputation. Similar to Kale et al. (2003) the bidder and target
financial advisors in each transaction are given credit for the full value of the deal. Con-
sequently, tier-one investment banks are defined as the top ten advisors with the largest
market share; all other advisors that are ranked higher than tenth are classified as tier-two.
5 April 22 represented the last date on which the data was available when I collected the sample.6 Carter, Dark, and Singh (1998) show that continuous market share, three-tier market share rankings, andtombstone rankings are highly correlated for the IPO market.
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Moeller et al. (2004) argued that cumulative abnormal returns are equally-weighted and
give the same weight to small and large acquirers making loss-making deals (calculated in
dollar value) look, on average, profitable when actually they are not. Therefore, a sample of
M&A transactions generating an average CAR of 1% might, in fact, have resulted in large
negative dollar gains. Hence, similar to a recent study on the role of financial advisors in
the M&A market (Kale et al. 2003) this paper uses abnormal dollar gains as a performance
measure which is calculated as the market capitalization 2 months prior to the
announcement of the merger multiplied by the cumulative abnormal return in the (-2, ?2)
window.7 The abnormal dollar gain to the target is calculated in a similar manner; how-
ever, the pre-merger toehold presence of the acquirer in the target firm is adjusted for. The
abnormal return is estimated using a standard event study methodology as in Brown and
Warner (1985). The market model is employed and the model’s parameters are estimated
over (-210, -20) interval using the CRSP value-weighted index returns as the benchmark
for US firms and the DataStream index for non-US firms.
3.3 Descriptive statistics
Table 1 contains the summary statistics for the sample. Tier-one advisors that are identified
are very much similar to those recognized by other studies (e.g. Rau 2000; Hunter and
Jagtiani 2003). The table shows that the most prestigious advisor in the sample (Goldman
Sachs) advised acquirers and targets on deals worth nearly $210 and $395 billion
respectively. Tier-one advisors participated in deals which are much larger than those
advised by tier-two. In addition, tier-one advisors seem to dominate the takeover market
with a market share of nearly 60% of the volume total as acquirer advisors and approxi-
mately 65% when representing targets. Tier-one advisors also participate in deals with very
large acquirers.
4 Results
4.1 Performance of acquirer advisors
Table 2 presents the performance of acquirer advisors. I find no consistency between
acquirer advisors’ ranking and the gains generated by their clients. For instance, acquirers
advised by Salomon Smith Barney, ranked fifth within the tier-one advisors, generated the
highest mean dollar gains per deal ($157 million), while the gains generated by those
advised by Morgan Stanley, the second top advisor, were among the lowest. Moreover,
acquirers advised by tier-one investment banks earned mean dollar gains of nearly
-$28 million per deal whereas, acquirers advised by tier-two advisors gained about
$6 million per deal. Aggregating abnormal dollar gains across acquirers, it is found that
firms advised by tier-one advisors lost approximately $42 billion, while those advised by
tier-two advisors enjoyed a total dollar gain of $13.5 billion.
7 Fuller et al. (2002) justifies the use of the 5-day window by the fact that after checking the accuracy of theSDC announcement date they find that for about 92.6% of a random sample of 500 acquisitions the date wasaccurate. However, for the remaining deals it was off by two days at most. I use the 5-day CAR for myanalysis similar to Fuller et al. (2002); however, I also run the tests using other windows and found that myresults are robust. Results and tables are available upon request.
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The worst performers among tier-one banks were Lehman Brothers, Lazard, and
Morgan Stanley since their clients’ losses averaged $178.94 million, $169.55 million and
$158 million per deal, respectively. Those values reflect a total dollar loss of more than
$82 billion. On the other hand, In-House deals resulted in the largest loss per deal of
$826 million, which translates into a total abnormal dollar loss of nearly $115.7 billion.8
At first sight, employing quality investment banks seems to have not resulted in quality
value gains for acquirer shareholders which is consistent with prior research (e.g. Servaes
and Zenner 1996; Rau and Rodgers 2002; and Da Silva Rosa et al. 2004). These gains are
8 I closely investigated the losses of In-House deals and found that they are mainly driven by dealscompleted by very large acquirers, those were Lucent Technologies, Cisco Systems, Intel Corp. and AOL.The abnormal dollar losses of those four acquirers reached nearly $145 billion during the sample period.
