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
Michelle Lowry •
Penn State University
Phone: (814) 865-1483
July 13, 2009
We thank Lubomir Petrasek for excellent research assistance. We thank Richard Bundro, Laura Field, Urs Peyer
and seminar participants at Case Western Reserve University, Hong Kong University of Science and Technology,
INSEAD, National University of Singapore, Singapore Management University, the University of Colorado, and the
University of Lausanne for helpful comments and suggestions.
When do banks listen to their analysts?
Evidence from mergers and acquisitions
We find that the asset management division of a bank ‘listens’ to its own analysts’
recommendations of client firms that have recently announced a merger. In contrast, we observe
no evidence of such a relation in the pre-merger announcement period or among non-advisor
banks. Empirical results suggest that increased information sharing across divisions regarding
the value of the acquirer, rather than pressure on both analysts and asset management divisions to
support the acquirer, explain this result. Among banks most sensitive to conflicts of interest
from the investment banking division, consistency across divisions is weakest. Finally, banks’
strategy of only listening to their analyst recommendations in times when the analyst is most
likely to have value-relevant information and in cases where analysts’ likely conflicts of interest
are lowest appears to be a profitable one. In sum, the value of interactions between divisions
within a financial institution varies with both conflicts of interest and the information
This study examines the interaction of divisions within financial conglomerates.
Although the divisions of a financial institution generally fall narrowly within the financial
industry, the fiduciary duties of these divisions vary substantially. An institution’s investment
banking division is often advising corporations that its analysts are recommending for outside
investors, and its asset managers are trading these same stocks for the bank’s own account or for
other outside investors. This setting has the potential to lead to conflicts of interest in which the
activities of one division are favored at a cost to another. It also creates potential for information
sharing across divisions in ways that would not be possible among stand alone entities.
Although these interactions may be optimal for the financial conglomerate, they are not
necessarily in the best interests of the bank’s clients. These concerns are heightened by the
importance of information in the transactions that financial institutions specialize, as noted by
Mehran and Stulz (2007).
Prior literature provides evidence of information transfers within investment banks, from
the investment banking division to analysts and from the investment banking division to asset
management. Michaely and Womack (1999) find that analysts at affiliated banks are pressured
into making upwardly biased recommendations on client firms, while Massa and Rehman (2007)
find that mutual funds of affiliated banks obtain inside information that informs their investments
in client firms, enabling them to earn higher returns. The combined findings of these papers
highlight both the conflicts of interest and information advantages that can arise within a
financial conglomerate. Although conflicts of interests can diminish the performance of non-
investment banking divisions, informational advantages gained from investment banking can
also benefit other divisions. The focus of this paper is to examine the relative importance of
Our analysis on the association between the analyst and asset management divisions of
financial institutions focuses around two hypotheses. The ‘Division Consistency’ hypothesis
posits that investment banks invest in a manner consistent with the advice they are providing to
clients: they change their holdings of stocks in response to their own analysts’ upgrades and
downgrades. 1 From the perspective of investors relying on such recommendations, this is
obviously what is expected. However, from the perspective of the agents within the bank, we
expect to only observe divisional consistency if analysts and asset managers both face similar
incentives and also act on similar information sets.
Alternatively, the ‘Division Inconsistency’ hypothesis proposes that divisions act
divergently: firms that are upgraded by an institution’s analysts are as likely to be bought as to
be sold by its asset managers. A finding of division inconsistency indicates that the analysts and
assets managers face different conflicts of interests and/or that the divisions rely on different
We study these issues by following a financial institution’s analysts and asset managers
at the time that it advises an acquirer in a merger. Although potential conflicts of interest and
information sharing can be ongoing, they are arguably particularly large around mergers.
Mergers are a large source of revenues for investment banks, and the magnitude of these fees can
increase conflicts of interests within other divisions that could potentially support such deals.
While investment banks have buy-side analysts that directly report to asset management within the bank,
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
(see, e.g., Becher and Juergens, 2005, Kolanski and Kothari, 2009). 2 In addition, mergers are
important information events. As highlighted by Moeller, Schlingemann, and Stulz (2005), the
value of companies can change dramatically around mergers. Therefore, the potential benefits of
information flow within the financial institution are particularly large. 3
Our analysis of affiliated investment banks, i.e., banks advising the acquirer around a
merger event, provide support for the Division Inconsistency hypothesis in the period prior to the
merger announcement and the Division Consistency hypothesis in the period following the
merger announcement. More specifically, there is a strong positive relation between changes in
analyst recommendations and changes in bank holdings of the acquirer stock in the period
following the merger announcement, indicating that the banks, on average, are investing in a
manner consistent with recommendations made to clients. However, there is no significant
relation in the year leading up to this announcement, suggesting that the bank places a lower
value on this subset of recommendations. The increase in division consistency following the
merger announcement is not consistent with an increased bias in analyst recommendations
combined with an increased precision of asset management investments, as suggested by prior
The increase in division consistency indicates that there was a change in information
sharing across divisions at this time. We note that information sharing across divisions can take
different forms. Under one scenario, if the investment banking division shares information on
the quality of the merger with analysts, this should enable the analyst to make a better
In 2007 alone, the top 20 investment banks earned more than $42 billion in fees from underwriting mergers and
acquisitions, about half of the total fees that they earned from all investment banking activities. In addition to these
direct fees, mergers can also lead to revenues from follow-on business, including financing and underwriting. See
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.
recommendation and one would expect the asset management divisions of the bank to be more
likely to listen to these better recommendations. 4 However, under an alternative scenario, the
investment banking division may use their information on the deal to pressure both analysts and
asset management divisions to support the deal: analysts to make positive recommendations on
the acquirers that it has recently advised, and asset management divisions to increase
shareholdings of these acquirers (either on the bank’s own account or through mutual funds).
Although both are technically forms of information sharing, the first scenario results in better
quality advice to clients and better trading decisions. The second scenario, the result of conflicts
of interest, yields less useful advice and lower returns from asset management.
