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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) 863-6372

April 12, 2010

Forthcoming, Review of Financial Studies

• Corresponding author: Michelle Lowry, 313 Business Building, University Park, PA 16802, 814-863-6372. We thank Lubomir Petrasek for excellent research assistance. We thank Richard Bundro, Laura Field, Peter Iliev, Sandy Klasa, Urs Peyer and seminar participants at Case Western Reserve University, Hong Kong University of Science and Technology, INSEAD, McGill University, National University of Singapore, Singapore Management University, the University of Colorado, the University of Dauphine, and the University of Lausanne for helpful comments and suggestions.

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When do banks listen to their analysts?

Evidence from mergers and acquisitions

April 12, 2010 Abstract: We examine the conflicts of interest and the flow of information between divisions of financial institutions. Using data on analyst recommendations and stockholdings of investment banks advising acquirers in mergers, we find evidence that information from investment banking flows to other divisions of the bank. Specifically, following a merger announcement, changes in a bank’s stockholdings of the acquirer are positively associated with changes in recommendations by its analyst. This relation, however, does not exist before the merger announcement. Additional tests show that the relation between stockholdings and recommendations following a merger announcement is strongest when conflicts of interest for analysts are likely smallest.

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Financial institutions engage in a broad range of activities. Investment banks, for example,

commonly act as underwriters, lenders, asset managers, and providers of investment

recommendations. By offering multiple services, information generated from one division can

be transferred to another in ways not possible when divisions stand alone. Along these lines,

Sufi (2004) and Suarte-Silva (2009) show how information gained from a bank’s lending

activities can benefit other divisions, for example by reducing costs of underwriting debt,

enabling better certification of equity issues, and increasing the probability of becoming a lead

underwriter.1

However, combining divisions can also be detrimental to the divisions of a bank. Of

primary concern are the conflicts of interest that can arise between divisions. For example, a

bank’s sell-side analysts can face pressures to provide overly optimistic recommendations to

support the activities of the investment banking division. Likewise, a bank's asset managers can

face pressures to make investment decisions to support investment banking, leading managers to

purchase shares of client companies for affiliated mutual funds.

What is unclear for banks is when and to what extent conflicts of interest and information

sharing arise. Indeed, in an extensive review of the literature, Mehran and Stulz (2007) describe

the empirical evidence on conflicts of interest for analysts of investment banks as inconclusive.

As they discuss, although the potential for conflicts of interest often exists, there are also

important factors that can mitigate these conflicts. For example, pressures for a bank’s analyst to

inflate recommendations can be offset by the reputational capital that the analyst has at stake.

Similar arguments can be made for information sharing. Although combining divisions can

create the potential for information to be shared across divisions, regulatory issues and conflicts

of interest can mitigate or even eliminate such transfers. As a result, the extent of information

sharing between divisions is also not obvious.

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The objective of this paper is to shed light on these issues by examining the activities of

the divisions of investment banks that are advising acquirer companies in mergers. We use this

setting to examine questions regarding whether information generated from a bank’s investment

banking division helps its analysts and asset managers, whether investment banking leads to

conflicts of interest for analysts and asset managers, and how conflicts of interest potentially

affect information flow between divisions.

Although conflicts of interest and information sharing within a bank can be ongoing, both

can be particularly large – and easier to measure empirically – when the bank is advising an

acquirer in a merger. For one, mergers are a large source of revenues for investment banks.2

Consequently, mergers can result in increased conflicts of interest between a bank’s investment

banking and other divisions. 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, around the time of a merger, the information flow

between divisions of the bank advising the acquirer can be especially valuable.

Our analysis focuses on the activities of an investment bank’s analysts and asset

management divisions around the time the bank is advising an acquirer in a merger. We begin

by examining changes in investment recommendations by a bank’s analysts for the acquirer. We

examine these recommendation changes both before and after a merger announcement. Of

primary interest is whether changes in the bank’s holdings of the acquirer’s shares are associated

with changes in the bank’s analyst recommendations: does the asset management division assess

the analyst recommendations to contain valuable information, and does this assessment vary

around the time that the acquiring firm announces and completes the merger?

Because conflicts of interest can affect just one division (e.g., analysts or asset

management) or multiple divisions (e.g., analysts and asset management), there are several

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possibilities for the relation between the bank’s recommendations and stockholdings. One

possibility is that around the time of a merger, the asset managers of the advising bank do not

change holdings of the acquirer when analysts change their recommendations for the acquirer.