Table 1 Descriptive statistics by the type of financial advisors
Financialadvisors
No. ofacquirers
Meandealvalue
Totaldealvalue
Meanacquirersize
No. oftargets
Meandealvalue
Totaldealvalue
Meanacquirersize
Goldman Sachs& Co
251 834 209,434 13,676 376 1,028 386,481 10,961
Morgan Stanley 258 668 172,359 10,619 287 729 209,101 14,790
Merrill Lynch &Co Inc
212 641 135,865 6,870 204 729 148,626 8,123
Credit SuisseFirst Boston
161 796 128,190 5,490 201 656 131,909 13,245
Salomon SmithBarney
84 1,503 126,294 14,089 82 1,047 85,844 15,408
LehmanBrothers
141 456 64,284 7,262 157 375 58,948 11,657
JP Morgan 85 1,788 152,010 16,581 118 570 67,220 13,326
Lazard 86 820 70,486 14,697 101 452 45,696 14,595
DonaldsonLufkin &Jenrette
154 468 72,021 1,518 161 355 57,097 3,367
Bear Stearns &Co Inc
102 222 22,646 4,809 113 401 45,369 8,331
Top 10 advisors(tier 1)
1,534 752 1,153,588 9,203 1,800 687 1,236,291 11,283
Other advisors(tier 2)
2,259 192 433,795 2,333 3,178 167 531,532 5,735
Undisclosed 2,446 112 275,085 7,279 1,359 100 135,516 2,220
In-house deals 140 328 45,955 31,635 42 121 5,084 1,630
The table presents summary statistics for the study sample. Deals are completed between Jan 1985 and April2004 as reported by SDC excluding all financial institutions deals; where the deal value is at least $1 millionand the acquirer gains control of a public, private or a subsidiary target firm. The table names the top ten(tier-one) advisors which were identified by the volume of deals advised during the sample period. Addi-tionally, the distribution is made across four categories. Tier-one advisors, tier-two advisors which are theinvestment banks that did not occupy the first ten positions in terms of market share, In-House deals whichare those with no investment bank retained and undisclosed advisors deals these are the deals for which theadvisor is not reported in SDC database. Deal Value is the value paid for the target firm as reported in SDC;by size I mean market value of equity 2 months prior to the acquisition announcement. Dollar amounts arein millions
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inconsistent with the high ranking of those banks; instead, they support the deal completion
hypothesis, which stems from the agency conflict between acquirers and their investment
banks who may be purely motivated by fee income (Rau 2000).
In order to investigate the performance of acquirer advisors further, I rank investment
banks in the sample based on the mean dollar gains generated by acquiring firms. Similar
to Michel et al. (1991), the analysis is restricted to the advisors who participated in at least
15 M&A transactions during the sample period.9 It is found that only two tier-one banks
rank among the top ten (Salomon Smith Barney, and Merrill Lynch & Co. Inc. ranked
fourth and sixth respectively).
4.2 Does the performance around the internet bubble explain the results?
The speculative internet bubble is believed to have occupied roughly the period of 1995 to
2000, for instance, according to Goldfarb et al. (2006) the NASDAQ index peaked at 5,132
on March 10, 2000 before it crashed on Monday March 13, 2000. Right after the burst of
the bubble, the market rallied downward until around the end of September 2002. These
upward and downward surges in stock markets are worth being taken into account so that
to examine their effects on the results in Table 2. Hence I identify the Internet Bubble
period (Jan 1995 to March 10, 2000) and the bear market period (March 13, 2000 to end of
September 2002). The results in Appendix A show that during the bubble period (Panel A)
tier-one and tier-two acquirer advisors generated large total gains ($61.57 billion and
$25.37 billion, respectively) to their clients and that tier-one advisors outperformed
Table 2 Comparative performance of acquirers financial advisors
Financial advisor No. of acquirers Total dollar gain Mean dollar gain
Goldman Sachs & Co 251 9,190.52 36.62
Morgan Stanley 258 -41,048.26 -159.10
Merrill Lynch & Co Inc 212 23,306.25 109.94
Credit Suisse First Boston 161 -2,288.60 -14.21
Salomon Smith Barney 84 13,200.59 157.15
Lehman Brothers 141 -26,552.11 -188.31
JP Morgan 85 4,318.90 50.81
Lazard 86 -15,463.82 -179.81
Donaldson Lufkin & Jenrette 154 -4,488.72 -29.15
Bear Stearns & Co Inc 102 -2,647.70 -25.96
Top 10 advisors (tier-one) 1,534 -42,472.96 -27.69
Other advisors (tier-two) 2,259 13,546.39 6.00
Undisclosed 2,446 -5,025.85 -2.05
In-house deals 140 -115,681.31 -826.30
The table presents the performance of acquirer financial advisors for deals that were completed between Jan1985 and April 2004 as reported by SDC excluding all financial institutions deals; where the deal value is atleast $1 million and the acquirer gains control of a public, private or a subsidiary target firm. The total dollargain is calculated as the market capitalization 2 months prior to the announcement of the merger multipliedby the CAR (-2, ?2). CAR (-2, ?2) is the 5-day cumulative abnormal returns estimated using the marketmodel. The mean dollar gain is the total dollar gain divided by the number of deals advised by each advisor.Dollar amounts are in millions
9 The ranking tables are available upon request.
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tier-two advisors in that period. Conversely, the performance outside the bubble period
(Panel B) shows huge acquirer losses irrespective of the advisor tier however, larger losses
are generated by tier-one advisors compared to tier-two advisors (-$104 billion vs.
-$11 billion). Such results imply that the findings in Table 2 are mainly driven by the
performance outside the bubble period.
In Panel C, the results for the bear market period (March 13, 2000 until Sept. 30, 2002)
lead to very interesting conclusions, these are, the findings in Panel B are mostly explained
by the performance after the bubble burst. For instance, for tier-one (tier-two) advisors,
nearly 77% (55%) of the losses recorded in Panel B appear to have been incurred during
the bear market period. On the other hand, if I compare the results in Panel C with the
earlier findings in Table 2, I conclude that if the bear market period is excluded from the
sample (Panel D), most of the losses will be converted into gains and most importantly,
earlier results that tier-one acquirer advisors lag behind tier-two advisors will be inverted.