We conduct four tests to examine the ways in which different types of information
sharing across divisions may explain the increased consistency between analyst
recommendations and bank investment decisions following the merger announcement. Each test
sheds light on whether the increased division consistency reflects pressure on both analysts and
asset management to support the investment banking division, or whether it is consistent with
analysts having more information to make better recommendations and asset management
following these better recommendations. First, we compare the abnormal returns around
recommendation changes in the pre-merger announcement versus post-merger announcement
period. Second, we examine the patterns in bank investment decisions around upgrades versus
downgrades. Third, we develop proxies for the quality of the recommendation and the extent of
conflicts of interest, and examine whether banks are more or less likely to follow different
subsets of recommendations. Finally, we examine whether banks’ strategy of following their
analysts’ recommendations of client firms is profitable.
It is also possible that the asset management divisions received similar information themselves and therefore have
a similar view as the analysts.
Empirical results across these four tests suggest that the increased division consistency
following the merger announcement primarily reflects increased information sharing from the
investment banking division, resulting in higher quality analyst forecasts that asset management
is more likely to follow. We find that the market reaction to analyst recommendation changes is
significantly greater in the post-announcement period, suggesting that these recommendations
contain more information. Moreover, the market reaction recommendation changes by affiliated
analysts is significantly greater than the reaction to unaffiliated analyst recommendation changes,
indicating that the market pe5rceives affiliated analysts to have more valuable information. In
addition, the consistency between analyst recommendations and asset management investments
is most pronounced for higher quality analysts, again consistent with the increase in division
consistency reflecting quality of information rather than common conflicts of interest across
asset management and analysts.
Across all tests, results provide no support for the idea that the increase in divisional
consistency is driven by pressure on both asset management divisions and analysts to support the
merger. Rather, we find that the extent of divisional consistency is mitigated by conflicts of
interest. For example, we find no significant relation between analyst recommendation changes
and bank investments within those banks where analysts likely face more severe conflicts of
interest. Also, the relation between bank investment decisions and analyst recommendation
changes is concentrated around analyst downgrades; there is less evidence that banks are more
likely to buy shares around analyst upgrades. To the extent that upgrades are more likely driven
by conflicts of interest, this suggests that the increase in division consistency caused by
information sharing is concentrated among those cases where conflicts of interest are least likely
to play a role.
Finally, stock returns following changes in holdings show the value of information
around mergers. A strategy of following a subset of analyst recommendations, recommendations
that are most likely to be based on valuable information and least likely to be biased by conflicts
of interest, appears to be a good one. Conditional on a recommendation change, those acquirers
in which the advisor bank increased holdings outperformed those in which the bank decreased
holdings by an average 1.36% per month over the subsequent three 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 the literatures on both information sharing and conflicts of
interest within investment banks. Aggarwal, Prabhala, and Puri (2002), Schenone (2004),
Drucker and Puri (2005), Bodnaruk, Massa, and Simonov (2007), Massa and Rehman (2008),
Michaely and Womack (1999), and Ljungqvist, Marston, and Wilhelm (2005) all document
information sharing within investment banks. Information sharing affects the interactions
between analysts and the investment banking division, the relations between banks and affiliated
mutual funds, the quality of merger advice, and the loan terms between commercial and
underwriting banks. In some cases, such information sharing appears to benefit clients of the
bank, for example providing mutual fund investors with higher returns and causing IPO firms to
be less underpriced. However, in other cases, clients of the bank are harmed, for example by
investing in recent IPOs after observing a positive recommendation by an affiliated analyst.
Moreover, in several high profile cases, investment banks have been sharply criticized for
publicly supporting certain assets that informed players within the bank believed to be
overvalued. We examine the effects of information sharing in a setting in which both likely
downsides and upsides for clients are substantial. Moreover, we consider the effects of
information flows between multiple portions of the bank: investment banking, analysts, and
Our paper proceeds as follows. Section 2 outlines the data and sample characteristics.
Section 3 tests the divisional consistency versus divisional inconsistency hypotheses, by
empirically examining the relation between analyst recommendations and institutional trades by
the advisor investment bank. Section 4 investigates the ways in which information sharing and
conflicts of interest contribute to divisional consistency. Section 5 provides an analysis of stock
returns, which quantifies the potential gains from considering both the presence of an analyst
recommendation change and the likely information set and incentives behind this change.
Section 6 examines whether non-advisor banks follow advisor analyst. Finally, Section 7
discusses several robustness checks, and Section 8 concludes.
2.1 Sample Construction
Our data consists of mergers and acquisitions between 1995 and 2007, 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. 5 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. To remove confounding interests, we do not include advisors to the target
firms in this non-advisor consensus measure. We compute analyst upgrades as cases where an
Ljungqvist, Malloy, and Marston (2009) document data problems with IBES tapes. Consistent with the authors’
recommendations to future researchers, our analysis is based on the 2007 IBES download, which is less likely to
contain biased data.
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 and downgrades. 6
2.2 Sample Characteristics
As shown in Table 1, these requirements result in a sample of 1,197 mergers. Among
these 1,197, 154 were announced but never completed. Across the mergers, 555 are stock
acquisitions, 196 are cash, and 446 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 1,413
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.
We thank Leonardo Madureira for providing the dates on which the banks revised recommendations in an effort to
comply with the Global Settlement.
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 acquirer and by whether the advisor owns shares
in the acquirer, both measured one quarter prior to the merger announcement. Several
differences become apparent. The acquirers covered by the advisor’s analyst and owned by the
advisor are larger than other acquirers. This finding 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 and issue analyst recommendations have higher market-to-book ratios,
higher leverage ratios, higher profitability, and lower working capital as a fraction of total assets.
