When do banks listen to their analysts? Evidence from mergers ...
When do banks listen to their analysts?
Evidence from mergers and acquisitions
Penn State University
Phone: (814) 865-7969
Penn State University
Phone: (814) 865-1483
March 6, 2009
We study the extent to which an investment bank’s investment decisions are related to both their
own analysts’ recommendations and the likely incentives behind these recommendations. Using
the analyst recommendations and investment decisions of investment banks advising acquirers,
we show that, on average, advisors buy the acquirers that their analysts upgrade and sell the
acquirers that their analysts downgrade. This relation, however, varies across types of advisor
banks. More severe conflicts of interest within banks that are highly dependent on investment
banking cause these analysts to upgrade acquirer stocks more often. However, such upgrades are
not accompanied by purchases. In contrast, downgrades by these same analysts are accompanied
by significant sales. Traders within an investment bank are cognizant of the incentives of the in-
house sell-side analysts, and knowledge of such incentives significantly affects the extent to
which they rely on their recommendations.
We thank Lubomir Petrasek for excellent research assistance. We thank Richard Bundro, Urs Peyer and seminar
participants at Case Western Reserve University and the University of Colorado for helpful comments and
The potential for conflicts of interest is prevalent within investment banks. As noted by
Mehran and Stulz (2007), information plays a critical role in the transactions in which financial
institutions specialize, and the potential for information asymmetries is substantial. Such
asymmetries are a fertile ground for conflicts of interest. Consistent with this, a wide body of
evidence suggests that the various divisions of investment banks do not act independently;
conflicts of interest appear to be a driving factor behind many observed outcomes. In fact,
Leaven and Levine’s (2007) finding of a diversification discount for financial conglomerates and
DeLong’s (2001) event study analysis of investment bank mergers suggests a valuation penalty
for offering too many services under one roof.
For consumers of investment bank services, the quality of the information they are
purchasing is of obvious import. Does the information represent an investment bank’s unbiased
opinion, or does the information reflect the effects of certain conflicts of interest? Prior literature
has provided somewhat contradictory evidence on this quality issue. For example, in the area of
analyst recommendations, one stream of literature shows that analysts’ recommendations have
investment value while another finds that the over-optimism of affiliated analysts contributes to
temporarily inflated stock prices. A survey of 29 studies of sell-side analyst activities by
Mehran and Stulz (2007) shows that the evidence on whether analysts provide biased advice is
split almost identically.
We take a new approach towards assessing the value-relevance of analyst
recommendations, by examining whether investment banks follow their own advice.
Specifically, we examine whether changes in the stock holdings of investment banks are related
to the upgrades and downgrades of their own analysts. In order to provide the strongest setting
to test for both value-relevance and conflicts of interest, our analysis of the interaction between
analyst recommendations and investment bank stock holdings focuses around mergers.
Although conflicts of interest can be ongoing, they are arguably particularly large when a bank is
advising a company in a merger. Mergers are a large source of revenues for investment banks,
and analysts can be important in both enabling the bank to land merger deals and in increasing
the probability that the deals will be completed (see, e.g., Becher and Juergens, 2005).1 In
addition, the insights of analysts into the expected costs and/or synergies of the merger can make
their resulting recommendations quite valuable. As highlighted by Moeller, Schlingemann, and
Stulz (2005), the value of companies can change dramatically around mergers.2
Our analysis is based on the idea that people within an investment bank have a better
understanding than people outside of the bank regarding the conflicts and incentives that the
bank’s own sell-side analysts face. Our prediction is that a firm’s trading decisions will mirror
the advice of its analysts if the analysts’ conflicts of interest are low. In contrast, if the
perception is that analysts’ recommendation changes are largely driven by conflicts of interest,
for example by pressure to support the investment banking business, we would expect no relation
between the bank’s stock positions and its analysts’ recommendations. Our comparisons focus
on the recommendations and stock holdings by the advisor investment bank in the acquirer firm.
While all analysts face the sometimes contradictory incentives of both providing the most
accurate recommendations and supporting the investment banking arm of their firm, these two
incentives are arguably not of equal importance across all times and across all banks. If analysts’
insights into firm value are greater at some points in time, then we would expect a closer relation
In 2006 alone, the top 20 investment banks earned almost $35 billion in fees from underwriting mergers and
acquisitions,1 about half of the total fees that they earned from all investment banking activities.
As shown by Moeller, Schlingemann, and Stulz (2005), returns to acquirers around the announcement of mergers
at the 5% and 95% level range from -6% to 7% between 1980 to 1997 and -19% to 13% between 1998 and 2001.
between analyst recommendation changes and changes in bank stock holdings at these times.
Similarly, if conflicts of interest are greater in some banks, than we would expect less of a
relation between analyst recommendation changes and changes in stock holdings in these banks.
We posit that banks in which investment banking is a more important source of revenue
are likely to put more pressures on analysts to support this arm of the business, for example by
issuing optimistic recommendations around events such as mergers that provide substantial
investment banking revenues. As a result, traders at these banks should rely less on their own
analysts’ recommendations, meaning stock holdings will not be related to recommendations. In
contrast, in banks that rely most heavily on trading as a source of revenue, analysts should be
motivated to provide the most accurate recommendations possible, particularly around an event
such as a merger that is potentially associated with large value changes. As a result, stock
holdings should be significantly related to analyst recommendations within these banks.
Our findings are broadly consistent with the idea that the value relevance of analyst
recommendations differs in predictable ways across investment banks and over time. We find no
evidence that the stock holdings of the advisor bank move in line with the advisor bank’s analyst
recommendations (on the acquirer firm) prior to the merger. However this association changes
markedly after the merger: there is a significant positive relation between an advisor bank’s
analyst recommendations and its stock holdings following the merger announcement. Within the
advisor bank, mergers in which the analyst upgrades the acquirer stock are associated with
significantly larger increases in share ownership of the acquirer, compared to cases where the
analyst downgrades the acquirer.
The finding that advisor bank stock holdings are only related to the analyst
recommendations of the acquirer firm after the merger suggests that the analysts have more
value-relevant information to convey at this time. However, it is also the case that these analysts
may face larger conflicts of interest at this time, particularly those analysts at banks that rely
heavily on investment banking as a source of revenue. An examination of variation in analyst
forecasts supports this conjecture. Analysts at high investment banking banks are significantly
more likely to upgrade the acquirer firm following the announcement of the merger, while
analysts within banks that rely most heavily on trading are significantly less likely to upgrade.
Not surprisingly, traders within the advisor bank are aware of these conflicts of interest.
The frequent analyst upgrades of acquirer firms at the high investment banking banks appear to
be discounted: there is no significant relation between advisor upgrades and stock holdings
among these banks. In contrast, downgrades by such banks are relatively less common and
traders consider them to be an important source of information: there is a strong relation
between downgrades and changes in stock holdings within banks that rely most heavily on
investment banking as a source of revenue. Among those advisor banks that rely most heavily
on trading as a source of revenue, stock holdings of the acquirer firm are strongly positively
related to the analyst recommendations of the acquirer firm: banks increase their holdings when
their analyst upgrade the acquirer and they decrease holdings when the acquirer is downgraded.
Our classification of banks into high versus low conflicts of interest is based on publicly
available information, suggesting that other institutions could easily consider similar factors
when making their investment decisions. However, our findings indicate that non-advisor
institutions do not similarly incorporate both the advisor bank recommendations and the likely
incentives behind these recommendations into their investment decisions. This raises the
question of whether advisor banks overestimate the value of their analysts’ recommendations, or
whether the non-advisor institutions are missing value-relevant information when they disregard
Our analysis of returns provides evidence against the proposition that investment banks
overestimate the value of their analysts’ recommendations. Rather, our results suggest that
investment banks gain by basing their investment decisions on both their analysts’
recommendations and the likely incentives behind these recommendations. We consider the
sample of acquirers with a recommendation change by the advisor bank, and we divide this
sample into those firms in which the advisor bank increased holdings versus those in which the
bank decreased holdings. We find that those acquirers in which the advisor bank increased
holdings outperformed those in which the bank decreased holdings by an average 66 basis points
per month over the subsequent 12 months. In contrast, we find no evidence of excess returns
following changes in analyst recommendations that are not conditional on changes in holdings.