This would suggest that asset management views the analyst recommendations as being

uninformative. Asset managers might perceive Chinese Walls as being strict and analysts as

therefore having no incremental information about the acquirer, or they might view an analyst

upgrade as reflecting pressures for the analyst to support a merger rather than containing new

positive information.

Alternatively, the combined effects of information sharing and conflicts of interest may

produce a positive relation between changes in recommendations and stockholdings for the

advising bank. There are two potential explanations for such a finding. First, analyst

recommendations might be more informative at this time, potentially due to information gleaned

from the investment banking division. Second, analyst recommendations might be less

informative due to conflicts of interest, but asset managers might face similar conflicts of interest

and therefore behave similarly. That is, investment banking may pressure analysts to upgrade

the acquirer company stock and pressure asset management to buy the acquirer company stock,

for example through affiliated mutual funds and/or client accounts.

Using a sample of 1,197 mergers between 1995 and 2007, we find that following the

announcement of a merger, when the advising bank analysts change their recommendations of

the acquirer, these banks correspondingly change their stockholdings of that acquirer. In

contrast, there is no association between changes in analyst recommendations and changes in

stockholdings of the acquirer prior to the merger. We conduct additional analysis to disentangle

whether the increase in the correlation between activities of analysts and asset managers

following the merger indicates an increase in information flow across divisions or an increase in

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conflicts of interest between divisions.

Results from additional tests suggest that the increased relation between

recommendations and shareholdings primarily reflects an increase in information flow between

divisions of the bank. In particular, changes in advising bank analyst recommendations are more

likely to lead those of non-advising banks following a merger announcement than prior to the

announcement. In addition, the increase in the association between an advising bank’s analyst

recommendations and shareholdings is most pronounced for higher quality analysts who would

be expected to provide a more reliable signal of new information.

The results also show that the extent of the increase in the relation between

recommendations and shareholdings varies with the conflicts of interest analysts face. There is

little evidence, however, of similar conflicts within the asset management division. Specifically,

advising banks do not increase shareholdings of the acquirer following upgrades by their

analysts. Rather, the relation between the advising bank’s investment decisions and analyst

recommendation changes is concentrated around analyst downgrades. To the extent that

upgrades are more likely driven by conflicts of interest, the finding suggests that asset managers

follow recommendations of their analysts when the recommendations are least likely to reflect

conflicts of interest. We reach similar conclusions when we follow Agrawal and Chen (2008)

and classify banks according to percent of revenues from investment banking. The relation

between recommendations and shareholdings is only for banks that are less dependent on

investment banking and conflicts of interest are likely smallest.

Our findings support the hypothesis that investment banking produces information that is

shared across divisions of a bank, but that conflicts of interest among analysts affect the

dissemination of this information. Thus, the results highlight the benefits and problems that can

arise when divisions are combined. The findings indicate that to understand the importance of

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information sharing and conflicts of interest, they need to be considered together.

Our paper proceeds as follows. Section 1 outlines the data and sample characteristics.

Section 2 empirically examines the relation between changes in the advising bank analyst

recommendations of the acquirer and changes in the bank’s holdings of the acquirer’s shares.

Section 3 investigates the extent to which this relation reflects information sharing or conflicts of

interest. Section 4 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 5 examines whether non-advising

banks follow the recommendations of the advising bank’s analysts. Finally, Section 6 discusses

several robustness checks, and Section 7 concludes.

1. Data

1.1 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

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

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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 advising bank in at least 10

deals over our sample period. Banks not matched include those, such as Houlihan, Lokey,

Howard & Zukin and Greenhill & Co, LLC, that do not have either an asset management

division or analysts. Mergers in which the advising bank either did not have an advisory arm

(i.e., wasn’t listed in IBES), didn’t have an asset management division (i.e., wasn’t listed in

Spectrum), or served as an advising bank 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.3 We calculate total shares held by each

advising bank institution and each non-advising bank 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.4 We identify the advising bank recommendation

outstanding three days prior to each institutional trading date, and we aggregate all non-advising

bank recommendations outstanding as of this same date into a non-advising bank average

consensus recommendation. To remove confounding interests, we do not include advising banks

to the target firms in this non-advising bank consensus measure. 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 analysts revised their

recommendations downward in the wake of the Global Settlement, to comply with regulations