Finally, relative merger size is significantly lower among companies in which advisors provide
analyst coverage and own shares. This difference in relative merger size is potentially driven by
differences in firm size – companies in which the advisor bank 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 five quarters prior to the merger
announcement and continues through five quarters following the merger completion (or through
the withdrawal date for non-completed mergers). In conducting this analysis, we assume that an
investment bank’s expectations regarding 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
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.7 For example, the percent of advisors
with analyst coverage increases from 48% five quarters prior to the merger announcement to
57% one quarter before the merger announcement. While this increase is monotonic across
quarters, we observe no systematic pattern in advisor analysts as a percentage of all analysts
covering the acquirer, which varies between 11.4% and 12.0%. Evidently other analysts are also
picking up coverage of the acquirer during this time. Columns (3) and (4) show that advisor
analyst recommendations are consistently more optimistic than non-advisor recommendations,
where analyst recommendations are measured on a scale from one to five, with one being the
Turning to the right-hand side of the table, the percent of advisors owning shares of the
acquirer increases from 54% to 58% during the pre-announcement period, but actually decreases
slightly as a fraction of shares owned by all institutions, from 0.94% to 0.89%. In sum, the
results provide little evidence of disproportionate changes in ownership or analyst coverage by
the advisor during this period. Rather, much of the increases in advisor analyst coverage and
advisor share ownership appear to be driven by increases in the size of the acquirer firm over the
quarters prior to the merger announcement. These increases in firm size cause an increase in
overall analyst coverage and institutional ownership in the acquirer firm.
As noted previously, non-advisors exclude advisors to both the acquirer and the target firms.
3. Are changes in advisors analyst recommendations and stockholdings correlated?
Our tests of the divisional consistency versus inconsistency hypotheses focus on the
relation between changes in the advisor’s analyst recommendations and changes in the advisor’s
stockholdings. If the banks invest in a manner consistent with the advice they provide to clients,
we would expect a positive relation. However, if one of the divisions faces conflicts of interest
different from the other division or if the asset management division has no confidence in the
quality of the information analysts are conveying in their recommendations, we would not expect
to observe divisional consistency.
3.1 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 in
terms of both raw changes in shares held and percentage changes in shares held, where the
percent change is measured as number of shares held in quarter t minus number of shares held in
quarter t-1, all deflated by the number of shares outstanding in quarter t-1. The data underlying
the analyses represent a panel dataset, with one observation for each acquirer firm advisor in
Table 4 shows that 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 474 advisor bank downgrades of
acquirer firms, 777 upgrades, and 8,755 firm quarters with no change in advisor bank
recommendation. The frequency of downgrades is notable and contrasts strongly with
recommendation patterns following IPOs, where affiliated analysts almost always initiate with
very positive recommendations (see, e.g., Michaely and Womack, 1999). On average across the
474 downgrades, advisors increased their shareholdings by 44,279 shares, compared to an
increase of 84,621 shares in firm quarters with no recommendation change and 122,323 shares in
firm quarters with an analyst upgrade (by the advisor bank). 8 The t-stat for the difference
between downgrades and upgrade quarters equals 1.66, significant at the 10% level. Similarly,
we observe a monotonic increase in the percentage change in shares held, as we move from
downgrades, to no recommendation change, to upgrades, however the difference in percentage
changes between downgrade quarters and upgrade quarters is not significant at conventional
Looking at Panel B, in the five quarters leading up to the merger announcement there are
almost twice as many upgrades of the acquirer by the advisor analysts as downgrades (389 to
199). Results, however, indicate that there is no relation during this pre-announcement period
between changes in these recommendations and changes in 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 (or through the withdrawal date for
non-completed mergers). Regardless of the measure for change in stockholdings used, the
results indicate that advisors invest significantly more shares in acquirers that their analyst
upgraded than those that they downgraded. Moreover, there is a monotonic increase in both
Across the entire sample of firm quarters, both raw changes and percent 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).
measures (from downgrade, to no change, to upgrade). For example, percentage change in
shares held equals 0.13% across the 275 downgrades, 0.45% across the 5,001 firm quarters with
no recommendation change, and 0.88% across the 388 upgrade quarters.
3.2 Regression Analysis of Changes in Recommendations and Stockholdings
Table 5 examines this relation between changes in analyst recommendations and percent
changes in stockholdings in a regression framework. The dependent variable in each regression
equals the percentage change in shares held, as defined previously (number of shares held in
quarter t minus number of shares held in quarter t-1, all deflated by the number of shares
outstanding in quarter t-1). In columns 1 and 2, regression observations include the period
beginning five quarters prior to the merger announcement and extending through five quarters
following the merger completion (or through the withdrawal date for non-completed mergers).
In column 3, the sample is restricted to those quarters preceding the merger announcement, and
in column 4 the sample represents those quarters following the merger announcement.
Regressions are estimated with maximum likelihood, firm fixed effects, and standard errors
clustered by calendar year.
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. We only include dummies for strong buy, buy, and hold, because there are fewer
observations with lower recommendations (sells and strong sells). We control for the change in
the consensus recommendation across all non-advisor analysts and for the change in market
capitalization of the acquirer. We also include lagged percent of shares held by the advisor bank
in the acquirer firm, to account for the fact that a bank may be less likely to increase its holdings
if it already holds a substantial number of shares. Finally, we include an estimate of the number
of acquirer shares that the advisor bank would obtain automatically following completion of a
stock merger, as a result of shares previously held in the target. For stock mergers in the first
quarter following merger completion, we estimate this as the number of shares owned in the
target prior to merger completion times the ratio of target to acquirer price one day prior to
merger completion. This variable equals zero for all other firm quarters.
The results show the variation in the relation between changes in recommendations and
stock holdings around mergers. Column 1 shows a positive coefficient on change in advisor
recommendation, consistent with advisors changing their stock holdings in the same direction as
the change in their analyst recommendations. However, the coefficient is not significant at
conventional levels. The results in column 2, however, indicate that the lack of significance over
the entire event period actually combines two very different effects: a highly significant relation
over the post-announcement period and a lack of any significant relation in the pre-
announcement period. The interaction term, change in advisor analyst recommendation * post-
merger dummy, is significantly positive (t-statistic = 3.15). In contrast, the interaction term
advisor analyst recommendation * pre-merger dummy is negative and not significant at
conventional levels (t-statistic = -0.83). A Chi-squared tests indicates that these two coefficients
are significantly different (χ2 = 3.52, p-value = 0.06). Columns 3 and 4 yield similar inferences.
In column 3, where the sample only includes pre-announcement firm quarters, we observe no
significant relation between analyst recommendation changes and changes in stock positions.