4.3 Does size matter?
Tier-two banks attract the smaller bidders who earn higher abnormal returns than large
acquirers (Moeller et al. 2004). In addition, tier-one advisors attract large acquirers, which
are the source of large dollar losses (Moeller et al. 2005). Therefore, it is worthwhile
investigating the size effect on the results in Table 2. I define small and large acquirers as
the first and the fourth quartile of the sample, respectively. Table 3 (panel A) shows that in
terms of total dollar gains, acquirers advised by tier-two investment banks outperform
those advised by tier-one advisors regardless of their size, large or small ($17,062 million
vs. -$45,528 million and $2,466 million vs. $307.45 million respectively). Additionally,
the same pattern is observed for the mean dollar gains ($55.58 million vs. -$75.25 million
and $3.04 million vs. $1.73 million, respectively). Therefore, it does not seem that the
earlier results reported in Table 2 were driven by size.
4.4 Do the advisors’ incentives differ when they take on large deals vs. small deals?
Rau (2000) argued that financial advisors have strong deal completion incentives as their
fees are partially contingent on the completion of the deal. But, McLaughlin (1990)
contended that even if investment banks are motivated by fee income, they may not want to
increase the acquisition prices, because this type of behaviour would reduce the value of
their reputation capital. I reason that perhaps the trade-off between hurting the reputation in
the future, and receiving a one-time higher fee today, differs between large and small deals.
In other words, for a large enough deal, the investment banks might want to maximize the
fee they receive even if that means that their reputation will suffer in the future. On the
flipside, smaller deals might not present a high enough incentive for the advisors to take
advantage of their clients so in those cases they may have a higher incentive to keep the
premium lower in order to build their reputation.
I inspect the performance of investment banks when they advise on large deals as
opposed to small deals. Small and large deals are defined as the first and the fourth quartile
of the sample respectively. Table 3 (panel B) indicates that large deals result in smaller
dollar gains to the acquirers, irrespective of the investment bank tier.
The comparison across the investment banks tier reveals, once again, that tier-one
advisors lag behind tier-two investment banks in both large and small deals sub-samples,
owing to larger gains generated by their clients (-$17 billion vs. -$55.5 billion and
$9.5 billion vs. $1.85 billion respectively). Furthermore, I investigate whether value
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creation in small deals vs. value destruction in large deals are driven by the merger
premium. In this respect, the premium paid for public firms is computed as the deal value,
as reported by SDC, divided by the market value of equity for the target firm 2 months
prior to the deal announcement date. It is found that the mean premium paid in large deals
(99.35%) is significantly larger than that paid in small deals (63.61%), (P-value being
0.0018). Additionally, because the premium results in troubling outliers, Moeller et al.
(2004) and Officer (2003) truncate it so that it takes values between zero and two. This
procedure was followed and it emerged that the mean truncated premium paid in large
deals (74.38%) is also significantly larger than that paid in small deals (61.44%), (P-value
being 0.0031). The analysis was replicated to learn whether the results hold for each
advisor tier. The earlier findings were confirmed for tier-two advisors as the corresponding
merger premiums were 97.62 and 53.3% for large and small deals respectively, the
Table 3 Comparative performance of acquirers financial advisors by acquirer size and deal size
Financial advisor No. Total dollar gain Mean dollar gain
Panel A: acquirer gain sorted by acquirer size large and small
Large acquirers
Top 10 advisors (tier-one) 605 -45,528.41 -75.25
Other advisors (tier-two) 307 17,061.59 55.58
Undisclosed 621 -12,614.13 -20.31
In-house deals 63 -115,791.66 -1,837.96
Small acquirers
Top 10 advisors (tier-one) 178 307.45 1.73
Other advisors (tier-two) 811 2,466.14 3.04
Undisclosed 585 893.51 1.53
In-house deals 21 99.91 4.76
Panel B: acquirer gain sorted by deal size large and small
Large deals
Top 10 advisors (tier-one) 785 -55,449.55 -70.64
Other advisors (tier-two) 472 -17,002.93 -36.02
Undisclosed 293 -54,328.76 -185.42
In-house deals 45 -56,332.20 -1,251.83
Small deals
Top 10 advisors (tier-one) 83 1,847.96 22.26
Other advisors (tier-two) 635 9,486.01 14.94
Undisclosed 847 52,151.24 61.57
In-house deals 30 6,253.17 208.44
The table presents the performance of acquirer financial advisors for deals that were completed between Jan1985 and April 2004 as reported by SDC excluding all financial institutions deals; where the deal value is atleast $1 million and the acquirer gains control of a public, private or a subsidiary target firm. In Panel A thedistribution is made by acquirer size small vs. large where small and large represent the smallest and thelargest 25% of the transactions in the sample respectively measured by acquirer market value 2 months priorto the announcement of the merger. In Panel B the distribution is made by deal size small vs. large wheresmall and large represent the smallest and the largest 25% of the deals in the sample respectively measuredby consideration paid. The total dollar gain is calculated as the market capitalization 2 months prior to theannouncement of the merger multiplied by the CAR (-2, ?2). CAR (-2, ?2) is the 5-day cumulativeabnormal returns estimated using the market model. The mean dollar gain is the total dollar gain divided bythe number of deals advised by each advisor. Dollar amounts are in millions
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difference being significant at the 1% level. But for tier-one advisors it was found that the
difference between the mean premium paid in large and small deals was not significant at
the conventional levels as the P-value was 0.1071.10
4.5 Are the results affected by large loss deals?
Moeller et al. (2005) found that the losses of acquiring firm shareholders from 1998 to
2001, wiped out all the gains made between 1990 and 1997. The authors showed that these
losses are caused by a few large loss deals. Therefore, the possibility that the results from
this study are driven by large loss deals is examined, adopting the criteria for ‘large loss
deals’ used by Moeller et al. (2005), those being transactions that result in a dollar loss of
at least $1 billion for acquiring firm shareholders. One hundred and seventy-eight (178)
such deals were identified. Those resulted in an accumulated loss of nearly $870 billion for
the acquiring firm shareholders.11 On the other hand, out of the 178 large loss deals, the
share of tier-one advisors was 80 deals ensuing in a total loss of about $250 billion, while
tier-two advisors’ share was 22 deals that accumulated a total loss of $49 billion.12 Table 4
shows that when these deals were excluded, acquirers advised by tier-one advisors gen-
erated a much larger dollar gain than their counterparts who were advised by tier-two
investment banks ($207 billion vs. $62.8 billion).