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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.5

1.2 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

advising bank. Due to our focus on conflicts of interest at the investment bank level, many of

our analyses use advising bank-level recommendations and stock ownership. Our sample

includes 1,413 advising bank-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 and sub-samples. The sample is

divided by whether the advising bank has an analyst covering the acquirer and by whether the

advising bank owns shares in the acquirer, both measured one quarter prior to the merger

announcement. Several differences become apparent. The acquirers that are covered by the

advising bank’s analyst and owned by the advising bank are larger than other acquirers. This

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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 that are covered by the advising bank’s analyst and owned by

the advising bank also 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 advising banks provide analyst coverage and

own shares. This difference in relative merger size is potentially driven by differences in firm

size – companies in which the advising 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

announcement.

Table 3 shows an increase in both the advising bank’s analyst coverage of the acquirer

and in the advising bank’s stockholdings of the acquirer in the period leading up to merger.

These increases are, however, comparable to those of other non-advising banks.6 For example,

Panel A shows that the percent of advising banks with analyst coverage increases from 48% five

quarters prior to the merger announcement to 57% one quarter before the merger announcement.

Although this increase is monotonic across quarters, we observe no systematic pattern in

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advising bank analysts as a percentage of all analysts covering the acquirer, which varies

between 11.4% and 12.0%. This increase suggests that other analysts are also picking up

coverage of the acquirer during this time.

Columns (3) and (4) show that advising bank analyst recommendations are consistently

more optimistic than non-advising bank recommendations, where analyst recommendations are

measured on a scale from one to five, with one being the most optimistic. The average

recommendation among advising banks changes from 2.07 five quarters prior to the merger

announcement to 2.04 one quarter before the merger announcement. By comparison, the average

recommendation level among non-advising banks during this time remains around 2.11. In the

quarters immediately following merger completion, average recommendations by the advising

banks become increasingly positive (average = 1.96 one quarter post-completion). However, in

subsequent quarters, advising banks’ recommendations drift back (average = 2.03 five quarters

post-completion). This trend in recommendations by analysts from the advising banks might

reflect the tendency of acquirers to select advisors that are most positive about the prospects of a

merger. Alternatively, the increasingly optimistic recommendations by the advising banks

around the merger potentially reflect pressures among analysts to win business for its investment

banking division, pressures that are eased once the bank secures the business (i.e., a conflict of

interest).7 We further explore the importance of conflicts of interest below.

As shown in panel B of Table 3, the percent of advising banks owning shares of the

acquirer increases from 54% five quarters prior to the merger announcement to 58% one quarter

before the merger announcement. The increase in the number of advising banks owning shares,

however, is part of a larger trend of increasing institutional ownership in the acquirer. Shares

held by advising banks as a fraction of shares held by all institutional investors decreases

slightly, from 0.94% to 0.89%. In sum, the results provide little evidence of disproportionate

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changes in ownership by the advising bank during this period. Much of the increases in both

advising bank analyst coverage and advising bank share ownership appear to be driven by

increases in the size of the acquirer firm over the quarters prior to the merger announcement.

2. Are changes in advising banks analyst recommendations and stockholdings correlated?

Our main analysis begins by examining the relation between advising bank analyst

recommendations for the acquirer and advising bank stockholdings in the acquirer. We examine

this relation both before and after the merger announcement. As discussed above, a finding of no

relation between changes in recommendations by a bank’s analysts and changes in the bank’s

stockholdings would indicate that the analyst recommendations are not informative either before

or after the merger. The bank’s asset managers, for example, might view upgrades by its

analysts as reflecting pressures for the analyst to support a merger rather than new positive

information, or they may view the analysts as not gaining informational advantages from the

bank’s investment banking division.

There are two potential interpretations of a finding of an increased relation between

changes in recommendations by the bank’s analysts and changes in the bank’s stockholdings

from before to after the merger. One possibility is that analyst recommendations might be more

informative at this time, potentially due to information gleaned from the investment banking

division. A second potential explanation is that analysts’ recommendations are not informative

and reflect conflicts of interest. Asset managers behave similarly only because they face similar

conflicts. Our tests attempt to sort through these possibilities.