However, the relation is positive and highly significant during the post-merger announcement
period (column 4).
Our evidence is somewhat inconsistent with the findings of Chan, Cheng, and Wang
(2009) who find a significant relation between analyst recommendations and in-house trading
throughout time. It is possible that their larger sample size (which they obtain by looking at all
firms across a ten-year sample period) gives them more power to find significant differences.
However, as a robustness check we also examine the possibility that our finding of a lack of
significance in the pre-merger announcement period is in some way related to the merger. For
example, if asset management knew of the merger ahead of time, they might be trading on inside
information during this period. In contrast, even if analysts knew of the information ahead of
time, they would be unlikely to convey it in public releases. To examine this, we re-estimate the
pre-merger announcement regression (column 3 of Table 5), using quarters -10 through -6,
relative to the merger announcement. No one within the bank is likely to foresee the merger this
far ahead of time, thereby lessening the probability that merger-related information flows are
affecting results. Results (untabulated) are qualitatively similar to those for quarters -5 through -
1: there is no evidence of a relation between analyst recommendation changes and investments
by asset management.
Results in Table 5 show different patterns in divisional consistency across the pre-merger
announcement versus post-merger announcement periods. In the pre-announcement period,
advisor banks’ investment decisions are completely unrelated to the advice being provided to
clients, suggesting the banks themselves do not believe in the information they are publishing.
However, following the merger announcement, advisor banks’ investment decisions are
positively related to the advice being provided to clients. Do analysts have higher quality
information in this post-announcement period, possibly as a result of information sharing from
the investment banking division? Alternatively, is pressure from the investment banking
division causing both analysts to upgrade the acquirer stocks and the asset management division
to purchase acquirer shares (either on its own account or through its mutual funds)? The
distinction is an important one: the first scenario implies a greater value in analyst
recommendations in the post-announcement period, while the second scenario actually implies
the reverse. The following section investigates in more depth the reasons for the greater
divisional consistency following the merger announcement.
4. Information Sharing versus Conflicts of Interest
4.1 Analyst upgrades versus downgrades
As a first step toward understanding the source of the greater divisional consistency in the
post-merger announcement period, we compare the extent to which asset management divisions
(of the advisor bank) invest in response to affiliated analyst upgrades versus downgrades. If the
investment banking division places pressure on both analysts and asset management divisions to
support the acquirer, this pressure would likely take the form of analyst upgrades and stock
purchases. Thus, if such pressure from investment banking explains the increased consistency
during the post-announcement period, we would expect this consistency to be greatest around
analyst upgrades. Alternatively, a finding of a stronger relation around downgrades would
suggest that conflicts of interest are stronger for the analysts, less for the asset management side.
The asset management side might be more likely to respond to downgrades because they are less
likely to be biased by conflicts of interest.
Table 6 shows two regressions, similar to those shown in table 5 except that the sample in
column 1 is limited to firm quarters with an analyst upgrade or no recommendation change, and
the sample in column 2 is limited to firm quarters with an analyst downgrade or no
recommendation change. The dependent variable in each is the percentage change in advisor
bank shareholdings in the acquirer, as defined earlier. Independent variables include the change
in advisor bank recommendation in the pre-announcement period, the change in advisor bank
recommendation in the post-announcement period, plus the same control variables as in Table 5.
Across both regressions, upgrades are denoted as a positive recommendation change and
downgrades as a negative recommendation change. Regressions are maximum likelihood, with
firm fixed effects and standard errors clustered by calendar year.
In column 1, we find no relation between analysts upgrades and changes in advisor
holdings. In contrast, column 2 shows a significant relation between downgrades and changes in
advisor holdings of the acquirer. When the advisor analyst downgrades the acquirer, the advisor
is significantly likely to sell more shares.
The finding that changes in the advisor’s shareholdings are only related to analyst
downgrades provides preliminary evidence against the idea that the increase in division
consistency following the merger announcement reflects pressure from the investment banking
division on both analysts and asset management to support the acquirer. Rather, results suggest
that the asset management divisions tend to place more weight on analyst downgrades, perhaps
because they are less likely affected by conflicts of interest.
4.2 Abnormal returns to analyst recommendations
If information sharing across divisions increases the accuracy of the advisor’s analyst
recommendations in the post-announcement period, we would expect a greater market reaction
to the recommendation changes in this period. Alternatively, if conflicts of interest decrease the
quality of advisor bank analyst recommendations in the post-announcement period, we would
expect less of a market reaction in this period, particularly for analyst upgrades.
Panel A of Table 7 shows the abnormal return around analyst recommendation changes
in the pre-announcement period and the post-announcement period, where abnormal returns are
defined as the cumulative firm return over days -1 through 1 net of the value-weighted market
return over this same period. Day 0 represents the day of the recommendation change. Row 1
shows the abnormal return across analyst upgrades, and row 2 across analyst downgrades.
Results indicate that the magnitude of the abnormal return is greater in the post-
announcement period, particularly with respect to downgrades. The abnormal return to upgrades
is insignificantly different between the pre-announcement and post-announcement periods.
However, the abnormal return to downgrades is -3.5% in the pre-announcement period versus
-5.9% in the post-announcement period, a difference that is significant at the 5% level (t-statistic
Moreover, panel B shows that the market reaction to recommendation changes by the
advisor analyst is significantly greater than the market reaction to non-advisor recommendation
changes. Around upgrades, the average abnormal return to advisor analyst recommendation
changes is 2.4%, compared to 1.3% for non-advisor analysts, a difference that is significant at
the 1% level (t-statistic = 2.82). Analogously, around downgrades the average abnormal return
to advisor analyst recommendation changes is -5.9%, compared to -4.3% for non-advisor
analysts (t-statistic = 2.06).
The finding that the market reaction to advisor analyst recommendation changes is
stronger in the post-announcement period, combined with stronger market reactions to advisor
analyst recommendation changes than non-advisor analyst recommendations provides additional
evidence that the quality of information behind advisor analyst recommendations is particularly
high following the merger announcement, potentially as a result of information sharing from the
investment banking division. However, the greater market reactions to downgrades than
upgrades suggest that conflicts of interest are also important.