4.6 Determinants of acquirer abnormal wealth gains
It is worthwhile accounting for other factors such as deal and firm characteristics and
examining whether the findings of the earlier univariate analysis still hold in a multivariate
setting. Kale et al. (2003) used the total abnormal dollar gain as their dependent variable,
but in order to control for the influence of outliers, they used a trimmed sample by deleting
extreme values from both sides.13 This procedure was adopted and therefore, the sample
was trimmed by deleting 5% of the largest and smallest wealth gains. Three regression
models were run using the following independent variables:
In order to examine the effect of the advisors’ reputation on the acquirer wealth gains
three dummy variables are used set equal to one if the acquirer advisor is tier-one, the
target advisor is tier-one, and the target advisor is tier-one while the acquirer advisor is tier-
two (superior reputation of target advisor), zero otherwise. Other variables include dum-
mies set equal to one if the target is public, or a subsidiary firm; the method of payment is
cash, or equity; the target and acquirer share the same two-digit SIC codes (related
industries); the target is a foreign company, the deal attitude is hostile as defined in the
SDC database, and whether the acquirer had a toehold, 5% ownership, in the target firm
prior to the acquisition announcement. Additional variables include the relative size of the
10 For tier-one advisors’ clients, the mean premium paid in large deals was 100.8% while that paid in smalldeals was 42.42%. The difference was not significant as there were only 11 small deals advised by tier-onebanks.11 Similar to Moeller et al. (2005), over the 20-year period of the study, most of the losses (87%) werefound to have taken place between 1998 and 2001. The aggregate losses accumulating from large loss dealsbetween 1998 and 2001 reached nearly $757 billion created from 127 deals.12 The remaining losses were created in In-House deals and Undisclosed advisor deals ($173 billion and$398 billion respectively).13 Kale et al. (2003) followed another procedure that is: they ranked bidder’ wealth gains in ascending orderand used each deal’s rank as their dependent variable. I used the same method and found that the resultswere robust.
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target to acquirer and the acquirer size (Ln (equity)). Year and one-digit SIC code dummies
are included in all models but are not reported.
The results are presented in Table 5 where the coefficients for the acquirer reputation
dummy in models (1) and (2) are not significantly different from zero, which indicates that
employing highly reputed advisors does not result in larger abnormal dollar gains to the
acquiring firm shareholders. There is no need to adjust for large loss deals, since a trimmed
sample is used which already excludes large loss deals. The negative coefficient for the
target advisor reputation dummy in model (2) indicates that the higher the reputation of the
target advisor, the lower the acquirer dollar gains. This result implies that the target advisor
might have negotiated a higher premium for his client which resulted in a lower return for
the acquirer. The latter finding is supported by the negative coefficient (although not
significant) on the superior reputation dummy of the target advisor in model (3) which,
consistent with Kale et al. (2003), signifies that when the target advisor is more reputable
than that of the acquirer, lower gains are accumulated for the acquirer firms. The coeffi-
cient on cash deal is positive and significant in all models, suggesting that such transactions
generate higher gains than equity and mixed financing acquisitions. The coefficient on
equity deals is negative but significant only in model (1) implying that equity offers are less
value-adding than cash offers. The significant negative coefficients on the public deals
dummy support the previous evidence that the acquisitions of public firms result in lower
returns than the takeover of subsidiary and private firms (e.g. Moeller et al. (2004), Fuller
et al. (2002). Moreover, the coefficient of the size variable (Ln (Acq. equity) is signifi-
cantly negative in model (2), being consistent with earlier findings of a size effect (Moeller
et al. 2004).
Table 4 Comparative performance of acquirers financial advisors excluding large loss deals
Financial advisor No. of acquirers Total dollar gain Mean dollar gain
Goldman Sachs & Co 236 66,396.90 281.34
Morgan Stanley 241 23,460.22 97.35
Merrill Lynch & Co Inc 208 32,556.19 156.52
Credit Suisse First Boston 147 20,871.63 141.98
Salomon Smith Barney 79 32,586.89 412.49
Lehman brothers 132 11,031.18 83.57
JP Morgan 78 19,582.42 251.06
Lazard 84 -1,445.94 -17.21
Donaldson Lufkin & Jenrette 151 -1,037.01 -6.87
Bear Stearns & Co Inc 98 3,394.64 34.64
Top 10 advisors (tier-one) 1,454 207,397.1 142.639
Other advisors (tier-two) 2,237 62,834.9 28.08891
Undisclosed 2,383 393,232.2 165.0156
In-house deals 127 57,703.41 454.3576
The table presents the performance of acquirer financial advisors for deals that were completed between Jan1985 and April 2004 as reported by SDC excluding all financial institutions deals and excluding deals thatresult in acquirer dollar loss of at least $1 billion; where the deal value is at least $1 million and the acquirergains control of a public, private or a subsidiary target firm
The total dollar gain is calculated as the market capitalization 2 months prior to the announcement of themerger multiplied by the CAR (-2, ?2). CAR (-2, ?2) is the 5-day cumulative abnormal returns estimatedusing the market model. The mean dollar gain is the total dollar gain divided by the number of deals advisedby each advisor. Dollar amounts are in millions
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4.7 Performance of target advisors
In this section I examine whether the conclusions about acquirer advisors’ performance are
maintained when these banks advise target firms. Table 6 shows that targets advised by
tier-one investment banks generate, on average, $119.94 million per deal compared to the
$28.65 million earned by tier-two advisors’ clients. These figures translate into total dollar
gains of $63.3 billion and $27.1 billion for targets advised by tier-one and tier-two
investment banks, respectively. Additionally, it is found that Goldman Sachs & Co. leads
tier-one advisors with nearly $22 billion total dollar gains generated for its target clients. In
sum, these results, contrary to those of the acquirers’ advisors, are supportive of the
superior deal hypothesis.