2.1 Univariate Analysis of Changes in Recommendations and Stockholdings

Table 4 provides descriptive evidence on the relation between analyst recommendations

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of the acquirer and stockholdings in the acquirer, by the advising bank. The panels in this table

show the average change in stockholdings conditional on an analyst upgrade, downgrade, or zero

change in recommendation. We examine four measures of changes in the advising bank

stockholdings of the acquirer:

(1) Raw changes in shares held

(2) 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

(3) Change in investment in acquirer as a percent of advising bank portfolio,

1

1''%

−

−−=Δt

t

t

t

firmsallholdingsIBAdvMCaprAcqinholdingsIBAdvMCap

firmsallholdingsIBAdvMCaprAcqinholdingsIBAdvMCap

portfolioadvisorof

(4) Change in investment in acquirer as a percent of advising bank portfolio, net of average

change in percent of non-advising bank portfolio,

portfolioadvisornonofportfolioadvisorofNETportfolioadvisorof −Δ−Δ=Δ %%%

The data underlying the analyses represent a panel dataset, with one observation for each

acquirer firm advising bank in each quarter.

Panel A of Table 4 shows results for the entire event period: five quarters pre-

announcement through five quarters post-completion. Although it might not be surprising that

advising banks often upgrade acquirers around a merger, downgrading is also common. During

this period, there were 472 advising bank downgrades of acquirer firms, 773 upgrades, and 8,708

firm quarters with no change in advising 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 472 downgrades, advising banks increased their

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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

advising 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 levels. Finally, advising bank holdings of the

acquirer as a percent of the bank’s total portfolio decrease by 0.016% conditional on a

downgrade, compared to an increase of 0.11% of their total portfolio conditional on an upgrade

(t-stat=2.33, p-value < 0.05).

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 advising bank analysts as downgrades (386

to 198). Results, however, indicate that there is no relation during this pre-announcement period

between changes in these recommendations and changes in advising bank 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 advising banks invest significantly more shares in acquirers that their analyst

upgraded versus those that they downgraded. Moreover, there is a monotonic increase in all

three measures (from downgrade, to no change, to upgrade). For example, percentage change in

shares held equals 0.13% across the 274 downgrades, 0.45% across the 4,976 firm quarters with

no recommendation change, and 0.88% across the 387 upgrade quarters.

There are obviously many factors that may cause an advising bank to change its

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shareholdings in the acquirer firm, for example earnings releases, corporate events such as equity

or debt offerings, voluntary disclosures related to expected future performance, etc. Moreover,

Altinkilic and Hansen (2009) suggest that these factors tend to be correlated with analyst

recommendation changes. For example, a very poor earnings release may prompt the analyst to

downgrade the stock and the asset managers to sell the stock. If such events are more important

in the post-merger announcement period, for example because of greater uncertainty regarding

how the new merged firm will perform, then we might be capturing the effects of these other

events. Notably, such events are likely to cause not only the advising bank to change their

portfolio weightings, but also all other institutions as well. The final row of each panel in Table

4 examines the extent to which changes in advising bank analyst recommendations are

associated with greater portfolio re-allocations by the advising bank, relative to all non-advising

bank institutions. Results using this final measure, change in ‘percent of advising bank portfolio’

net of the average change in ‘percent of non-advising bank portfolio,’ show a pattern similar to

that observed with other measures of advising bank investment. We find a significantly greater

increase in upgrade quarters relative to downgrade quarters, but only in the post-merger

announcement period. These results suggest that advising bank institutions are buying and

selling in response to advising bank analyst recommendation changes rather than in response to

other public information. They also suggest that non-advising bank institutions do not change

their portfolio allocations in response to advising bank analyst recommendations. The reasons

that only the advising banks (but not non-advising bank institutions) choose to respond to

advising bank analyst recommendation changes is investigated further in section 5.

In sum, univariate results provide preliminary evidence of a distinct shift around the time

of a client firm merger announcement in the extent to which financial institutions listen to their

analysts. Financial institutions only invest consistent with their analyst recommendations in the

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period following the merger announcement. The following subsection analyzes this relation in a

multivariate framework, and subsequent sections investigate whether this relation is driven by

common conflicts of interest across both the analyst and asset management divisions or whether

it reflects increased information sharing from the investment banking division that increases the

accuracy of the analyst forecasts.