4.3 Level of conflicts of interest in banks, Quality of analysts and sources of revenue
To provide additional evidence into the ways in which information sharing versus
conflicts of interest affect interactions between divisions, this section strives to develop proxies
for both the extent of conflicts of interest within a bank as well as the ability of an analyst to
skillfully interpret information.
To examine the extent of conflicts of interest within investment banks, we classify
investment banks based on their sources of revenue. Following 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.
If pressure from investment banking also extends to asset management divisions, then we would
expect the higher conflict of interest banks to be more likely to buy these same stocks.
For each publicly traded advisor investment bank, we obtain source of revenue data from
the bank’s 10K. Because not all banks in our sample 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. Investment banks are required to describe the source of their revenues, and the
banks generally break down the revenues into those from investment banking, as well as those
from various other activities on which we are not focusing. Thus, for each of these banks in each
year during which they were publicly traded, we are able to determine the fraction of revenues
from investment banking.
To examine analyst ability we follow Loh and Mian (2006) and use the average prior
forecast error of each advisor bank analyst in our sample, i.e., the analysts at the advisor bank
issuing recommendations on the acquirer firm. For each of these analysts, we collect data on
quarterly earnings forecasts he or she has made (on all firms he or she follows) over the prior
three years, where forecasts consist of the last forecast made prior to the end of the forecasted
firm’s fiscal quarter. We calculate the forecast error as the absolute value of the difference
between the forecast and actual earnings, deflated by the absolute value of earnings.
Although we expect percent of revenues from investment banking to be positively related
to the level of analyst recommendations, we do not expect any relation between analyst quality
and the level of analyst recommendations. Table 8 confirms both these predictions. 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).
Analyst recommendations for each firm are measured at the end of the first quarter following the
merger announcement. Consistent with Agrawal and Chen (2008), we find that
recommendations are significantly more positive for firms that receive a greater portion of
revenues from investment banking (t-stat = 2.35). In contrast, there is no relation between the
analyst forecast error and the level of the recommendation. Control variables indicate that
investment banks tend to issue more positive recommendations about larger firms, and they tend
to issue more positive recommendations about firms that are making stock acquisitions.
Table 9 uses these proxies to categorize banks according to magnitude of conflicts of
interest and analyst quality. Specifically, for each year, we classify banks with above-median
(below-median) percent of revenues from investment banking as high (low) investment banking.
Similarly, analysts with above-median (below-median) forecast error are classified as low (high)
quality analysts. Table 9 is restricted to those observations for which we have the source of
revenues for the advisor bank and prior analyst forecasts to compute analyst quality. For each
firm, the sample consists of the first quarter following the merger announcement through five
quarters following the merger completion.
Similar to Table 5, Table 9 shows maximum likelihood regressions of the percent change
in advisor holdings of the acquirer on changes in their analysts’ recommendations, with firm
fixed effects and standard errors clustered by calendar year. The only difference between
column 1 in this table and column 4 in Table 5 is that the sample is restricted to those mergers
for which we have sources of revenues data for the advisor bank and prior forecasts for the
analyst. 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
In columns 2 and 3, we restrict the sample to high quality and low quality analysts,
respectively, where high quality analysts are those with low forecast errors and vice versa for
low quality analysts. To the extent that information is shared between the investment banking
division and the analysts, we would expect to observe the highest divisional consistency among
high-quality analysts, who are better able to interpret the extra information and translate it into
meaningful recommendations. Alternatively, if conflicts of interest drive the increase in
divisional consistency, we might expect greater consistency within the sample of low quality
analysts, who are more easily pressured into issuing biased recommendations. Comparing
results in columns 2 and 3, we see results consistent with information sharing across divisions:
the relation between analyst recommendation changes and changes in advisor bank
shareholdings is only significant among the high quality analysts (t-statistic = 1.92).
Columns 4 and 5 similarly split the sample into two groups, but now the split is based on
percent of revenues from investment banking, with high IB banks in column 4 and low IB banks
in column 5. If both the analyst and the asset management divisions face pressure from the
investment banking division to support the acquirer, then we would expect the greatest divisional
consistency among high IB banks, where such conflicts are likely greatest. However, results
provide no support for the idea that the increase in division consistency reflects common
conflicts of interest across both asset management and analysts. Among banks most subject to
such conflicts (high IB banks), we observe no significant relation between analyst
recommendation changes and asset management investment decisions. Rather, the relation is
concentrated among low IB banks, where such conflicts are likely less severe.
In sum, results show that information sharing between the investment banking division
and analysts increases the value of analyst recommendations in the post-merger announcement
period, contributing to greater divisional consistency. They also, however, indicate that conflicts
of interest among analysts affect this relation. In particular, consistency is greater for analyst
downgrades than upgrades and greater when investment banking accounts for a small proportion
of the advisor’s revenues.
5. Returns from the advisors investment decisions following changes in recommendations
Results in Tables 4 through 9 suggest that the advisor bank selectively follows the subset
of analyst recommendations that is most likely to contain value-relevant information and least
likely to be driven by conflicts of interest. As an approximation of the bank’s level of success in
this strategy, we examine returns subsequent to changes in advisor shareholdings that are
conditional on analyst recommendation changes (i.e., returns from banks listening to their
analysts.) A finding that returns following the advisor’s purchases exceed returns following the
advisor’s sales suggests that the bank gained through its attention to not just the analyst
recommendations, but also the information set and incentives behind these recommendations.
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 (6 and
12 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 (6, 12 months). In Panel A of Table 10, 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 136 basis points per month (significant at the 5%
level) over the first three months following the institutional reporting date. Return differences
are not statistically significant over longer intervals.
Panel B of Table 10 shows a similar analysis, except that firms are placed into terciles
based on the change in shareholdings of the advisor 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. Similar to
inferences in Panel A, results indicate that this long-short portfolio produced significantly
positive returns of 154 basis points per month over the 3-month horizon.