Similar to the procedure that I use for acquirer advisors, I also rank target advisors. The
rankings of target advisors show that JP Morgan, a tier-one advisor, ranks first with a mean
Table 5 Determinants of acquirer wealth gains
(1) (2) (3)
Intercept 9.221 45.904** 46.886**
Acquirer advisor tier-one 3.850 9.415
Target advisor tier-one -15.306**
Target advisor tier-one and acquireradvisor tier-two
-9.556
Shares -10.796** -6.063 -5.890
Cash 11.399*** 24.759*** 24.763***
Public -20.059*** -28.033*** -26.007***
Private 0.607 -5.463 -3.806
Industry relatedness -0.853 7.144 7.126
National -5.519 -7.288 -8.459
Hostile -13.266 -9.549 -10.515
Relative size 0.328 -2.699 -3.354
Toehold 5.622 16.215 16.064
Ln (acquirer equity) 0.046 -6.114*** -6.328
Adj R-Sq 0.0148 0.0203 0.0184
F-value 5.68*** 4.75*** 4.71***
Number of observations 3,431 2,173 2,173
The table presents ordinary least square regressions of the total dollar gains for the acquirer shareholders fordeals completed by US acquirers between Jan 1985 and April 2004 as reported by SDC excluding allfinancial institutions deals where the deal value is at least $1 million and the acquirer gains control of thetarget firm. The sample was trimmed by deleting 5% of the largest and smallest wealth gains. The inde-pendent variables include dummies for acquirer advisor tier, the target advisor tier, the target advisor tierrelative to acquirer advisor tier, cash, shares, public, private, industry relatedness, national, hostile, andtoehold that take the value one if acquirer advisor is tier-one, the target advisor is tier-one, the target advisoris tier-one while the acquirer advisor is tier-two, for acquisitions using pure cash, pure equity, acquisitions ofpublic targets, private targets, acquisitions of firms that share the bidder the same two-digit SIC code,acquisitions of US targets, hostile acquisitions as defined in SDC, and deals where the acquirer had at least5% ownership in the target firm prior to the acquisition, respectively. Relative size is the target market valueof equity divided by the acquirer market value of equity 2 months prior to the acquisition announcement,and Ln (Equity) is the natural logarithm of the acquirer market value of equity 2 months prior to the dealannouncement. I also include year and one-digit SIC code dummies in all models but do not report them
***, **, * Significant at the 1%, 5% and 10% respectively
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dollar gain of $218.79 million. Additionally, contrary to the ranking of the acquirers’
advisors, the comparisons based on the mean dollar gains and even the total dollar gains
were very much consistent with the advisors’ reputation. It is found that eight tier-one
banks rank among the top ten target advisors by the mean dollar gains earned by their
clients.14
4.8 Determinants of target abnormal wealth gains
Table 7 presents the findings on the effect of advisor reputation on target abnormal wealth
gains after controlling for various deal and firm characteristics as in Table 5. The findings
lend support to the univariate results in Table 6 as the coefficient on the target advisor
reputation dummy is positive and significant in models (1) (2) and (3).15 Moreover, similar to
Kale et al. (2003), it is found that when the target advisor is more reputable than the acquirer,
target gains are bound to be higher, as in model (4) the coefficient of the superior reputation
dummy is significant at the 5% level. The equity payment dummy which is negative and
significant in model (4) only, indicates that equity exchange offers result in lower dollar gains
than cash and mixed settlement deals, which is consistent with the standard M&A literature
(see for example Huang and Walkling 1987; Franks et al. 1991). However, the cash payment
dummy is significantly negative in models (2), (3) and (4) implying that cash settlement deals
Table 6 Comparative performance of target financial advisors
Financial advisor No. of targets Total dollar gain Mean dollar gain
Goldman Sachs & Co 134 21,869.15 163.20
Morgan Stanley 87 10,951.60 125.88
Merrill Lynch & Co Inc 55 5,784.43 105.17
Credit Suisse First Boston 60 8,160.49 136.01
Salomon Smith Barney 27 -1,315.00 -48.70
Lehman Brothers 41 3,199.78 78.04
JP Morgan 24 5,250.92 218.79
Lazard 19 3,340.60 175.82
Donaldson Lufkin & Jenrette 52 2,787.08 53.60
Bear Stearns & Co Inc 29 3,301.76 113.85
Top 10 advisors (tier-one) 528 63,330.81 119.94
Other advisors (tier-two) 943 27,106.25 28.65
Undisclosed 64 460.24 7.19
In-house deals 10 151.85 15.19
The table presents the performance of target financial advisors for deals that were completed between Jan1985 and April 2004 as reported by SDC excluding all financial institutions deals; where the deal value is atleast $1 million and the acquirer gains control of a public target firm
The total dollar gain is calculated as the market capitalization 2 months prior to the announcement of themerger multiplied by the CAR (-2, ?2). CAR (-2, ?2) is the 5-day cumulative abnormal returns estimatedusing the market model. The mean dollar gain is the total dollar gain divided by the number of deals advisedby each advisor. Dollar amounts are in millions
14 The ranking tables are available upon request.15 The number of observations in Model 2 is smaller than in Model 1 because the sample in Model 1 is atrimmed sample where 5% from both sides of the distribution of acquirer abnormal dollar gains areexcluded; whereas in Model 2 only large loss deals are excluded.