2.2 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

advising bank analyst recommendation, defined as the advising bank recommendation

outstanding immediately prior to the quarter t holdings date minus the advising bank

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

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interpreted as an upgrade and a negative recommendation change as a downgrade.

Control variables include dummies for the level of the advising bank 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-advising bank analysts and for the

change in market capitalization of the acquirer. We also include lagged percent of shares held by

the advising 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. Following Parrino, Sias,

and Starks (2003), we include the log of acquirer market capitalization, a dummy for whether the

acquirer firm decreased dividends during the quarter, industry adjusted EBIT/TA for quarter t,

and acquirer stock return net of market return over quarter t. Finally, we include an estimate of

the number of acquirer shares that the advising 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.9

Results show that the relation between changes in recommendations and stockholdings

varies around mergers. Column 1 shows a positive coefficient on change in advising bank

recommendation, consistent with advising banks changing their stockholdings in the same

direction as the change in analyst recommendations. However, the coefficient is not significant

at conventional levels. Notably, the results in column 2 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 advising bank analyst recommendation *

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post-merger dummy, is significantly positive (t-statistic = 3.12). In contrast, the interaction term

advising bank analyst recommendation * pre-merger dummy is negative and not significant at

conventional levels (t-statistic = -0.08). 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. As a robustness check we 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 argument, 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.

Table 6 replicates the analysis in Table 5, defining the dependent variable in terms of the

advising bank’s portfolio allocation. Specifically, the dependent variable equals the market

value of the advising bank’s investment in the acquirer as a percent of the advising bank’s total

portfolio in quarter t, minus this percent in quarter t-1. This measure captures the extent to

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which the investment bank re-allocates its investments either toward or away from the acquirer

firm, in response to changes in analyst recommendations. That is, how is the bank changing its

weights in the acquirer, relative to other firms in the bank’s portfolio? Results using this

measure are qualitatively similar. Specifically, in the period following the merger

announcement, an advising bank significantly changes its portfolio weights in the acquirer firm

in the same direction as changes in recommendations by its analysts. However, there is no

evidence of a similar relation in the pre-announcement period.

Results in Tables 5 and 6 show dramatically different patterns across the pre-merger

announcement versus post-merger announcement periods. In the pre-announcement period,

advising banks’ investment decisions are completely unrelated to the advice being provided to

clients, suggesting the banks themselves do not view the changes in recommendations by their

analysts to contain important new information. However, following the merger announcement,

advising banks’ investment decisions are positively related to the advice being provided to

clients. An interpretation of this relation is that analysts have higher quality information in this

post-announcement period, possibly as a result of information sharing from the investment

banking division. An alternative is that pressure from the investment banking division causes

both analysts to upgrade the acquirer stocks and asset management to purchase acquirer shares

(either on its own account or through its mutual funds / client accounts). The distinction between

these explanations 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 focuses on this distinction.

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3. Information Sharing versus Conflicts of Interest

3.1 Analyst upgrades versus downgrades

As a first step toward understanding the source of the stronger relation between analyst

recommendation changes and advising bank stockholdings in the post-merger announcement

period, we compare the extent to which asset management divisions (of the advising 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.

The regressions in Table 7 are 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 advising

bank shareholdings in the acquirer, as defined earlier. Independent variables include the change

in advising bank recommendation in the pre-announcement period, the change in advising 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.

21

In column 1, we find no relation between analyst upgrades and changes in advising bank

holdings. In contrast, column 2 shows a significant relation between downgrades and changes in

advising bank holdings of the acquirer. When the advising bank analyst downgrades the

acquirer, the advising bank is significantly likely to sell more shares. The coefficient of 0.51

indicates that a downgrade in analyst recommendations is associated with decrease in the

advising banks’ holdings that is roughly a half percentage point greater than when there is no

change in the analyst recommendations. Results (not tabulated) are qualitatively similar when the

dependent variable is defined as the change in the advising bank’s investment in the acquirer as a

percent of the advising bank’s total portfolio.

The finding that changes in the advising bank’s shareholdings are only related to analyst

downgrades provides preliminary evidence against the idea that the relation between analyst

recommendations and asset management investments following the merger announcement

reflects pressure (from the investment banking division) on both divisions 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 to be affected by conflicts of

interest.