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
find no evidence of significantly higher returns following advisor firm upgrades versus
downgrades. The finding that changes in the advisor’s analyst recommendations do not
unconditionally predict returns contrasts with the findings of Jegadeesh et al (2004), who find
that the quarterly change in consensus recommendations does predict returns. The results are
consistent with changes in recommendations reflecting an increase in both conflicts of interest
and information around mergers. Returns indicate that asset managers can sort the importance of
these factors when deciding whether to trade on these recommendations.
6. Do non-advisor institutions similarly rely on advisor bank recommendations?
Our results suggest that analysts to the advisor bank have more information regarding the
acquirer firm, on average. However, the extent of the greater reliability in the advisor analysts’
recommendations varies systematically across time, type of bank, and type of analyst. Empirical
tests that classify banks and analysts solely on readily available public information show that
banks only change their stock positions in response to analyst recommendations that are less
likely driven by conflicts of interest and more likely to contain value-relevant information,
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, other institutions
might also be expected to base their trades on them. To examine this proposition, we re-estimate
the regressions from Table 5, using the percent change in advisor shares held net of the average
percent change in non-advisor shares held. If other institutions similarly consider the advisor
analysts’ recommendations in light of the likely information and likely conflicts of interest
behind such recommendations, the advisor analyst recommendation change should not be
statistically significant in these regressions.
The results from these regressions are shown in Table 11. Notably, the coefficients on
the analyst recommendation variables are comparable to those in Table 5. The relation between
analyst recommendation changes and raw changes in percent advisor shares held is qualitatively
similar to that between analyst recommendation changes and net percent 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
This finding is consistent with the long-run returns evidence. There is no significant
difference in long-run returns for a strategy of buying all post-merger announcement advisor
analyst upgrades and shorting the analogous downgrades. Advisors primarily trade on the
subset of recommendations that is most likely to contain value-relevant information and is least
likely to be biased by conflicts of interest. The combination of findings presented in this paper
suggests that this determination is based on both private and public information, and is not
replicable by people outside of the bank. Moreover, the higher returns earned by advisor banks
only extend to a three-month horizon. By the time that advisor banks’ holdings are publicly
released (six weeks following the end of the quarter), the opportunity for higher returns no longer
7. Robustness Checks
7.1 Regulatory Changes
During our sample period, there were several important regulatory changes that altered
the structure of analyst recommendations and also the way that analysts could interact both with
outside investors and with other parts of the investment bank. In October 2000, Regulation Fair
Disclosure (Reg FD) required that all publicly traded companies disclose any material
information to all investors at the same time. Following the implementation of this rule, analysts
were no longer able to obtain information by calling companies directly; companies had to
provide any information to the entire public. In April 2003, the Global Settlement was reached,
which included a variety of provisions to address the conflicts of interest within investment
banks. For example, the requirement that investment banking departments and analysts be
separated via Chinese walls was strengthened, analysts were prohibited from going on IPO road
shows, and analyst compensation had to be independent of investment banking business. In
addition, in 2002 many brokerage houses refined their recommendation system, going from a
five-tier scale to a three-tier scale and making the ratio of optimistic to pessimistic
recommendations more balanced (see Kadan, Madureira, Wang, and Zach (2008) for a complete
discussion). These regulations should lessen the extent to information flow between the
investment banking division and analysts.
In an attempt to shed some light on the extent to which the dynamics observed in this
paper extended throughout our sample, we divide our sample into two parts: 1995 – 2000, and
2003 – 2007. While the smaller sample sizes weaken statistical significance, the magnitude of
the coefficient on analyst recommendation change*post-announcement period is approximately
equal in the two sub-samples (results not tabulated). Therefore, the importance of conflicts of
interest and information sharing persist after these regulatory changes.
We note that even in the presence of Chinese walls, those within an institution can have
greater insights into the factors affecting the actions of the institution’s other divisions, compared
to outsiders . Specifically, analysts may have better ability to interpret the actions of the
investment banking division and infer the quality of the merger, and asset management divisions
may have better ability to interpret the importance of conflicts of interest and information content
in analyst recommendations. Common knowledge regarding company practices, compensation
schedules, incentive schemes, etc. likely increase understanding of the true meaning of certain
7.2 Econometric Specifications
The sample underlying many of our regressions represents a panel dataset. As discussed
by Peterson (2008), the appropriate handling of both standard errors and fixed effects in such
samples is paramount. Following Peterson, we have included firm fixed effects and clustered
standard errors by calendar year. The firm fixed effects allow for the fact that there may be
company-specific factors (i.e., characteristics of the acquirer firm) that affect a bank’s tendency
to invest in the company, but which we have not controlled for. The clustering of standard errors
allows for the fact that both analyst recommendations and institutional investment vary over
time, for example due to regulatory changes as discussed in the prior subsection and
macroeconomic conditions. Results are also robust to specifying the regressions using calendar
year fixed effects and clustering standard errors on the deal level.
7.3 Advisors to the Target
If the advisor to the target firm gains an intimate knowledge of the acquirer through the
merger negotiation process, then it is possible that this information may be similarly shared
among other divisions of the target firm. Specifically, the investment banking division of the
target advisor may share information regarding the acquirer with the target advisor’s analysts
and/or asset management divisions. If such value-relevant information sharing takes place, then
we would expect to see similar relations between analyst recommendation changes and asset
management investments (of the acquirer) within the target advisor bank. Alternatively, if the
advisor bank learns more about the long-run acquirer value by advising the acquirer than the
target, then the target bank may learn substantially less about the future value of the acquirer.
Also, many banks have long-run relationships with clients, suggesting that the knowledge of the
acquirer advisor may not stem just from this one merger, but rather from a long association with
To examine whether the analysts working for the target advisor similarly have more
valuable information around the time of the merger, we examine the relation between changes in
analyst recommendations and asset management investments, by the target advisor in the
acquirer firm. Results show no significant relation, either in the pre-merger or post-merger
periods. The results support the notion that asset management divisions of the target advisor do
not consider their analysts to have abnormally valuable insights into the value of the acquirer.
Results suggest that acquirer advisors either learn more about the value of the merger (compared
to target advisors) or benefit from a longer-term relationship with the acquirer.