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result in lower gains than mixed offers.16 The hostile dummy is also positive and significant
as such deals are accompanied with higher merger premiums. The negative and significant
coefficient of the toehold dummy in models (1) and (3) indicates that toehold presence
reinforces the bidder’s position during the deal negotiation process, or it could lessen
information asymmetry about the true performance and value of the target firm. In the same
vein, Ismail (2008) found that deals with acquirer toehold result in paying lower premiums.
The significant positive coefficient of the industry relatedness dummy implies that industry
Table 7 Determinants of target wealth gains
(1) (2) Excluding largeloss deals
(3) (4)
Intercept -58.422*** -153.865*** -83.862*** -102.515***
Acquirer advisor tier-one 5.538
Target advisor tier-one 29.728*** 54.705*** 33.809***
Target advisor tier-one and acquireradvisor tier-two
12.675**
Shares 1.404 -13.454 -6.137 -7.697*
Cash -4.399 -29.994** -8.254*** -8.559*
Industry relatedness 6.249** 11.217 12.015*** 14.694***
National 3.427 8.303 8.272 16.853**
Hostile 18.725*** 95.483*** 26.424** 33.240***
Relative size 7.337*** 18.594*** 7.549*** 9.624***
Toehold -14.131** -27.825 -15.811* -14.498
Ln (acquirer equity) 10.664*** 25.844*** 14.271*** 17.475***
Adj R-Sq 0.2845 0.1253 0.311 0.2525
F-value 59.36*** 23.28*** 43.71*** 36.58***
Number of observations 1,321 1,400 948 948
The table presents ordinary least square regressions of the total dollar gains for the target firm shareholdersfor deals completed by US acquirers between Jan 1985 and April 2004 as reported by SDC excluding allfinancial institutions deals where the deal value is at least $1 million and the acquirer gains control of thetarget firm. The sample was trimmed by deleting 5% of the largest and smallest wealth gains. The inde-pendent variables include dummies for acquirer advisor tier, the target advisor tier, the target advisor tierrelative to acquirer advisor tier, cash, shares, industry relatedness, national, hostile, and toehold that take thevalue one if acquirer advisor is tier-one, the target advisor is tier-one, the target advisor is tier-one whilethe acquirer advisor is tier-two, for acquisitions using pure cash, pure equity, acquisitions of firms that sharethe bidder the same two-digit SIC code, acquisitions of US targets, hostile acquisitions as defined in SDC,and deals where the acquirer had at least 5% ownership in the target firm prior to the acquisition, respec-tively. Relative size is the target market value of equity divided by the acquirer market value of equity2 months prior to the acquisition announcement, and Ln (Equity) is the natural logarithm of the acquirermarket value of equity 2 months prior to the deal announcement. Model (2) controls for large loss deals;these are defined as those that result in acquirer dollar loss of at least $1 billion. I also include year and one-digit SIC code dummies in all models but do not report them
***, **, * Significant at the 1%, 5% and 10% respectively
16 The negative coefficient on the cash payment dummy may look contradictory to the standard M&Aliterature. However, it is worthwhile noting that such literature uses the CAR as a dependent variable, whilethis study uses the dollar gains which are a function of both the CAR and the deal size. Moreover, aunivariate analysis of target mean dollar gains controlling for the method of payment shows that those gainsare larger for mixed offers, than for equity offer which are also larger than for cash deals ($102.07 million,$68.94 million and 65.81 million, respectively).
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focus deals are more favourably received by the market than diversified acquisitions. The
acquirer size and relative size coefficients are both significantly positive. On the other hand,
the acquirer advisor reputation does not seem to have a significant effect on the target wealth
gain as the coefficient is insignificant in model (3).
4.9 Can inference be drawn from the differential reputation of acquirer
and target advisors?
In this section the analysis is restricted to deals that are either advised by tier-one or tier-
two advisors, that is, In-House and Undisclosed deals are excluded. The performance of
investment banks is analyzed across the tier of the target and the acquirer advisors
simultaneously, using, in addition to target and acquirer gains, the combined dollar gains
for both parties.
Table 8 shows that even in the presence of a tier-one acquirer advisor, in terms of total
abnormal dollar gains, acquiring firms lose more (-$28.83 billion vs. -$10.22 billion)
while target firms and the combined entity gain more ($44.77 billion vs. 17.34 billion and
$15.9 billion vs. $7.12 billion, respectively) when targets employ a tier-one advisor than
when they utilize a tier-two bank. The mean dollar gains also show the same outcome.