3.2 Abnormal returns to analyst recommendations

If information sharing across divisions increases the accuracy of the advising bank’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 advising 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 8 shows the abnormal return around analyst recommendation changes

22

in the pre-announcement and post-announcement periods, where abnormal returns are defined as

the cumulative firm return over days -1 through 0, net of the value-weighted market return over

this same period.10 Day 0 represents the day of the recommendation change. Row 1 shows the

absolute value of the abnormal return across all advising bank analyst recommendation changes,

column 2 shows the abnormal return across upgrades, and row 3 across 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 -3.3% in the pre-announcement period versus

-6.0% in the post-announcement period, a difference that is significant at the 1% level (t-statistic

= -2.91). The market infers more information from the downgrades in the post-announcement

period.

If advising bank analysts have more value-relevant information in the post-announcement

period, then they may be more likely to issue recommendations prior to other analysts in this

period. Panel B examines the ordering of analyst recommendations in the quarters preceding

versus following the merger announcement. With respect to upgrades, we observe small

differences in the ordering of recommendations. In the pre-announcement period, 20% of

advising bank upgrades are followed within 14 days by a non-advising bank upgrade. This

increases to 24% in the post-announcement period. In contrast, the pattern of advising bank

analyst downgrades differs much more substantially. Only 11% of advising bank downgrades

are followed by non-advising bank downgrades in the pre-announcement period, compared to

26% in the post-announcement period. The increased tendency of advising bank analysts to lead

other analysts in the post-announcement period is consistent with these analysts having more

information during this period.

23

Panel C examines the effects of recommendation order and analyst affiliation (advising

bank versus non-advising bank) jointly. We regress the abnormal return around recommendation

changes on a dummy equal to one if another analyst issued a similar recommendation change in

the past 14 days, a dummy indicating if another analyst issued a similar recommendation change

on the same day, a dummy indicating if the recommendation change was by the advising bank

analyst during the pre-announcement period, and a dummy indicating if the recommendation

change was by the advising bank analyst during the post-announcement period. Column 1

focuses on abnormal returns around upgrades, and column 2 around downgrades.

Consistent with predictions, upgrades are associated with average positive announcement

returns, and downgrades with average negative returns. When more than one upgrade

(downgrade) is issued on the same day, the return is significantly higher (lower). In contrast,

when a similar recommendation change has been issued by another analyst within the past 14

days, the return is attenuated. Interestingly, the greater market response to advising bank analyst

recommendation changes in the post-announcement period observed in panel A is completely

explained by the effects of recommendation order. Coefficients on advising bank*pre-

announcement and advising bank*post-announcement are approximately equal. Results across

the three panels are consistent with advising bank analysts having more information in the post-

announcement period, and this information enabling them to lead other analysts in their

recommendation changes. Because these analysts are more frequently the first to disseminate

certain information in the post-announcement period, the market tends to react more strongly to

their recommendation changes.

3.3 Analyst quality and sources of banks revenue

Results to this point suggest that information sharing across divisions of financial

24

institutions explains the strong relation between analyst recommendation changes and

investments in the post-merger announcement period, but that in certain cases this relation is

mitigated by conflicts of interest among analysts. Notably, prior literature suggests cross-

sectional variation in both conflicts of interest and analyst quality. This section attempts to

partition banks on whether analysts are more susceptible to conflicts of interest and to partition

analysts on their ability to convert information into value-relevant recommendations. If the

relation between the advising bank’s analyst recommendations and investments is caused by

information sharing, we expect this relation to be strongest among the highest quality analysts

and among the banks where conflicts of interest are lowest.

To examine the extent of conflicts of interest within financial institutions, we classify

financial institutions 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 advising bank on an

acquisition. If pressure from investment banking also extends to asset management divisions, we

would expect the higher conflict of interest banks to be more likely to buy these same stocks.

For each publicly traded advising bank financial institution, 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 financial institutions. However, these 25 banks served as advising banks in the

majority of our acquisitions. Financial institutions are required to disclose 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.

25

To examine analyst quality we follow Loh and Mian (2006) and use the average prior

forecast error of each advising bank analyst in our sample, i.e., the analysts at the advising 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 9 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

financial institutions 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 10 uses these proxies to categorize banks according to the 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 errors are classified as low

(high) quality analysts. For each firm, the sample consists of the first quarter following the

26

merger announcement through five quarters following the merger completion.