Our paper contributes to a growing literature on conflicts of interest within investment
banks. Aggarwal, Prabhala, and Puri (2002), Schenone (2004), Drucker and Puri (2005),
Bodnaruk, Massa, and Simonov (2007), and Massa and Rehman (2008) all document various
conflicts of interest within investment banks. Conflicts of interest affect the interactions between
analysts and investment banks, the relations between mutual funds and banks within the same
financial group, the effects of investment bank ownership stakes on merger advice, and the
differences between commercial and underwriting banks. We add to this literature by examining
the interactions between an investment bank’s trading, analyst recommendations, and advising
activities around mergers, conditional on the bank’s primary sources of revenues.
Our paper proceeds as follows. Section 2 reviews prior literature on conflicts of interest
within investment banking. Section 3 outlines the data and sample characteristics. Section 4
includes empirical tests on the relation between analyst recommendations and institutional
trades, by the advisor investment bank. Section 5 investigates how this relation varies depending
on the likely magnitude of the conflict of interest faced by analysts. Section 6 examines whether
the adviser banks change their stock positions significantly more than other institutions in
response to changes in advisor analyst recommendations. Section 7 provides an analysis of stock
returns, which quantifies the potential gains from considering both the presence of an analyst
recommendation change and the likely incentives behind this change. Finally, Section 8
2. Related Literature
A substantial body of literature has examined the value of analyst recommendations, and
there is a broad consensus that analysts have incentives to issue value-relevant recommendations
but also face conflicts of interest. Hong and Kubik (2003) and Jackson (2005) show that analysts
are motivated to increase their reputations by issuing the most informative forecasts and
recommendations.3 However, Michaely and Womack (1999) and Kolanski and Kothari (2009)
show that analysts tend to issue overly optimistic recommendations in an effort to support the
investment banking division, for example around initial public offerings and mergers.
The ways in which these contradictory incentives affect both recommendations and stock
prices is a matter of debate, with some papers concluding that conflicts of interest result in overly
optimistic recommendations that lead to temporarily inflated stock prices, and other papers
finding that the effects of these conflicts are trivial (see Mehran and Stulz, 2007, for a survey).
Part of the inconsistency in these streams of prior literature is potentially related to the
fact that not all analysts face the same conflicts at all times with respect to all stocks. Ljungqvist,
Ljungqvist, Malloy and Marston (2006) find that the importance of accuracy for career outcomes has become more
limited in recent years.
Marston, Starks, Wei, and Yan (2007) examine this issue by separating stocks by the level of
institutional ownership. Analysts’ career paths are largely influenced by the All-Star rankings,
which are based on institutional investor feedback. Consequently, it follows that an analyst’s
incentives to provide unbiased, accurate recommendations are highest in those stocks with the
highest institutional ownership. Consistent with this conjecture, the authors find that
recommendations relative to consensus are negatively related to ownership by institutional
investors, but positively related to investment banking relationships. Similarly, Agrawal and
Chen (2008) show that when investment banking revenues are a greater fraction of a bank’s total
revenues, analysts are more likely to provide optimistic recommendations and upgrade stocks.
Chen and Cheng (2002) examine the value-relevance of analyst recommendations by
considering the relation between such recommendations and institutional trading. They find a
positive relation between consensus analyst recommendations and institutional holdings,
providing evidence that analyst recommendations are perceived as having value. However,
unlike us, they compare all institutional trading with consensus recommendations, thus implicitly
treating each analyst recommendation as having equal value, as being equally affected by
conflicts of interest.
More similar to our approach, Chan, Chang, and Wang (2005) match quarterly trades of
financial firms with the recommendations of their own analysts. The specification and focus of
their study, however, differs considerably from ours. Chan et al focus on the value relevance of
recommendations in a general setting. Correspondingly they examine all recommendations, not
just those around a corporate event. Consistent with the analyst recommendations having value,
they find that in-house trade is more positive around upgrades than downgrades. In contrast, our
study focuses on mergers and the banks advising the acquirer. In this setting, a bank clearly has
value at stake and conflicts of interest are more likely to arise for analysts. Moreover, this
approach enables us to examine the extent to which the relative importance of such conflicts
varies both over time and across banks.
3.1 Sample Construction
Our data consists of mergers and acquisitions between 1995 and 2005, as obtained from
the Securities Data Company (SDC) database. To ensure that the merger is a material event for
the acquiring firm, we require the market value of the target to be at least 5% of the combined
market capitalization of the bidder and the target. Both targets and acquirers are public firms
traded in the U.S., and the acquirer must be publicly traded for at least three years prior to the
merger announcement. We require each bidder firm to be followed by at least one analyst, as
listed on the IBES recommendation database, and to be partially owned by at least one
institution, as listed in the Spectrum 13(f) filings, one year prior to the announcement of the
Our analysis necessitates merging the SDC merger data, the IBES recommendation data,
and the Spectrum institutional holdings data. For each merger, we identify the advisory
investment bank from SDC. We match by hand the identity of this bank with the IBES broker
code and with the Spectrum institutional name. In matching the institutions between the SDC,
IBES, and Spectrum databases, we are careful to account for both mergers between investment
banks and for banks reporting under different names (e.g., Smith Barney Inc. and Smith Barney
& Co). We attempt to match every investment bank that served as an advisor in at least 10 deals
over our sample period. The only advisors not matched were those such as Houlihan, Lokey,
Howard & Zukin and Greenhill & Co, LLC, neither of which have either a trading desk or
analysts. Mergers in which the advisor either did not have an advisory arm (i.e., wasn’t listed in
IBES), didn’t have a trading arm (i.e., wasn’t listed in Spectrum), or served as an advisor in less
than ten deals are omitted from our sample.
Institutional holdings data are reported in Spectrum quarterly, on March 31st, June 30th,
September 30th, and December 31st of each year. We calculate total shares held by each advisor
institution and each non-advisor institution over the period beginning five quarters prior to the
merger announcement and continuing through five quarters following the merger completion.
For our analysis of analyst recommendations, we obtain from IBES all analyst
recommendations on each acquirer firm. We identify the advisor firm recommendation
outstanding three days prior to each institutional trading date, and we aggregate all non-advisor
recommendations outstanding as of this same date into a non-advisor average consensus
recommendation. We compute analyst upgrades as cases where an analyst revised its
recommendation upwards, and analogously for downgrades. Kadan, Madureira, Wang, and Zach
(2008) note that many investment banks revised their recommendations downward in the wake
of the Global Settlement, in order to comply with regulations and present a more balanced set of
recommendations, i.e., more equal portions of optimistic versus pessimistic ratings. The process
of the banks reclassifying substantial numbers of recommendations resulted in large numbers of
recommendation changes that were not information based. As Kadan et al show, banks generally
reclassified their outstanding recommendations within a very short period of time, and these
changes did not result in significant stock price reactions. Based on these findings, changes in
recommendations related to the Global Settlement are not classified in our sample as upgrades
3.2 Sample Characteristics
As shown in Table 1, these requirements result in a sample of 914 mergers, of which 468
are stock acquisitions, 127 are cash, and 319 are mixed. Many of the mergers have more than
one advisor. Due to our interest in conflicts of interest at the investment bank level, many of our
analyses focus on advisor-level recommendations and stock ownership. Our sample includes
1048 advisor-level observations. The sample is spread over time, with the largest number of
transactions occurring in the late 1990s. This concentration is consistent with the finding in prior
literature that M&A activity tends to be particularly high when the stock market is strong.