A very similar pattern of dollar gains is observed when the acquirers employ a tier-two
bank, except that the combined entity’s gain is lower (-$6.9 billion) when targets employ
tier-one banks, which is, obviously, driven by the large acquirer losses in this sub-sample.
However, if the comparison is conducted based on the target advisor’s reputation level,
it is found that, irrespective of the target advisor tier, acquirers’ gains are worse (-$28.8
vs. -$19.1 billion) while the targets and the combined entity’s gains are better ($44.77 vs.
$12.24 billion and $15.94 vs. -$6.94 billion respectively) when acquirers employ a
tier-one advisor than if they use a tier-two investment bank.
Table 8 Simultaneous comparative performance of tier-one and tier two acquirer and target advisors
Acquirer advisor tier
Target advisor tier Tier-one Tier-two
N Total dollargains
Mean dollar gain N Total dollargains
Mean dollargain
Tier-one
Acquirer 282 -28,833.77 -102.25 156 -19,173.20 -122.91
Target 282 44,770.84 158.76 156 12,237.38 78.44
Combined 282 15,937.07 56.51 156 -6,935.83 -44.46
Tier-two
Acquirer 275 -10,221.35 -37.17 341 -2,337.77 -6.86
Target 275 17,340.61 63.06 341 5,573.55 16.34
Combined 275 7,119.26 25.89 341 3,235.78 9.49
The table presents the comparative performance of tier-one and tier-two financial advisors for deals thatwere completed between Jan 1985 and April 2004 as reported by SDC excluding all financial institutionsdeals; where the deal value is at least $1 million and the acquirer gains control of a public, private or asubsidiary target firm. The total dollar gain is calculated as the market capitalization 2 months prior to theannouncement of the merger multiplied by the CAR (-2, ?2). CAR (-2, ?2) is the 5-day cumulativeabnormal returns estimated using the market model. The mean dollar gain is the total dollar gain divided bythe number of deals advised by each advisor. For the combined entity here I define the total dollar gains asthe sum of the gains accruing to each party. Dollar amounts are in millions
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These results imply that target advisors are able to extract more gains for their clients,
which lead to a higher combined gain at the expense of the acquirer. This, once again, is
consistent with the superior deal hypothesis for the target advisors and with the deal
completion hypothesis for the acquirer advisors. Additionally, the combined wealth results
support the superior deal hypothesis, as larger gains are attributed to the high reputation of
both parties’ advisors.
4.10 Determinants of combined abnormal wealth gains
The results on the combined wealth gains to the acquirer and target firms are presented in
Table 9. In addition to the variables used earlier in this study, two additional dummies are
included; these are set equal to one if one advisor is tier-one and if both advisors are
Table 9 Cross sectional regression analyses
(1) (2) Excluding largeloss deals
(3) (4) (5)
Intercept 16.244 15.262 31.020 13.261 35.241
Acquirer advisor tier-one 30.481** 30.007**
Target advisor tier-one 28.095** 32.285**
Both advisors tier-one 40.077**
Either advisor tier-one 41.758***
Target advisor tier-one and acq.advisor tier-two
5.309
Shares -30.073* -29.795* -31.866* -30.345* -33.455**
Cash 29.095 27.785 29.263 27.762 27.116
Industry relatedness 12.813 14.349 13.159 13.271 14.151
National -26.078 -26.139 -23.179 -24.066 -17.934
Hostile 68.426* 67.632* 69.266* 74.857* 80.669**
Relative size -1.016 -0.662 -1.720 -0.897 -1.955
Toehold -35.181 -35.571 -35.896 -33.695 -33.836
Adj R-Sq 0.0266 0.0278 0.0228 0.0254 0.0161
F-value 3.88 *** 3.99*** 3.77*** 4.09*** 2.94***
Number of observations 948 942 948 948 948
The table presents ordinary least square regressions of the combined dollar gains for the target and acquirerfirms’ shareholders for deals completed by US acquirers between Jan 1985 and April 2004 as reported bySDC excluding all financial institutions deals where the deal value is at least $1 million and the acquirergains control of the target firm. The sample was trimmed by deleting 5% of the largest and smallest wealthgains. The independent variables include dummies for acquirer advisor tier, target advisor tier, both advisorstier, either advisor tier, target advisor tier relative to acquirer advisor tier, cash, shares, industry relatedness,national, hostile, and toehold that take the value one if acquirer advisor is tier-one, the target advisor is tier-one, both advisors are tier-one, either advisor is tier-one, the target advisor is tier-one while the acquireradvisor is tier-two, for acquisitions using pure cash, pure equity, acquisitions of firms that share the bidderthe same two-digit SIC code, acquisitions of US targets, hostile acquisitions as defined in SDC, and dealswhere the acquirer had at least 5% ownership in the target firm prior to the acquisition, respectively. Relativesize is the target market value of equity divided by the acquirer market value of equity 2 months prior to theacquisition announcement. Model (2) controls for large loss deals; these are defined as those that result inacquirer dollar loss of at least $1 billion. I also include year and one-digit SIC code dummies in all modelsbut do not report them
***, **, * Significant at the 1%, 5% and 10% respectively
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tier-one, zero otherwise. In model (1) the coefficients of the advisors’ reputation dummies
are both significant at the 5% level implying that combined wealth gains are larger for
deals with a tier-one acquirer advisor and a tier-one target advisor. The results are con-
firmed in model (2), which excludes large loss deals and in model (3) as the coefficient on
both advisors’ reputation dummies is significantly positive. On the other hand, model (4)
shows that when one of the parties’ advisors is in tier-one, the combined wealth gains
would be significantly higher as well, this is consistent with Bowers and Miller (1990) and
with the univariate analysis of Table 8. Moreover, the remaining coefficients were con-
sistent across all the models. For instance, the significant negative coefficient of the equity
settlement dummy indicates that lower gains are expected for equity deals; this is con-
sistent with prior M&A studies (see e.g. Eckbo and Langohr 1989; Franks et al. 1991; and
Ismail and Davidson 2005). Furthermore, the positive coefficient of the hostile deal
dummy denotes that such deals result in larger wealth gains as well.
