When do banks listen to their analysts? Evidence from mergers and acquisitions

David Haushalter

Penn State University E-mail: gdh12@psu.edu Phone: (814) 865-7969

Michelle Lowry•

Penn State University E-mail: mlowry@psu.edu

Phone: (814) 865-1483

March 6, 2009 Abstract: 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 suggestions.

1

1. Introduction

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

2

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

1 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. 2 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.

3

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

4

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

5

these recommendations.

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

6

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

concludes.

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,

3 Ljungqvist, Malloy and Marston (2006) find that the importance of accuracy for career outcomes has become more limited in recent years.

7

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

8

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. Data

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

acquisition.

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,

9

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

10

and downgrades.4

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,

4 We thank Leonardo Madureira for providing the dates on which the banks revised recommendations in an effort to comply with the Global Settlement.

11

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.

12

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

13

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

5 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).

14

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

15

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

16

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

17

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

next section.

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

analysts.

For each advisor investment bank, we download the income statement from the bank’s

18

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

proprietary trading.

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

19

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

quarter.

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

20

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

21

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

recommendations.

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

6 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.

22

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

incentives.

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

23

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

24

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

analysts’ recommendations.

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’

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

25

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

significant.

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.

26

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.

8. Conclusion

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

27

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.

28

References

Aggarwal, R., Prabhala, N., Puri, M., 2002. Institutional allocation in initial public offerings:

empirical evidence. Journal of Finance 57, 1421-1442.

Agrawal, A., Chen, M., 2008. Do analyst conflicts matter? Evidence from stock

recommendations. Forthcoming, Journal of Law and Economics.

Barth, M., Kasznik, R., McNichols, M., 2001. Analyst coverage and intangible assets. Journal

of Accounting Research 39, 1-34.

Becher, D., Juergens, J., 2005. Analyst recommendations and mergers: do analysts matter?

Unpublished working paper, Arizona State University.

Bodnaruk, A., Massa, M., Simonov, A., 2007. Investment banks as insiders and the market for

corporate control. Review of Financial Studies, forthcoming.

Carhart, M., 1997. On persistence in mutual fund performance. Journal of Finance 52, 57-82.

Chan, K., Chang, C., Wang, A., 2005. Put your money where your mouth is: do financial firms

follow their own recommendations? Unpublished working paper, Cornell Unversity.

Chen, X., Cheng, Q., 2002. Institutional holdings and analysts’ stock recommendations.

Unpublished working paper.

Cowen, A., Groysberg, B., Healy, P., 2006. Which types of analyst firms are more optimistic?

Journal of Accounting and Economics 41, 119-146.

DeLong, G., 2001. Stockholder gains from focusing versus diversifying bank mergers. Journal

of Financial Economics 59, 221-252.

Drucker, S., Puri, M., 2005. On the benefits of concurrent lending and underwriting. Journal of

Finance 60, 2763-2799.

Fama, G., French, K., 1993. Common risk factors in the returns on stocks and bonds. Journal of

Financial Economics 33, 3-56.

Gompers, P. and A. Metrick, 2001. Institutional investors and equity prices. Quarterly Journal

of Economics 116, 229-259.

Groysberg, B., Healy, P., Chapman, C., Shanthikumar, D., Gui, Y., 2007. Do buy-side analysts

outperform the sell-side? Working paper.

Hong, H., Kubik, J.D., 2003. Analyzing the analysts: career concerns and biased earnings

forecasts. Journal of Finance 58, 313-351.

Jackson, A.R., 2005. Trade generation, reputation, and sell-side analysts. Journal of Finance 60,

29

673-717.

Kadan, O., Madureira, L., Wang, R., Zach, T., 2008. Conflicts of interest and stock

recommendations: the effects of the global settlement and related regulations. Review of

Financial Studies, forthcoming.

Kolanski, A., Kothari, S.P., 2009. Investment Banking and Analyst Objectivity: Evidence from

Analysts Affiliated with M&A Advisors. Journal of Financial and Quantitative Analysts,

forthcoming.

Leaven, L., Levine, R., 2007. Is there a diversification discount in financial conglomerates?

Journal of Financial Economics 85, 331-367.

Ljungqvist, A., Marston, F., Starks, L, Wei, K., Yan, H., 2007. Conflicts of interest in sell-side

research and the moderating role of institutional investors. Journal of Financial

Economics 85, 420-456

Massa, M., Rehman, Z., 2008. Information lows within financial conflomerates: evidence from

the banks-mutual funds relation. Journal of Financial Economics, forthcoming.

Mehran, H., Stulz, R., 2007. The economics of conflicts of interest in financial institutions.

Journal of Financial Economics 85, 267-296

Michaely, R., Womack, K., 1999. Conflict of interest and the credibility of underwriter analyst

recommendations. Review of Financial Studies 12, 653-686.

Moeller, S., Schlingemann, F., Stulz, R., 2005. Wealth destruction on a massive scale? a study

of acquiring-firm returns in the recent merger wave. Journal of Finance 60, 757-782.