Looking at the industry distribution, the largest number of mergers is in the business equipment
and finance industries.
Table 2 provides descriptive statistics for the full sample. Of greatest interest for our
analysis is analyst coverage and stockholdings of the advisor. Therefore the sample is divided by
whether the advisor has an analyst covering the advisor and by whether the advisor owns shares
in the acquirer. Several differences become apparent. The acquirers covered by the advisor’s
analyst and owned by the advisor are larger than other acquirers. This finding likely reflects the
more general result that both analyst coverage and institutional ownership are greater in larger
firms, as shown by Gompers and Metrick (2001) and Barth, Kasznik, and McNichols (2001).
The acquirers in which their advisors own shares have higher market-to-book ratios, higher
leverage ratios, and lower working capital as a fraction of total assets, however there are no
differences in these measures when acquirers are sorted by advisor analyst coverage. Finally,
We thank Leonardo Madureira for providing the dates on which the banks revised recommendations in an effort to
comply with the Global Settlement.
relative merger size is significantly lower among companies with advisor analyst coverage and in
which advisors own shares. This difference in relative merger size is potentially driven by
differences in firm size – companies in which the advisor bank issues recommendations and
owns shares are significantly larger, meaning a given target size will be relatively smaller.
Table 3 examines the extent to which a bank’s tendency to issue analyst
recommendations or own shares in a firm is related to either expected or recent M&A advisory
business by the investment bank. The analysis begins four quarters prior to the merger
announcement and continues through five quarters following the merger completion. In
conducting this analysis, we assume that an investment bank’s view of the acquirer can change
substantially during this period. A bank likely has a much better idea that there is an opportunity
to advise a firm in a merger one quarter prior to the merger announcement than five quarters
prior to the announcement.
Table 3 shows an increase in both the advisor’s analyst coverage of the acquirer and in
the advisor’s stockholdings of the acquirer in the period leading up to merger. These increases
are, however, comparable to those of other non-advisors. For example, the percent of advisors
with analyst coverage increases from 50% five quarters prior to the merger announcement to
64% one quarter before the merger announcement. Because other analysts are also picking up
coverage of an acquirer during this time, recommendations by advisor’s analysts as a percentage
of all analysts covering the acquirer only increases from 8.9% to 9.5%. The percent of advisors
owning shares of the acquirer increases from 67% to 73% during this period, but decreases as a
fraction of shares owned by all institutions from 0.62% to 0.54%. Therefore, the results provide
little evidence of disproportionate changes in ownership or analyst coverage by the advisor
during this period.
4. Are changes in advisors analyst recommendations and stockholdings correlated?
The focus of our analysis is the relation between changes in the advisor’s analyst
recommendations and changes in the advisor’s stockholdings. We assume that in making
investment decisions, a firm has a better understanding of the conflicts that its analysts face than
other investors. Therefore, the investment decisions of advisors should only follow the
recommendations of its analysts if the analysts’ conflicts of interest are low.
4.1 Univariate Analysis of Changes in Recommendations and Stockholdings
Table 4 provides descriptive evidence on the relation between analyst recommendations
of the acquirer and stockholdings in the acquirer, by the advisor bank. The panels in this table
show the average change in stockholdings conditional on an analyst upgrade, downgrade, or zero
change in recommendation. We measure changes in the advisor stockholdings of the acquirer
each quarter in three different ways. The first measure is an indicator variable equal to -1 if
holdings decrease, 1 if holdings increase, and 0 if holdings do not change. The second is the
change in the number of shares held by the advisor. The third is this change in the number of
shares held by the advisor net of the average change in shares held by other institutional
investors. The data underlying the analyses represent a panel dataset, with one observation for
each acquirer firm advisor in each quarter.
The relation between recommendations changes and stockholdings varies around the time
of the merger. Results for the entire event period (five quarters pre-announcement through five
quarters post-completion) are shown in Panel A of Table 4. Although it might not be surprising
that advisors often upgrade acquirers around a merger, downgrading is also common. During
this period, there were 408 advisor bank downgrades of acquirer firms, 682 upgrades, and 7,138
firm quarters with no change in advisor bank recommendation. On average across the 408
downgrades, slightly more advisor banks sold shares than bought shares (indicator variable =
-0.01). Across the 682 upgrades more advisor banks bought than sold shares (indicator variable
= 0.13).5 The t-stat for the difference equals 2.88, significant at the 1% level. Similarly, the
difference between the change in shares conditional on a downgrade versus upgrade is weakly
significant, at the 10% level. Finally, as shown in the last row of Panel A, the differences are not
statistically significant once we adjust for changes in holdings by other institutional investors.
Looking at Panel B, in the fivea quarters leading up to the merger announcement there
are almost twice as many upgrades of the acquirer by the advisors analysts as downgrades (293
to 147). Results, however, indicate that there is no relation during this pre-announcement period
between changes in these recommendations and advisor stockholdings.
The relation between changes in analyst recommendations and stockholdings is strongest
following the announcement of a merger, defined as the period between the merger
announcement and 5 quarters following merger completion. Panel C shows about 50% more
upgrades than downgrades of the acquirer by the advisor’s analyst during this period.
Regardless of the measure for change in stockholdings used, the results indicate that advisors are
significantly more likely to increase their holdings of acquirers that their analyst upgraded than
the acquirers they downgraded. Moreover, there is a monotonic increase in all measures (from
downgrade, to no change, to upgrade). For example, the indicator variable equals -0.05 across
Across the entire sample of firm quarters, both the indicator variable and changes in advisor shareholdings are
positive because an increasing number of advisor banks own shares in the acquirer firm over time (as reported in
Table 3). In addition, the size of the average position increases slightly over time (not tabulated).
the 261 downgrades, 0.07 across the 4,677 firm quarters with no recommendation change, and
0.12 across the 388 upgrade quarters. Banks were more likely to sell conditional on a
downgrade and more likely to buy conditional on an upgrade, and the difference is significant at
the 1% level (t-statistic = 2.51). Looking at the last row of Panel C, we see that changes in
advisor shareholdings net of change in non-advisor institutional shareholdings is also
significantly higher in firm quarters with upgrades versus downgrades. Evidently, other
institutions are not following the advisor analyst recommendations in the same way as the
advisor firms. We examine this finding in more depth in subsequent sections.
4.2 Regression Analysis of Changes in Recommendations and Stockholdings
Table 5 examines this relation between changes in analyst recommendations and changes
in stockholdings in a regression framework. Dependent variables in these regressions include the
same three measures (as in Table 4) of changes in advisor stockholdings of the acquirer: an
indicator variable (columns 1 and 2), the change in advisor bank stock holdings (columns 3 and
4), and the change in advisor bank stock holdings net of the change in non-advisor institutional
holdings (column 5). In columns 1 through 3, regression observations include the period
beginning four quarters prior to the merger announcement and extending through five quarters
following the merger completion. In columns 4 and 5 the sample is restricted to those quarters
following the merger announcement.
The independent variable of greatest interest in these regressions is the change in advisor
analyst recommendation, defined as the advisor recommendation outstanding immediately prior
to the quarter t holdings date minus the advisor recommendation outstanding immediately prior
to the quarter t-1 holdings date. Analyst recommendations range from one to five, with lower
numbers being more positive. The change in recommendation is multiplied by -1, so that a
positive recommendation change can be interpreted as an upgrade and a negative
recommendation change as a downgrade.