The potential for information sharing is pervasive in investment banks. Such information
sharing can be either beneficial or detrimental to various clientele of the bank, depending on the
extent to which it results in higher quality information and better investments, versus biased
information and suboptimal investments. We investigation this issue using a novel approach, by
examining the association between an investment bank’s own response to its analysts
Consistent with Ljungqvist, Marston, Starks, Wei, and Yan (2007) and with Fang and
Yasuda (2008), our results indicate the quality of analyst advice varies in predictable ways.
Specifically, we find recommendations to be more value-relevant following an investment
banking event as more value-relevant information flows from the investment banking division, in
banks that rely less on investment banking as a source of revenue and are therefore less subject
to conflicts of interest, and among higher quality analysts that are better able to distill the newly
available information into a meaningful recommendation.
We find that banks consider this variation in recommendation quality when making their
investment decisions. Changes in advisor firm stockholdings in the acquirer are based on both
the recommendation changes of its analysts and the likely information set and incentives behind
these recommendation changes. This attention to detail is rewarded: returns to firms that banks
purchased conditional on an analyst recommendation change are significantly higher than those
in that the banks sold.
Finally, the findings have implications for the literature on the diversification of activities
of financial conglomerates. Supporting arguments of agency problems from diversification,
prior work such as Delong (2001) and Laeven and Levine (2007) find that increased
diversification destroys – or at least does not create value. Our work shows that the information
benefits that an institution realizes from offering diverse activities, as suggested by Stein (2002)
and others, depend on divisional incentives and information environment. Specifically, the
benefits an asset management division realizes from the institution’s other activities are
decreasing in the conflicts of interest for analysts and increasing in the information generated
from investment banking.
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Table 1: M&A Sample
The sample consists of 1,197 mergers over the 1995 to 2007 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. 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 1,413 advisor observations across the 1,197 mergers. Mergers
are classified into industries based on the Fama-French 12 industry groupings.
Relative Size > 5%
Number of advisor observations 1,413
Number of unique mergers 1,197
Year # Mergers Industry # Mergers
1995 99 Consumer Nondurables 25
1996 106 Consumer Durables 10
1997 168 Manufacturing 78
1998 166 Oil, gas, coal extraction 50
1999 125 Chemicals and allied products 24
2000 105 Business Equipment 197
2001 63 Telephone & TV transmission 34
2002 40 Utilities 36
2003 73 Wholesale, Retail 74
2004 74 Healthcare, Med. Eqpt, Drugs 105
2005 58 Finance 307
2006 68 Other 257
Table 2: Descriptive Statistics
Descriptive statistics are provided for the sample of 1,197 mergers over the 1995 – 2007 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 the 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=1,197) Following Following Ownership Ownership
(n=810) (n=387) (n=778) N=419)
Market Cap (mil) 1,825 2,410 1,163*** 2,778 792***
Total Assets (mil) 1,759 1,928 1,464*** 2,565 881***
Sales (mil) 823 959 669*** 1,320 385***
Sales / TA 0.65 0.65 0.61 0.66 0.60
MB 2.28 2.34 2.12*** 2.35 2.17*
Book leverage 0.22 0.23 0.18** 0.23 0.17***
EBIT / TA 0.07 0.07 0.07* 0.08 0.06**
WC / TA 0.19 0.18 0.22* 0.17 0.25***
Relative Merger Size 0.28 0.25 0.33*** 0.25 0.32***
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 (or through the withdrawal date for non-completed mergers).
Percent of advisors represents the percentage of the 1,460 advisor-level observations in which the advisor bank to the acquirer had an analyst following the
acquirer. Percent of total recs by advisor equals the number of advisors covering the firm divided by the total number of analysts following the firm, averaged
across the 1,197 mergers. Average advisor rec equals the average advisor analyst recommendation in the acquirer, where recommendations vary from 1 to 5 with
1 being the most positive. Average non-advisor rec equals the average analyst recommendation in the acquirer, across all non-advisor analysts. Percent of
advisors that own shares represents the percentage of the 1,460 advisor-level observations in which the advisor bank to the acquirer owned shares in the acquirer.
Advisors as a % of total equals the number of advisors owning shares in the firm divided by the total number of institutions owning shares in the firm, averaged
across the 1,197 mergers. Percent of advisors that issue recs and own shares equals the percent of the 1,460 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 Total Average % of
Avg Advisors Advisors Company
% of Recs that non- Advisors
Advisor as % of that Issue Mkt Cap
Advisors are by Advisor that Own
Rec total insts Recs and ($mil)
Advisor Rec Shares
5 qtrs pre- ann’t 48% 11.4 2.07 2.11 54% 0.94% 33% $1,553
4 qtrs pre- ann’t 51% 12.0 2.09 2.11 55% 0.90% 34% $1,663
3 qtrs pre- ann’t 53% 12.1 2.09 2.11 56% 0.90% 36% $1,745
2 qtrs pre- ann’t 55% 11.9 2.05 2.12 56% 0.89% 37% $1,875
1 qtr pre- ann’t 57% 12.0 2.04 2.12 58% 0.89% 39% $2,020
1 qtr post-ann’t 57% 11.4 2.04 2.11 59% 0.93% 39% $2,220
1 qtr post-completion 61% 11.9 1.96 2.07 62% 0.75% 44% $2,633
2 qtrs post-completion 62% 12.3 1.96 2.08 64% 0.78% 46% $2,707
3 qtrs post-completion 63% 12.2 1.99 2.09 63% 0.80% 46% $2,817
4 qtrs post-completion 64% 12.0 2.01 2.13 64% 0.81% 47% $2,798
5 qtrs post-completion 62% 11.7 2.03 2.16 63% 0.79% 47% $2,769
Table 4: Relation between advisors’ recommendations changes and holdings changes
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 (or through the withdrawal date for
non-completed mergers). Panel B focuses on the pre-announcement quarters and Panel C on the post-announcement
quarters. Each panel shows the number of downgrades and two 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 the change in advisor shares held of the acquirer, from quarter t-1
to quarter t. The second measure is the percentage change in advisor shares held, defined as shares owned at the end
of quarter t minus shares owned at the end of quarter t-1, all deflated by shares outstanding at the end of quarter t-1.