Schenone, C., 2004. The effect of banking relationships on the firm’s IPO underpricing. Journal

of Finance 59, 2903-2958.

30

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

Stock 468

Cash 127

Mixed 319

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

Other 92

31

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).

Whole Sample (n=914)

Advisor Analyst

Following (n=591)

No Advisor Analyst

Following (n=323)

Advisor Institutional Ownership

(n=548)

No Advisor Institutional Ownership

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%***

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. 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

Advisors that Issue Recs and

own Shares

% of Advisors

Avg # Recs per Company

% of Total Recs that

are by Advisor

% of Advisors that Own

Shares

Avg # Insts

invested in co

Advisors as % of

total insts

Company Mkt Cap ($mil)

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

33

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

Adv. Downgrade No Adv. Rec

Change 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

Adv. Downgrade No Adv. Rec

Change 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

Adv. Downgrade No Adv. Rec

Change 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*

34

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.

5 qtrs pre-annt through 5 qtrs post-completion Announcement to 5 qtrs

post-completion Dept Variable Indicator

Variable Indicator Variable ΔAdv Shrs

ΔAdv Shrs ΔAdv Shrs - ΔNon Shrs

ΔRec (Advisor) 0.08**

(2.52) 0.10** (2.28)

0.09** (1.99)

ΔRec (Non-Advisor) -0.01 (-0.19) -0.001

(-0.03) 0.02

(0.38) ΔRec * Pre- Merger (Advisor)

0.07 (1.39)

0.01 (0.19)

ΔRec * Post Merger (Advisor) 0.09**

(2.31) 0.09**

(2.29)

ΔRec * Pre Merger (Non-Adv) 0.01

(0.20) -0.02

(-0.38)

ΔRec * Post Merger (Non-Adv) -0.02

(-0.37) -0.005

(-0.10)

Strong Buy Dummy (Advisor) 0.03 (0.49)

0.03 (0.42)

0.02 (0.31)

0.004 (0.05)

0.005 (0.06)

Buy Dummy (Advisor) 0.02 (0.41)

0.02 (0.35)

0.02 (0.36)

0.009 (0.11)

0.008 (0.10)

Hold Dummy (Advisor) -0.02 (-0.28)

-0.02 (-0.33)

-0.02 (-0.42)

-0.13 (-1.60)

-0.12 (-1.48)

ΔMkt Cap 6.05*** (3.75)

6.03*** (3.73)

7.97*** (5.11)

8.50*** (4.37)

6.56*** (3.42)

Adv Sharest-1 -37.08*** (-11.26)

-46.21*** (-10.70)

-45.25*** (-10.63)

Qtr t-1 Dum*Adv Shares in Targett=-1

215.96*** (6.73)

186.59***

(5.21) 174.01***

(4.93)

N Obs 7085 7085 7028 4587 4580

35

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*** (-49.9)

0.51*** (24.0)

%Rev from IB 2.43*** (9.7)

0.20** (2.7)

%Rev from Trade -1.39*** (-11.2)

-0.13*** (-3.4)

Acquirer Mcap 5.55*** (6.9)

0.52** (2.2)

Rec 1 Dummy -0.54*** (-26.7)

Rec 2 Dummy -0.47*** (-23.8)

Rec 3 Dummy -0.42*** (-20.3)

Shrs Held Advt-1 -6.76 (-1.6)

-1.67** (-1.4)

M&A annt AR 0.27* (1.7)

0.06 (1.3)

Stock dummy 0.06* (1.8)

0.02* (1.9)

Cash dummy -0.16*** (-2.6)

-0.02 (-1.2)

Relative Size 0.09** (2.5)

0.02** (2.2)

N Obs 2597 2597

Adj R-squared 8.1% 22.1%

36

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**

(2.29) 0.14** (2.32) 0.08

(1.30)

ΔAdv Rec * Low Trade 0.04 (0.58) 0.11

(1.11) -0.03 (-0.22)

ΔAdv Rec * High Trade 0.28*** (3.57) 0.31***

(2.86) 0.30** (2.45)

ΔAdv Rec * Low IB 0.13* (1.71) 0.26***

(2.58) -0.02 (-0.12)

ΔAdv Rec * High IB 0.18** (2.35) 0.14

(1.30) 0.26** (2.21)

Adv Strong Buy Dummy 0.004 (0.05)

-0.01 (-0.11)

-0.002 (-0.02)

0.03 (0.36)

0.02 (0.18)

0.03 (0.31)

-0.01 (-0.13)

-0.02 (-0.13)

-0.01 (-0.11)

Adv Buy Dummy 0.01 (0.10)

0.001 (0.02)

0.005 (0.06)

0.03 (0.30)

0.01 (0.13)

0.02 (0.27)

-0.03 (-0.27)

-0.03 (-0.23)

-0.03 (-0.24)

Adv Hold Dummy -0.12 (-1.59)

-0.13 (-1.64)