Control variables include dummies for the level of the advisor recommendation at the end
of quarter t-1. This accounts for the fact that an analyst with a strong buy cannot upgrade and
more generally for the fact that an analyst with a positive recommendation outstanding may be
less likely to upgrade (and vice versa for downgrades). We only include dummies for strong
buy, buy, and hold, because there are fewer observations with lower recommendations (sells and
strong sells). We also control for the market capitalization of the acquirer. In columns 3 through
5, we include lagged advisor bank holdings of the acquirer firm to account for the fact that a
bank may be less likely to increase its holdings if it already holds a lot of shares. Finally, we
include the number of shares of the target firms held by the advisor in quarter t-1, multiplied by a
dummy variable equal to 1 in the first quarter following a stock merger, 0 otherwise. This
variable is used in columns 3 through 5 to account for the mechanical effects on changes in
shares held for stock mergers if the advisor bank owned shares in the target firm.
The results in column 1 show that, on average, advisors change their stock holdings in the
same direction as the change of their analyst recommendations. The results in column 2,
however, indicate that this relation is only significant for the quarters following the merger
announcement. The interaction term, change in advisor analyst recommendation * post merger
dummy, is significantly positive. In contrast, the interaction term advisor analyst
recommendation * pre merger dummy is not significant at conventional levels. Results are
similar in column 3, where the dependent variable is the change in advisor shares. Consistent
with results in Table 4, Table 5 suggests that the advisor firm changes its stock positions in the
acquirer in line with the advisor analyst recommendation changes following the merger
announcement, but not before. This potentially reflects a perception that analysts have more
value-relevant information to convey at this point, for example an assessment of likely changes
in firm value as a result of the merger.
Given the evidence suggesting that the relation between analyst recommendations and
changes in stock holdings is restricted to the period following the merger announcement,
columns 4 and 5 focus on this period. Results in column 4 are consistent with those in the first
three columns: changes in the advisor’s stockholdings of the acquirer are positively related to
changes in the recommendations by its analysts. Control variables are also consistent with
predictions. Changes in advisor banks’ holdings of the acquirer are positively related to changes
in the market capitalization of the acquirer. Also, a bank that owns more shares in the acquirer
already is less likely to increase its holdings by as great an amount, as reflected by the
significantly negative coefficient on AdvShrst-1. Finally, for stock mergers, a greater number of
shares owned in the target firm prior to merger completion is associated with greater increases in
stock holdings in the acquirer firm in the first quarter following the merger completion.
In column 5, the dependent variable equals changes in advisor firm holdings, net of the
average change in holdings of the acquirer by other institutions. Notably, the coefficient on
advisor bank recommendations is significantly positive, and similar in magnitude to that in
column 4. This finding indicates that other institutional investors are not following the advice of
the advisor firm analysts in the same way as the advisor bank.
The finding that non-advisor institutions choose not to follow the advisor analyst
recommendations is intriguing. If advisor bank traders choose to follow advisor analyst
recommendations in the quarters following the merger announcement because of a greater
perceived value-relevance during this period, then one would expect other institutions to follow.
However, it is also possible that differences between the pre- and post-merger period reflect
changes in conflicts of interest. The effects of conflicts of interest are examined in detail in the
5. Do incentives vary across advisors?
Results from tables 4 and 5 indicate that advisor firm institutions trade in line with their
analysts’ recommendations in the quarters following the merger announcement. To the extent
that the advisor firm analysts have particularly valuable information, this is exactly what we
would expect. However, this is also a time in which the pressures on advisor analysts to support
investment banking efforts will be high. For example, as noted by Michaely and Womack in the
case of IPOs, issuing a favorable recommendation on a firm after a corporate event might
increase the bank’s chances of winning more investment banking business from this firm in the
future, or even of winning more business from other firms.
To examine the conflict of interest motivation for advisor analysts, we classify
investment banks into various categories based on their sources of revenue. This approach is
similar to Agrawal and Chen (2008). We posit that analysts working for institutions in which
investment banking is a more important source of revenue will face greater conflicts of interest,
for example stronger pressures to upgrade stocks of companies for which the bank has recently
served as advisor on an acquisition. In contrast, banks that receive a greater portion of revenues
from proprietary trading should demand the most accurate, unbiased recommendations from their
For each advisor investment bank, we download the income statement from the bank’s
10K. Data limitations restrict this sample to those investment banks that are publicly traded.
This limits us to 25 of the investment banks. However, these 25 banks served as advisors in the
majority of our acquisitions. (This data restriction decreases our sample to 620 mergers.)
Investment banks are required to describe the source of their revenues, and the banks generally
break down the revenues into those from investment banking, those from proprietary trading, and
also those from various other activities on which we are not focusing. Thus, for each bank and
each year, we are able to determine the percent of revenues from investment banking versus
5.1 Analyst recommendations and the source of advisor’s revenues
If the analysts from the high investment banking firms face more serious conflicts of
interest, we would expect these analysts to behave differently than other analysts. Specifically,
analysts from firms that receive a larger percent of revenues from investment banking should
face pressures to issue more positive recommendations and to upgrade companies that are
providing their bank with investment banking business. In contrast, analysts from firms that
receive a larger percent of revenues from trading should be less biased, meaning their
recommendations will be lower on average and they will be less likely to upgrade stocks merely
because of an investment banking relation.
To examine these issues, we start by examining whether analysts’ (of the advisor
investment bank) recommendations are related to their bank’s source of revenue. This analysis
is shown in Table 6. In column (1), the dependent variable is the level of analyst
recommendation, re -ordered such that a strong buy receives the highest possible value (5), while
strong sell receives the lowest possible value (1). In column (2) the dependent variable is a
dummy variable, equal to 1 if the advisor upgraded the stock and 0 otherwise. The data
represents a panel dataset, with data on each acquirer firm spanning the period from the first
quarter following the merger announcement through 5 quarters following the merger completion.
The results are consistent with arguments that the source of an advisor’s revenues is
associated with the recommendations of its analysts. On average, recommendations are more
positive for firms that receive a greater portion of revenues from investment banking (t-stat =
9.7). In contrast, the recommendations are significantly more negative among banks that receive
a greater portion of revenues from trading (t-stat=-11.2). Control variables include the market
capitalization of the acquirer firm and shares held by the advisor bank. Investment banks tend to
issue more positive recommendations about larger firms, and they tend to issue more positive
recommendations about firms in which they owned more shares at the end of the previous
The results in column 2 also support this argument. Analysts working for banks that rely
heavily on investment banking are significantly more likely to upgrade the acquirer stock (t-
stat=2.7), while analysts working for banks that rely heavily on trading as a source of revenues
are significantly less likely to upgrade the acquirer (t-stat=-3.4). Control variables in column 2
indicate that analysts are less likely to upgrade firms for which they already have high
recommendations outstanding, and they are more likely to upgrade larger firms.
Overall the analysis shows that the behavior of analysts varies significantly with the
advisor’s source of revenues. These findings are similar to Agrawal and Chen (2008) and
support conflicts of interest arguments: the pressures from investment banking force the analysts
to appear more optimistic. An alternative interpretation, however, of these results is that
advisors that do more investment banking tend to be more optimistic (i.e., more bullish) about
mergers. This could especially be true if the bank was the one who suggested the merger to the
acquirer in the first place. The next section addresses this issue.
5.2 When do advisors follow their analysts?
To disentangle the explanations for the association between analyst optimism and the
advisor’s source of revenues, we examine the investment decisions of the advisor. If conflicts of
interest cause analysts of high-investment banking firms to be more optimistic, then we would
not expect to find a relation between these firms’ investment positions and their analysts’
recommendations. If instead, advisors that do more investment banking are indeed more
optimistic about mergers, the association between the advisor’s investment decisions and its
recommendations should not depend on the advisors’ source of revenues.
Table 7 examines these relations between analyst recommendations and changes in stock
holdings in the acquirer by the advisor bank, conditional on the bank’s source of revenues. For
each year, we classify firms with above-median (below-median) percent of revenues from
investment banking as high (low) investment banking. Similarly, firms with above-median
(below-median) percent of revenues from trading are classified as high (low) trading firms.