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 474 8,755 777
∆ Advisor Shares Held
44,279 84,621 122,323 1.66*
%∆ Advisor Shares Held 0.33% 0.46% 0.67% 1.49
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 199 3,754 389
∆ Advisor Shares Held
79,761 64,709 65,371 0.24
%∆ Advisor Shares Held 0.61% 0.48% 0.46% 0.42
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 275 5,001 388
∆ Advisor Shares Held
18,603 99,567 179,421 2.19**
%∆ Advisor Shares Held 0.13% 0.45% 0.88% 2.31**
Table 5: Determinants of change in acquirer shares held by the advisor investment bank
This table shows firm fixed effects maximum likelihood regressions, where the dependent variable is percent change
in advisor bank ownership in the acquirer, defined as shares owned at the end of quarter t minus shares owned at the
end of quarter t-1, all deflated by shares outstanding at the end of quarter t-1. Regressions are estimated over the
1,460 advisor-level observations, for five quarters prior to the merger announcement to five quarters following the
merger completion (or through the withdrawal date for non-completed mergers). 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), and the second independent variable is the change in
average non-advisor recommendation. In column 2, these recommendation changes are 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 optimistic. 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. Pct held by Advt=-1 equals the percent of outstanding shares held by the acquirer advisor in the acquirer firm
one quarter prior. For stock mergers in the first quarter following merger completion, Qtr t-1 Dum*Shares assumed
in acquirert=+1equals the number of shares held by the advisor in the target firm in the previous quarter; for all other
firm quarters this variable equals 0. Standard errors are clustered by calendar year, and Z-statistics are shown in
Dep’t Var = % change in Advisor Shares Held (in acquirer)
5 qtrs pre-annt through 5 qtrs Pre-ann’t Post-ann’t
post-completion period period
ΔRec (Advisor) 0.16 -0.12 0.35***
(1.36) (-0.46) (2.67)
ΔRec (Non-Advisor) -0.18 -0.27 -0.03
(-0.83) (-0.86) (-0.13)
ΔRec * Pre- Merger (Advisor) -0.13
ΔRec * Post Merger (Advisor) 0.40***
ΔRec * Pre Merger (Non-Adv) -0.31
ΔRec * Post Merger (Non-Adv) -0.06
Strong Buy Dummy (Advisor) 0.16 0.10 0.84* -0.14
(0.64) (0.38) (1.68) (-0.43)
Buy Dummy (Advisor) -0.14 -0.19 -0.07 -0.28
(-0.92) (-1.25) (-0.34) (-0.95)
Hold Dummy (Advisor) -0.11 -0.15 0.13 -0.47
(-0.46) (-0.61) (0.41) (-1.41)
ΔMkt Cap 15.05*** 15.11*** 12.19 7.61*
(2.62) (2.60) (0.79) (1.70)
Pct held by Advt-1 -132.7*** -132.9*** -145.8*** -193.8***
(-7.44) (-7.49) (-8.76) (-6.02)
Qtr t-1 Dum*Shares assumed 0.61*** 0.61*** 0.70***
in acquirert=+1 (2.81) (2.81) (3.05)
N Obs 9,126 9,126 3,764 5,253
Table 6: Determinants of change in acquirer shares held by the advisor investment bank,
Upgrades vs Downgrades
This table shows firm fixed effects maximum likelihood regressions, where the dependent variable is percent change
in advisor bank ownership in the acquirer, defined as shares owned at the end of quarter t minus shares owned at the
end of quarter t-1, all deflated by shares outstanding at the end of quarter t-1. Across the 1,460 advisor-level
observations and five quarters prior to merger announcement through five quarters post-merger completion sample
(or through the withdrawal date for non-completed mergers), column 1 includes firm quarters with an analyst
upgrade or no recommendation change (excluding cases where the previously outstanding advisor recommendation
was a strong guy) and column 2 includes firm quarters with an analyst downgrade or no recommendation change.
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), and the second
independent variable is the change in average non-advisor recommendation. In column 2, these recommendation
changes are 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
optimistic. 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. Pct held by Advt=-1 equals the percent of outstanding shares held by the
acquirer advisor in the acquirer firm one quarter prior. For stock mergers in the first quarter following merger
completion, Qtr t-1 Dum*Shares assumed in acquirert=+1equals the number of shares held by the advisor in the target
firm in the previous quarter; for all other firm quarters this variable equals 0. Standard errors are clustered by
calendar year, and Z-statistics are shown in parentheses.
Dep’t Var = % change in Advisor
Shares Held (in acquirer)
ΔRec * Pre- Merger (Advisor) -0.24 -0.09
ΔRec * Post Merger (Advisor) 0.18 0.56**
ΔRec (Non-Adv) -0.28 -0.30
Strong Buy Dummy (Advisor) 0.31
Buy Dummy (Advisor) -0.21 -0.08
Hold Dummy (Advisor) -0.15 -0.08
ΔMkt Cap 26.26* 17.91**
Pct held by Advt-1 -166.50*** -137.34***
Qtr t-1 Dum*Shares assumed 0.88 0.44***
in acquirert=+1 (1.35) (2.55)
N Obs 6,069 8,429
Table 7: Abnormal Returns to Analyst Recommendation Changes
This table shows the three day abnormal return to analyst recommendation changes. Abnormal returns are
computed as the cumulative return to the stock around days -1 to 1, net of the cumulative return to the value-
weighted index around the same days, where day 0 is the day of the recommendation change. The pre-
announcement period consists of one to five quarters prior to the merger announcement, and the post-announcement
period consists of one quarter following merger announcement through five quarters following merger completion
(or through the withdrawal date for non-completed mergers). T-statistics in Panel A test the difference between the
pre-announcement and post-announcement periods, and in Panel B between recommendation changes by advisor
bank analysts versus non-advisor bank analysts.
Pre-Announcement Post-Announcement T-statistic
All Rec Changes
(absolute value of 4.9% 6.4% 3.19***
2.13% 2.42% 0.54
-3.5% -5.9% -2.48**
Advisor Non-Advisor T-statistic
2.4% 1.3% 2.82***
-5.9% -4.3% 2.06**