5 Conclusion
The study investigated whether employing high quality financial advisors results in larger
gains to targets, bidders and the combined entity. For a sample of 6,379 US M&A deals
completed between 1985 and 2004, the study found that employing prestigious financial
advisors (tier-one) destroyed value of more than $42 billion for acquiring firms’ share-
holders; whereas acquirers advised by tier-two investment banks generated a total dollar
gain of more than $13.5 billion. Six advisors, out of the top ten, wiped out the gains created
by the remaining four investment banks. These results hold irrespective of the acquirer size
and the deal size (large or small). I also found evidence that larger premiums are paid in
large deals as compared to small deals, which indicates that investment banks might have
different incentives when they advise on large deals as opposed to small ones. On the other
hand, it is also found that tier-one banks were involved in most of the large loss deals, and
that if they had not advised on those deals, they could have outperformed tier-two advisors.
Moreover, another key finding was that during the internet bubble period both type of
advisors generated large gains to their acquirer clients but tier-one advisors outperformed
tier-two advisors. I also find that most of the losses incurred by acquiring firms were in
fact, during the bear market period, and if this period were excluded from the sample, tier-
one acquirer advisors could have outperformed tier-two advisors. The ranking of invest-
ment banks showed that less prestigious advisors occupied the highest positions in terms of
the mean dollar gains earned by acquirers, however, tier-one advisors rarely occupied high
rankings.
The industry implications of these results are that advisors’ reputation league tables,
based on market share, could be misleading as they do not necessarily propose that top-tier
banks will generate high gains to their clients; and therefore the selection of investment
banks must be based on the advisors’ track record in generating quality gains to their
clients in prior acquisitions.
On the other hand, the results for target advisors were consistent with the superior deal
hypothesis as tier-one investment banks’ clients generated larger gains. Moreover, the
ranking of target advisors showed that most of the tier-one investment banks were at the
top of the league table.
Additionally, the paper found that the existence of a prestigious advisor on at least one
side of an M&A transaction results in higher wealth gains to the combined entity. There is
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also evidence that target advisors are able to extract more wealth gains for their clients
which lead to higher combined gains at the expense of the acquirer.
After controlling for various deal and firm characteristics, multivariate analyses on
acquirer, target and combined wealth gains were all supportive of the univariate results.
The regressions documented no relation between the acquirer advisor tier and the acquirer
wealth gains. However, the results also showed that acquirers’ gains are smaller when the
target advisor is tier-one. Targets also gain more when their advisor is more reputable than
that of the acquirer.
Appendix A
See Table 10.
Table 10 Comparative performance of acquirers financial advisors accounting for the internet bubble
Financial advisor No. of acquirers Total dollar gain Mean dollar gain
Panel A: the performance during the bubble period
Top 10 advisors (tier-one) 766 61,574.87 80.38
Other advisors (tier-two) 1,068 25,374.59 23.76
Undisclosed 967 102,851.27 106.36
In-house deals 132 -66,049.88 -500.38
Panel B: the performance outside the bubble period
Top 10 advisors (tier-one) 768 -104,047.83 -135.48
Other advisors (tier-two) 1,191 -11,828.20 -9.93
Undisclosed 1,479 -107,877.11 -72.94
In-house deals 8 -49,631.43 -6,203.93
Panel C: the performance during the bear market period between Mar 13, 2000 and Sept. 30, 2002
Top 10 advisors (tier-one) 309 -79,644.50 -257.75
Other advisors (tier-two) 380 -6,452.81 -16.98
Undisclosed 546 -124,607.01 -228.22
In-house deals 6 -49,643.02 -8,273.84
Panel D: the performance EXCLUDING the bear market period between Mar 13, 2000 and Sept. 30, 2002
Top 10 advisors (tier-one) 1,225 37,172 30.34
Other advisors (tier-two) 1,879 19,999 10.64
Undisclosed 1,900 119,581 62.94
In-house deals 134 -66,038 -492.82
The table presents the performance of acquirer financial advisors after accounting for the internet Bubblewhere the bubble period is between Jan 1995 and March 10, 2000 (Panels A and B). The Table also showsthe results during the bear market period between Mar. 13, 2000 and Sept. 30, 2002 and the results afterexcluding this period from the total sample (Panels C and D). The deals were completed between Jan 1985and April 2004 as reported by SDC excluding all financial institutions deals; where the deal value is at least$1 million and the acquirer gains control of a public, private or a subsidiary target firm
The total dollar gain is calculated as the market capitalization 2 months prior to the announcement of themerger multiplied by the CAR (-2, ?2). CAR (-2, ?2) is the 5-day cumulative abnormal returns estimatedusing the market model. The mean dollar gain is the total dollar gain divided by the number of deals advisedby each advisor. Dollar amounts are in millions
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