Table 7 is restricted to those observations for which we have the source of revenues for the
advisor bank. Also, based on results in Tables 4 and 5, the sample period represents the quarters
following the merger announcement.
Similar to Table 5, Table 7 shows regressions of the changes in advisor holdings of the
acquirer on changes in their analysts’ recommendations. The only difference between column 1
in this table and that in Table 5 is that the sample is restricted to those mergers for which we
have sources of revenues data for the advisor bank. Similar to prior findings, we find a
significant positive relation between changes in advisor analyst recommendations and changes in
advisor bank shareholdings of the acquirer firm.
In column 2, we replace the change in advisor analyst recommendation with two
interaction terms, the change in advisor analyst recommendation times the high trading dummy
and the change in advisor analyst recommendation times the low trading dummy. (Recall that
the high (low) trading bank dummy equals 1 for those advisor firms for which revenue from
trading is above (below) the median, 0 otherwise). Results suggest that the significantly positive
relation between advisor firm recommendations and shareholdings only exists among those
banks that receive a relatively high portion of their revenue from trading. When trading is more
important analysts potentially strive to provide more accurate recommendations and/or have
more resources available that enable them to provide more accurate recommendations.6 The
traders in these banks, aware of the incentives and resources of their firms’ analysts, tend to
change their positions in line with these recommendation changes. In contrast, in banks where
trading is less important the traders have less faith in the recommendations of their firms’
analysts, and there is no significant relation between bank stock holdings and analyst
The regression in column 3 is similar to that in column 2, except that it divides the
recommendation changes according to the importance of investment banking revenue for the
bank. The results show that advisors’ changes in stock holdings of the acquirer are significantly
associated with changes in their analysts’ recommendations for both high and low investment
banking firms. This is at first glance surprising, given the Table 6 finding that high investment
banking banks were significantly more likely to upgrade stocks. To the extent that this greater
propensity to upgrade reflects the effects of conflicts of interest, we would expect traders to not
While investment banks have buy-side analysts that directly report to traders, Groysberg, Healy, Chapman,
Shanthikumar, and Gui (2007) suggest that such analysts provide less informative recommendations, suggesting at a
minimum that traders probably also pay attention to the recommendations of the sell-side analysts.
heed these recommendations from the high investment banking banks.
The remaining regressions in table 7 explore this somewhat puzzling finding in more
depth, by separately considering analyst upgrades and downgrades. The regressions show
differences between the groups. Looking first at the results for analyst upgrades shown in
column 6, we see that the relation between analyst upgrades and changes in stock positions is
only significant among the low investment banking banks. In other words, advisors are buying
the acquirers that their analysts upgrade only when the revenues from investment banking are a
relatively small part of their operations, i.e., when the upgrade is less likely to be driven by
conflicts of interest.
This association, however, flips when we focus on downgrades. Looking at column 9, the
relation between analyst downgrades and changes in stock positions is only significant among
the high investment banking banks. Among these banks, downgrades are the rare event and thus
it is downgrades that are particularly informative. In sum, analysts at banks that rely more
heavily on investment banking revenues face very different incentives than those at banks where
investment banking is less important. Such conflicts result in significantly different
recommendations. The traders at the different types of banks are aware of the incentives their
firms’ analysts face, and they judge the recommendations accordingly. A way to view this
finding is that an analyst’s recommendation is more important when it runs counter to their
While the difference between high and low investment banking banks is bias (with high
investment banking analysts issuing upwardly biased recommendations), the difference between
the high and low trading banks is one of noise. Analysts at the high trading banks are clearly
motivated to issue the most accurate recommendations – thus their recommendations are
perceived to be the most value-relevant. Consistent with this conjecture, among the high trading
firms the relation between changes in advisor analyst recommendations and changes in advisor
stock holdings is similarly significant for upgrades and downgrades. In contrast, the relation is
insignificant in both the upgrade and downgrade regressions for the low trading firms.
6. Do non-advisor institutions similarly rely on advisor bank recommendations?
We have argued that an investment bank has greater insights into the conflicts that their
own analysts face than do other investment banks. Our empirical tests of this prediction rely on
a relatively simple classification of banks into high- versus low-investment banking and high-
versus low-trading that is based solely on readily available public information. We find that
banks only change their stock positions in response to analyst recommendations that are less
likely driven by conflicts of interest, suggesting that these are the only recommendations that
have investment value. Following this logic, if these less-biased recommendations do in fact
have investment value, then one would expect other institutions to similarly base their trades on
them. To examine this proposition, we re-estimate the regressions from Table 7 defining the
dependent variable as the change in acquirer shares held by the advisor net of the average change
in shares held by other institutional investors (as in Tables 4 and 5). If other institutions
similarly consider the advisor analysts’ recommendations in light of the conflicts of interest
behind such recommendations, then the analyst recommendation variable should not be
statistically significant in these regressions.
The results from these regressions are shown in Table 8. Notably, the coefficients on the
analyst recommendation variables are comparable to those in Table 7. The relation between
analyst recommendation changes and raw changes in advisor shares held is qualitatively similar
to that between analyst recommendation changes and net changes in advisor shares held. These
findings suggest that the advisor bank changes its positions in the acquirer stock significantly
more than other institutional traders, in response to advisor analyst recommendation changes.
Either the non-advisor institutions are missing value-relevant information that is contained in the
advisor bank recommendation or the advisor bank is overestimating the value of its own
7. Returns from the advisors investment decisions following changes in recommendations
In order to determine whether the advisor bank in fact gains through its strategy of
following a subset of its analysts’ recommendations, we examine returns following those
quarters in which the advisor investment bank elected to purchase shares versus sell shares
following a recommendation change by their analyst. A finding that returns following advisor
bank purchases exceeded returns following advisor bank sales (where both purchases and sales
are measured only in those quarters with an analyst recommendation change) would suggest that
the bank gained through its attention to both the recommendations and the incentives of its
analysts. Moreover, such a finding would also indicate that other institutions were losing by not
following a similar strategy. In contrast, a finding of no difference in returns between these two
strategies would indicate that banks tended to overweight the value of their own analysts’
As our focus is on banks’ response to recommendation changes, we define our sample as
firm quarters in which the advisor bank analysts changed their recommendation of the acquirer
firm. We estimate calendar time, four-factor regressions (Fama and French (1993) and Carhart
(1997)), where the dependent variable equals returns net of the risk free rate for acquirers who
have experienced a recommendation change by their advisor bank over the past 3 months (12
months, 36 months). Specifically, a firm enters the sample on the first institutional reporting
date (i.e., March 31, June 30, Sept. 30, Dec. 31) following the advisor analyst recommendation
change, and it stays in the sample for 3 months (12 months, 36 months). In Panel A of Table 9,
we consider portfolios of firms representing (1) a long position in acquirers in which the advisor
bank increased shares in the quarter of the recommendation change, (2) a long position in
acquirers in which the advisor bank decreased shares in the quarter of the recommendation
change, and (3) a long position in portfolio 1 combined with a short position in portfolio 2. The
table reports alphas (i.e.., intercepts) from these four-factor models.
Looking first at Panel A, we see that acquirers in which the advisors increased positions
outperformed those in which the advisors decreased positions (following a recommendation
change by one of their analysts) by an average 141 basis points per month (significant at the 10%
level) over the first three months following the institutional reporting date. Returns differences
for similar strategies over 12-month and 36-month horizons are positive, but not statistically
Panel B of Table 9 shows a similar analysis, except that firms are put into terciles based
on the change in shareholdings of the advisor bank in the acquirer firm (rather than just
conditioning on buy versus sell). We consider portfolios of firms representing (1) a long position
in acquirers in the top tercile based on changes in shareholdings by the advisor bank, (2) a long
position in acquirers in the bottom tercile based on changes in shareholdings by the advisor bank,
and (3) a long position in portfolio 1 combined with a short position in portfolio 2. Results
indicate that this long-short portfolio produced significantly positive returns at both the 12-month
and 36-month horizons.