-0.12 (-1.56)

-0.10 (-1.25)

-0.11 (-1.38)

-0.10 (-1.21)

-0.17 (-1.51)

-0.16 (-1.46)

-0.16 (-1.44)

ΔMkt Cap 8.51*** (4.40)

8.36*** (4.33)

8.49*** (4.40)

7.20*** (3.66)

7.08*** (3.60)

7.19*** (3.66)

8.36*** (4.18)

8.37*** (4.18)

8.38*** (4.18)

Qtr t-1 Dum * Adv Shares heldt-1

-46.21*** (-10.76)

-45.85*** (-10.69)

-46.01*** (-10.72)

-43.84*** (-10.13)

-43.47*** (-10.05)

-43.59*** (-10.07)

-46.22*** (-10.39)

-46.18*** (-10.38)

-46.14*** (-10.37)

Shares in Target 0.19*** (5.24)

0.19*** (5.20)

0.19*** (5.21)

0.21*** (5.81)

0.21*** (5.77)

0.21*** (5.82)

0.17*** (4.57)

0.17*** (4.59)

0.17*** (4.58)

N Obs 4635 4635 4635 4412 4412 4412 4294 4294 4294

37

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**

(1.96) 0.12** (1.99) 0.07

(1.15)

ΔAdv Rec * Low Trade 0.03 (0.38) 0.08

(0.85) -0.03 (-0.24)

ΔAdv Rec * High Trade 0.25*** (3.20) 0.26**

(2.45) 0.28** (2.33)

ΔAdv Rec * Low IB 0.11 (1.45) 0.23**

(2.26) -0.02 (-0.15)

ΔAdv Rec * High IB 0.15** (2.04) 0.10

(0.94) 0.24** (2.10)

Adv Strong Buy Dummy 0.004 (0.06)

-0.006 (-0.08)

-0.0001 (-0.00)

0.03 (0.36)

0.01 (0.17)

0.03 (0.30)

-0.02 (-0.18)

-0.02 (-0.17)

-0.02 (-0.16)

Adv Buy Dummy 0.007 (0.09)

0.001 (0.02)

0.005 (0.06)

0.02 (0.24)

0.01 (0.07)

0.02 (0.20)

-0.04 (-0.32)

-0.03 (-0.28)

-0.03 (-0.29)

Adv Hold Dummy -0.12 (-1.48)

-0.12 (-1.52)

-0.11 (-1.45)

-0.10 (-1.17)

-0.11 (-1.31)

-0.09 (-1.14)

-0.16 (-1.44)

-0.16 (-1.40)

-0.15 (-1.38)

ΔMkt Cap 6.52***

(3.42) 6.39***

(3.35) 6.51***

(3.42) 5.28

(2.73) 5.17***

(2.67) 5.27***

(2.72) 6.51***

(3.30) 6.51***

(3.30) 6.52***

(3.30) Qtr t-1 Dum * Adv Shares heldt-1

-45.24*** (-10.69)

-44.92*** (-10.63)

-45.07*** (-10.66)

-42.97 (-10.08)

-42.65*** (-10.01)

-42.76*** (-10.03)

-45.37*** (-10.34)

-45.34*** (-10.34)

-45.30*** (-10.33)

Shares held in target 0.17*** (4.96)

0.17*** (4.92)

0.17*** (4.93)

0.20 (5.53)

0.19*** (5.49)

0.20*** (5.55)

0.16*** (4.45)

0.16*** (4.46)

0.16*** (4.46)

N Obs 4627 4627 4627 4404 4404 4404 4287 4287 4287

38

Table 9: Returns to acquirers, conditional on changes in shareholdings of the advisor This table shows alphas of acquirers’ monthly returns computed from four factor regressions using Fama French and momentum factors. Returns are computed following the announcement of a merger if there is both a change in the advisor’s analyst recommendation and in the advisor’s holdings of the acquirer. Returns are sorted by the change in the advisors shareholdings in the quarter of the change in analyst recommendation. Panel A shows results in which acquires are sorted on whether the advisor bought or sold the stock. Panel B requires that a change in the advisor’s stock holdings be in the top or bottom tercile of the sample. T-stats are shown in parentheses.

Panel A: Alphas following increases versus decreases in holdings

Increase Decrease Increase – Decrease

3 months 0.53 (1.33 )

-0.87 (-1.48 )

1.41* (1.86)

12 months 0.06 ( 0.31)

-0.42 ( -1.49)

0.48 (1.40)

36 months -0.08 ( -0.73)

-0.33* (-1.92)

0.25 (1.30)

Panel B: Alphas following change in holdings in top versus bottom tercile

Highest tercile Lowest tercile Highest - Lowest

3 months 1.10** (2.09)

-0.15 (-0.27 )

1.26 (1.51)

12 months 0.06 (0.26)

-0.60** (-2.29)

0.66* (1.93)

24 months 0.04 (0.32)

-0.31* (-1.75)

0.26* (1.69)