Notably, the findings of excess returns are limited to recommendation changes that are
accompanied by changes in holdings, not just recommendation changes in general. In
untabulated tests we examine returns following all advisor analyst recommendation changes, and
we find no evidence of significantly higher returns following upgrades versus downgrades. The
findings support arguments that changes in holdings are more likely to follow changes in
recommendations that lead to an increase in value rather than recommendations resulting from
conflicts of interest.
The potential for conflicts of interest are pervasive in investment banks. Prior literature
has not reached a consensus on the extent to which such conflicts affect analyst
recommendations. We take a new approach to this problem, by examining the association
between an investment bank’s analyst recommendations and its investment decisions.
We find that advisor firm changes its stockholdings in the acquirer based on both the
recommendation changes of its analysts and the likely incentives behind these recommendation
changes. Analysts in banks that receive a greater portion of revenue from investment banking
tend to be more optimistic, particularly in the period following a merger announcement. They
are more likely to upgrade the acquirer stock. However, these upgrades are discounted; there is
no evidence that the investment bank changes its stock positions in response to such biased
recommendation changes. In contrast, downgrades by analysts at these banks are accompanied
by large sales by these same banks.
At banks that receive a higher portion of revenue from trading, analysts appear to be less
biased and there is consistent evidence that the bank changes its stock positions in response to
both upgrades (increases positions) and downgrades (decreases positions).
Notably, other institutions do not seem to employ the same information when making
their investment decisions. Changes in their stockholdings are not related to both advisor analyst
recommendations and the incentives behind recommendations in a similar way. Moreover, this
lack of attention to such information causes them to lose out on a profitable trading strategy.
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Table 1: Descriptive Statistics on M&A Sample
The sample consists of 914 mergers over the 1995 to 2005 period. For a merger to be included in the sample, the
acquirer firm must be followed by at least one analyst, as listed in the IBES database, and be owned by at least one
institutional investor, as listed in the Spectrum database, one year prior to the merger announcement. In addition,
the target market capitalization must be at least 5% of the combined market capitalization of the target plus acquirer,
where all market capitalizations are measured one month prior to the merger announcement. A merger with two
advisors is treated as two advisor-level observations; there are 1048 advisor observations across the 914 mergers.
Mergers are classified into industries based on the Fama-French 12 industry groupings.
Relative Size > 5%
Number of advisor observations 1048
Number of unique mergers 914
Year # Mergers Industry # Mergers
1995 83 Consumer Nondurables 23
1996 87 Consumer Durables 10
1997 150 Manufacturing 70
1998 144 Oil, gas, coal extraction 44
1999 105 Chemicals and allied products 23
2000 92 Business Equipment 162
2001 57 Telephone & TV transmission 29
2002 35 Utilities 32
2003 66 Wholesale, Retail 66
2004 67 Healthcare, Med. Eqpt, Drugs 90
2005 28 Finance 273
Table 2: Descriptive Statistics
Descriptive statistics are provided for the sample of 914 mergers over the 1995 – 2005 time period. All variables, with the exception of relative merger size,
refer to the acquirer firm, and all statistics represent medians. Market capitalization (in millions) is measured one month prior to the announcement of the
merger. All other financial variables are measured at the fiscal year end preceding the merger announcement. Market-to-book equals the equity market
capitalization divided by the book value of equity. Book leverage equals the sum of short-term and long-term debt, divided by total assets. Market leverage
equals the sum of short-term and long-term debt divided by the total firm market value, where total firm market value equals total assets plus market value of
equity minus the book value of equity. Total assets, sales, sales/TA, EBIT/TA, and WC/TA are computed using the relevant Compustat data items. Relative
merger size equals the target market capitalization divided by the combined market capitalization of the target plus acquirer, where all market capitalizations are
measured one month prior to the merger announcement. Statistics are computed for the whole sample, conditional on whether or not the advisor bank to the
acquirer firm has an analyst issuing recommendations on the acquirer one quarter prior to merger announcement, as listed on IBES, and conditional on whether
or not the advisor bank to the acquirer firm owns shares in the acquirer firm one quarter prior to merger announcement, as reported on Spectrum. Asterisks
denote whether the advisor analyst vs. no advisor analyst statistics are significantly different, and similarly whether then advisor institutional ownership vs. no
advisor institutional ownership are significantly different (*, **, *** represent the 10, 5, and 1% levels of significance).
Advisor No Advisor Advisor No Advisor
Whole Sample Analyst Analyst Institutional Institutional
(n=914) Following Following Ownership Ownership
(n=591) (n=323) (n=548) N=366)
Market Cap (mil) 1,742 2,087 1,325*** 2,735 860***
Total Assets (mil) 1,852 1,841 1,904 2,765 1,143***
Sales (mil) 846 960 752* 1,340 491***
Sales / TA 0.65 0.65 0.64 0.65 0.63
MB 2.40 2.49 2.22 2.51 2.19***
Book leverage 0.21 0.22 0.20 0.23 0.17***
Market leverage 0.13 0.13 0.12 0.13 0.12
EBIT / TA 0.07 0.08 0.07* 0.07 0.07
WC / TA 0.18 0.18 0.19 0.16 0.21***
Relative Merger Size 25% 23% 31%*** 22% 29%***
Table 3: Incidence of advisor recommendations and share ownership in the acquirer companies
This table provides information on the incidence of advisor recommendations and advisor institutional ownership in the acquirer company, from five quarters
prior to the announcement of the merger to five quarters following the completion of the merger. Percent of advisors represents the percentage of the 1048
advisor-level observations in which the advisor bank to the acquirer had an analyst following the acquirer. Average number of recs per company represents the
average number of analysts covering each acquirer firm. Percent of total recs by advisor equals the number of advisors covering each firm divided by the total
number of recs in each firm, averaged across the 914 mergers. Percent of advisors that own shares represents the percentage of the 1048 advisor-level
observations in which the advisor bank to the acquirer owned shares in the acquirer. Average # insts invested in co equals the total number of institutions
invested in each acquirer firm, averaged across all mergers. Advisors as a % of total equals the number of advisors owning shares in each firm divided by the
total number of institutions owning shares in each firm, averaged across the 914 mergers. Percent of advisors that issue recs and own shares equals the percent
of the 1048 advisors to the acquirer firms that both have an analyst following the acquirer and own shares in the acquirer. Company mkt cap equals the median
market capitalization of the acquirer firm.
Issuance of Recommendations Ownership of Shares % of
% of Total % of Avg # that Issue
Avg # Advisors Company
% of Recs that Advisors Insts Recs and
Recs per as % of Mkt Cap
Advisors are by that Own invested own
Company total insts ($mil)
Advisor Shares in co Shares
5 qtrs pre- ann’t 50% 8.5 8.9% 67% 187 0.62% 32% $1,433
4 qtrs pre- ann’t 54% 9.3 9.4% 68% 194 0.57% 34% $1,530
3 qtrs pre- ann’t 58% 9.9 9.2% 69% 201 0.57% 36% $1,623
2 qtrs pre- ann’t 61% 10.6 9.2% 69% 209 0.54% 38% $1,695
1 qtr pre- ann’t 64% 11.1 9.5% 71% 216 0.54% 41% $1,856
1 qtr post-ann’t 65% 11.7 9.2% 73% 230 0.55% 43% $2,079
1 qtr post-completion 68% 12.0 9.1% 76% 268 0.46% 47% $2,457
2 qtrs post-completion 70% 12.4 9.1% 77% 264 0.48% 50% $2,546
3 qtrs post-completion 71% 12.6 9.1% 78% 264 0.50% 50% $2,554
4 qtrs post-completion 71% 12.7 8.8% 79% 264 0.50% 52% $2,430
5 qtrs post-completion 68% 12.7 8.4% 78% 264 0.50% 52% $2,562
Table 4: Relation between advisors’ recommendations and institutional holdings
Each panel tabulates the number of quarters in which the advisor bank upgraded, downgraded, and made no
recommendation change to the acquirer firm. Panel A is based on the period beginning 5 quarters prior to the
merger announcement and extending through 5 quarters after merger completion. Panel B focuses on the pre-
announcement quarters and Panel C on the post-announcement quarters. Each panel shows the number of
downgrades and three measures of changes in advisor ownership of the acquirer firm in the quarters of these
downgrades (and similarly for quarters with no recommendation change and for quarters with upgrades). The first
measure is an indicator variable, equal to 1 if the advisor bank increased holdings in the acquirer in quarter t, -1 if
the advisor bank decreased holdings, and 0 if holdings did not change. The second measure equals the change in
advisor shares held of the acquirer, from quarter t-1 to quarter t. The third measure equals the change in advisor
shares held net of the average change in non-advisor institutional shareholdings of the acquirer. T-tests are for
differences between downgrades and upgrades.
Panel A: Differences in Advisor positions from 5 qtrs pre-ann’t – 5 qtrs post-completion
No Adv. Rec
Adv. Downgrade Adv. Upgrade T-Test
Number Observations 408 7,138 682
Indicator variable for chg in
advisor position -0.01 0.08 0.13 2.88***
∆Advisor Shares Held
44,266 89,880 134,204 1.66*
∆Advisor Shares, net of avg
∆non-advisor shares 19,290 59,250 91,145 1.32
Panel B: Differences in Advisor positions from 5 qtrs pre-ann’t through 1 qtr pre-annt
No Adv. Rec
Adv. Downgrade Adv. Upgrade T-Test
Number Observations 147 2,416 293
Indicator variable for chg in
advisor position 0.05 0.09 0.15 1.36
∆Advisor Shares Held
85,643 77,517 68,090 -0.25
∆Advisor Shares, net of avg
∆non-advisor shares 64,016 50,651 28,822 -0.51
Panel C: Differences in Advisor positions from 1 qtr post-annt through 5 qtrs post-completion
No Adv. Rec
Adv. Downgrade Adv. Upgrade T-Test
Number Observations 261 4,677 388
Indicator variable for chg in
advisor position -0.05 0.07 0.12 2.51***
∆Advisor Shares Held
20,961 97,562 184,477 2.08**
∆Advisor Shares, net of avg
∆non-advisor shares -5,998 65,322 139,072 1.88*
Table 5: Determinants of change in acquirer shares held by the advisor investment bank
This table shows fixed effects regressions, where the dependent variable is one of three measures of changes in
advisor ownership of the acquirer firm: (1) an indicator variable, equal to 1 if the advisor bank increased holdings in
the acquirer in quarter t, -1 if the advisor bank decreased holdings, and 0 if holdings did not change; (2) the change
in advisor shares held of the acquirer, from quarter t-1 to quarter t; (3) the change in advisor shares held net of the
average change in non-advisor institutional shareholdings of the acquirer. Regressions are estimated over the 1048
advisor-level observations, for five quarters prior to the merger announcement to five quarters following the merger
completion. The first independent variable is the change in the advisor analyst recommendation of the acquirer
company (measured over the same quarter but observed prior to the measurement of institutional ownership). This
recommendation is interacted with both a pre-merger dummy and a post-merger dummy (equal in 1 in the quarters
prior to and following the merger announcement, respectively, 0 otherwise). All recommendation changes are
multiplied by negative 1, such that higher recommendations and increases in recommendations can be interpreted as
more positive recommendations. Dummies for the level of the advisor recommendation at the beginning of the
quarter are included (strong buy, buy, and hold). The change in market capitalization represents the change in the
market capitalization of the acquirer company over the quarter. Adv sharest-1 equals the number of shares held by
the advisor in the previous quarter. For stock mergers in the first quarter following merger completion, Adv shares
in targett=-1 equals the number of shares held by the acquirer advisor in the target firm one quarter prior to merger
completion; for all other firm quarters this variable equals 0. T-statistics are shown in parentheses.
Announcement to 5 qtrs
5 qtrs pre-annt through 5 qtrs post-completion
Dept Variable Indicator Indicator ΔAdv Shrs ΔAdv Shrs -
Variable Variable ΔNon Shrs
ΔRec (Advisor) 0.08** 0.10** 0.09**
(2.52) (2.28) (1.99)
ΔRec (Non-Advisor) -0.01 -0.001 0.02
(-0.19) (-0.03) (0.38)
ΔRec * Pre- Merger (Advisor) 0.07 0.01
ΔRec * Post Merger (Advisor) 0.09** 0.09**
ΔRec * Pre Merger (Non-Adv) 0.01 -0.02
ΔRec * Post Merger (Non-Adv) -0.02 -0.005
Strong Buy Dummy (Advisor) 0.03 0.03 0.02 0.004 0.005
(0.49) (0.42) (0.31) (0.05) (0.06)
Buy Dummy (Advisor) 0.02 0.02 0.02 0.009 0.008
(0.41) (0.35) (0.36) (0.11) (0.10)
Hold Dummy (Advisor) -0.02 -0.02 -0.02 -0.13 -0.12
(-0.28) (-0.33) (-0.42) (-1.60) (-1.48)
ΔMkt Cap 6.05*** 6.03*** 7.97*** 8.50*** 6.56***
(3.75) (3.73) (5.11) (4.37) (3.42)
Adv Sharest-1 -37.08*** -46.21*** -45.25***
(-11.26) (-10.70) (-10.63)
Qtr t-1 Dum*Adv Shares in 215.96*** 186.59*** 174.01***
Targett=-1 (6.73) (5.21) (4.93)
N Obs 7085 7085 7028 4587 4580
Table 6: Analyst Recommendations, conditional on source of investment bank revenue
This table shows regressions of advisor bank analyst recommendations and advisor bank analyst upgrades. In
column 1, analyst recommendations are ordered from 1 to 5, with 5 being the most positive. In column 2, the
dependent variable equals 1 if the advisor upgraded the acquirer during quarter t, zero otherwise. The data represent
a panel dataset, with firm quarters extending from the first quarter following merger announcement through 5
quarters post-merger completion. The dependent variables are regressed on the percent of revenue the advisor bank
obtains from investment banking and the percent of revenue the bank obtains from trading. Control variables
include: acquirer market capitalization, measured one quarter prior to merger completion; dummy variables
denoting the recommendation level at the end of the previous quarter; the number of shares held by the advisor bank
in the acquirer company at the end of the previous quarter; stock and cash dummies denoting the method of payment
in the merger; and the relative size of the merger, defined as the target market capitalization divided by the market
capitalization of the new, combined company. T-statistics are reported in parentheses.
Announcement to 5 qtrs post-completion
Dep’t Var Adv Rec Adv Upgrade
Constant -2.06*** 0.51***
%Rev from IB 2.43*** 0.20**
%Rev from Trade -1.39*** -0.13***
Acquirer Mcap 5.55*** 0.52**
Rec 1 Dummy -0.54***
Rec 2 Dummy -0.47***
Rec 3 Dummy -0.42***
Shrs Held Advt-1 -6.76 -1.67**
M&A annt AR 0.27* 0.06
Stock dummy 0.06* 0.02*
Cash dummy -0.16*** -0.02
Relative Size 0.09** 0.02**
Table 7: Change in advisor shares of acquirer, conditional on sources of advisor bank revenue
This table shows fixed effects regressions, where the dependent variable is the change in shares owned by the advisor investment bank in the acquirer company.
Regressions are estimated over those advisor-level observations for which we are able to obtain sources of revenue data for the advisor investment bank, beginning
in the quarter following merger announcement and continuing through five quarters post-completion. The first independent variable is the change in the advisor
analyst recommendation of the acquirer company (measured over the same quarter but observed prior to the measurement of institutional ownership). The
recommendation change is interacted with a high IB dummy, equal to one if the advisor bank’s investment banking revenues as a fraction of total revenues fell
above the median (when ranked across all investment banks in that year) for the year of the merger, and zero otherwise. The recommendation change is also
interacted with a high Trade dummy, equal to one if the advisor bank’s trading revenues as a fraction of total revenues fell above the median (when ranked across
all investment banks in that year) for the year of the merger, and zero otherwise. Similarly, recommendation changes are also interacted with low IB dummies and
low trade dummies. Dummies for the level of the advisor recommendation at the beginning of the quarter are included (strong buy, buy, and hold). The change in
market capitalization represents the change in the market capitalization of the acquirer company over the quarter. Adv sharest-1 equals the number of shares held by
the advisor in the previous quarter. For stock mergers in the first quarter following merger completion, Adv shares in targett=-1 equals the number of shares held by
the acquirer advisor in the target firm one quarter prior to merger completion; for all other firm quarters this variable equals 0. T-stats are shown in parentheses.
All Advisor Recommendation Changes Advisor Upgrades Advisor Downgrades
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
ΔAdv Rec 0.01** 0.14** 0.08
(2.29) (2.32) (1.30)
ΔAdv Rec * Low Trade 0.04 0.11 -0.03
(0.58) (1.11) (-0.22)
ΔAdv Rec * High Trade 0.28*** 0.31*** 0.30**
(3.57) (2.86) (2.45)
ΔAdv Rec * Low IB 0.13* 0.26*** -0.02
(1.71) (2.58) (-0.12)
ΔAdv Rec * High IB 0.18** 0.14 0.26**
(2.35) (1.30) (2.21)
Adv Strong Buy Dummy 0.004 -0.01 -0.002 0.03 0.02 0.03 -0.01 -0.02 -0.01
(0.05) (-0.11) (-0.02) (0.36) (0.18) (0.31) (-0.13) (-0.13) (-0.11)
Adv Buy Dummy 0.01 0.001 0.005 0.03 0.01 0.02 -0.03 -0.03 -0.03
(0.10) (0.02) (0.06) (0.30) (0.13) (0.27) (-0.27) (-0.23) (-0.24)
Adv Hold Dummy -0.12 -0.13 -0.12 -0.10 -0.11 -0.10 -0.17 -0.16 -0.16
(-1.59) (-1.64) (-1.56) (-1.25) (-1.38) (-1.21) (-1.51) (-1.46) (-1.44)
ΔMkt Cap 8.51*** 8.36*** 8.49*** 7.20*** 7.08*** 7.19*** 8.36*** 8.37*** 8.38***
(4.40) (4.33) (4.40) (3.66) (3.60) (3.66) (4.18) (4.18) (4.18)
Qtr t-1 Dum * Adv -46.21*** -45.85*** -46.01*** -43.84*** -43.47*** -43.59*** -46.22*** -46.18*** -46.14***
Shares heldt-1 (-10.76) (-10.69) (-10.72) (-10.13) (-10.05) (-10.07) (-10.39) (-10.38) (-10.37)
Shares in Target 0.19*** 0.19*** 0.19*** 0.21*** 0.21*** 0.21*** 0.17*** 0.17*** 0.17***
(5.24) (5.20) (5.21) (5.81) (5.77) (5.82) (4.57) (4.59) (4.58)
N Obs 4635 4635 4635 4412 4412 4412 4294 4294 4294
Table 8: Change in advisor shares net of change in non-advisor shares, conditional on sources of advisor bank revenue
This table shows fixed effects regressions, where the dependent variable the change in advisor shares held net of the average change in non-advisor institutional
shareholdings of the acquirer. Regressions are estimated over those advisor-level observations for which we are able to obtain sources of revenue data for the
advisor investment bank, beginning in the quarter following merger announcement and continuing through five quarters post-completion. The first independent
variable is the change in the advisor analyst recommendation of the acquirer company (measured over the same quarter but observed prior to the measurement of
institutional ownership). The recommendation change is interacted with a high IB dummy, equal to one if the advisor bank’s investment banking revenues as a
fraction of total revenues fell above the median (when ranked across all investment banks in that year) for the year of the merger, and zero otherwise. The
recommendation change is also interacted with a high Trade dummy, equal to one if the advisor bank’s trading revenues as a fraction of total revenues fell above
the median (when ranked across all investment banks in that year) for the year of the merger, and zero otherwise. Similarly, recommendation changes are also
interacted with low IB dummies and low trade dummies. Dummies for the level of the advisor recommendation at the beginning of the quarter are included (strong
buy, buy, and hold). The change in market capitalization represents the change in the market capitalization of the acquirer company over the quarter. Adv sharest-1
equals the number of shares held by the advisor in the previous quarter. For stock mergers in the first quarter following merger completion, Adv shares in targett=-1
equals the number of shares held by the acquirer advisor in the target firm one quarter prior to merger completion; for all other firm quarters this variable equals 0.
T-stats are shown in parentheses.
All Advisor Recommendation Changes Advisor Upgrades Advisor Downgrades
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
ΔAdv Rec 0.08** 0.12** 0.07
(1.96) (1.99) (1.15)
ΔAdv Rec * Low Trade 0.03 0.08 -0.03
(0.38) (0.85) (-0.24)
ΔAdv Rec * High Trade 0.25*** 0.26** 0.28**
(3.20) (2.45) (2.33)
ΔAdv Rec * Low IB 0.11 0.23** -0.02
(1.45) (2.26) (-0.15)
ΔAdv Rec * High IB 0.15** 0.10 0.24**
(2.04) (0.94) (2.10)
Adv Strong Buy Dummy 0.004 -0.006 -0.0001 0.03 0.01 0.03 -0.02 -0.02 -0.02
(0.06) (-0.08) (-0.00) (0.36) (0.17) (0.30) (-0.18) (-0.17) (-0.16)
Adv Buy Dummy 0.007 0.001 0.005 0.02 0.01 0.02 -0.04 -0.03 -0.03
(0.09) (0.02) (0.06) (0.24) (0.07) (0.20) (-0.32) (-0.28) (-0.29)
Adv Hold Dummy -0.12 -0.12 -0.11 -0.10 -0.11 -0.09 -0.16 -0.16 -0.15
(-1.48) (-1.52) (-1.45) (-1.17) (-1.31) (-1.14) (-1.44) (-1.40) (-1.38)
ΔMkt Cap 6.52*** 6.39*** 6.51*** 5.28 5.17*** 5.27*** 6.51*** 6.51*** 6.52***
(3.42) (3.35) (3.42) (2.73) (2.67) (2.72) (3.30) (3.30) (3.30)
Qtr t-1 Dum * Adv -45.24*** -44.92*** -45.07*** -42.97 -42.65*** -42.76*** -45.37*** -45.34*** -45.30***
Shares heldt-1 (-10.69) (-10.63) (-10.66) (-10.08) (-10.01) (-10.03) (-10.34) (-10.34) (-10.33)
Shares held in target 0.17*** 0.17*** 0.17*** 0.20 0.19*** 0.20*** 0.16*** 0.16*** 0.16***
(4.96) (4.92) (4.93) (5.53) (5.49) (5.55) (4.45) (4.46) (4.46)
N Obs 4627 4627 4627 4404 4404 4404 4287 4287 4287