Similar to Table 5, Table 10 shows maximum likelihood regressions of the percent

change in advising bank 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 source of revenues data for the advising bank and prior forecasts for

the analyst. Similar to prior findings, we find a significant positive relation between changes in

advising bank analyst recommendations and changes in advising bank shareholdings of the

acquirer firm.

To the extent that information is shared between the investment banking division and the

analysts, we would expect to observe the strongest relation between advising bank

recommendations and investments among high-quality analysts, who are better able to interpret

the extra information and translate it into meaningful recommendations. A comparison of results

across columns 2 and 3 provides only weak support for this prediction. The relation between

analyst recommendation changes and changes in advising bank shareholdings is significant at the

10% level among the high quality analysts (t-statistic = 1.64).11 In comparison, the relation

between analyst recommendation changes and changes in advising bank shareholdings is

significant at the 12% level among the low quality analysts.

In unreported results, we divide the sample into terciles based on analyst quality:

analysts in the highest tercile are considered high quality, those in the lowest tercile as low

quality, and those in the middle tercile are omitted. Based on this categorization, we observe

much more substantial differences. The relation between analyst recommendation changes and

changes in advising bank shareholdings is significant at the 1% level among the high quality

analysts (coef=1.04, t-stat=3.24), but not significant at conventional levels among the low quality

27

analysts (coef=0.58, t-stat=1.04). To the extent that analysts in the middle tercile are most

ambiguously defined as either low or high quality when the sample is divided into just two

groups (as in Table 10), it is not surprising to find stronger results using terciles.12

To examine the conflicts of interest from investment banking, we split the sample into

two groups based on percent of revenues from investment banking. If both the analyst and the

asset management divisions face pressure from the investment banking division to support the

acquirer, we would expect the strongest relation between advising bank recommendations and

investments among high IB banks, where such conflicts are likely greatest.

The results using this split sample are shown in columns 4 and 5 of Table 5. These

results provide no support for the idea of common conflicts of interest for both asset

management and analysts. As shown in column 4, among high IB banks that are most likely to

be subject to such conflicts, we observe no significant relation between analyst recommendation

changes and asset management investment decisions.13 Rather, as shown in column 5, the

relation is concentrated among low IB banks, where such conflicts are likely less severe.14

Conclusions are qualitatively similar if the sample is divided into terciles.

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, and as a result asset managers are more likely to follow the recommendations in this

period. They also, however, indicate that conflicts of interest among analysts affect this relation.

In particular, the relation is stronger for analyst downgrades than upgrades and greater when

investment banking accounts for a small proportion of the advising bank’s revenues. These

findings raise the question of whether other non-advising banks can similarly filter the

recommendations, identifying those that are more likely to contain value-relevant information.

This question is directly examined in Section 5.

28

3.4 Multiple Advising banks

To further examine the variation in conflicts of interest across institutions, we examine

mergers in which there are multiple advising banks. If advising banks have better information

than the rest of the market, they should behave more similarly to each other than to other non-

advising banks. On the other hand, if the incentives for analysts and/or asset management

divisions differ across institutions, advising banks with similar information can behave

differently.

Out of our sample of 1,197 mergers, there are 182 that have more than one advising bank:

159 deals with two advising banks, 15 deals with three advising banks, and 8 deals with four or

more advising banks. Within this multiple advising bank sample, there are 853 firm quarters

where the analysts of at least two advising banks have an outstanding recommendation on the

acquirer. Of these 853 firm quarters, the recommendations of the two advising banks are only

equivalent in 37% of cases (315 firm quarters). Looking at recommendation changes, there are

341 quarters when an advising bank analyst of a multiple-advising bank deal makes a

recommendation change. However, there are only 26 quarters when analysts of both advising

banks make the same recommendation change. These statistics are consistent with variation in

incentives, i.e., in conflicts of interest, across analysts. Analysts’ recommendations are affected

by both information and incentives: even if information is similar across two analysts,

differences in incentives can cause their recommendations to differ.

Earlier results suggest that asset management divisions are not affected by conflicts of

interest. If the asset management divisions of all advising banks (in a merger) face similar

incentives, one would expect them to act similarly. To examine this proposition, we examine

quarters when at least one advising bank (advising bank Y) issued a recommendation change,

29

and we investigate the investment responses of all advising banks (advisors X and Y). We

estimate regressions in which the dependent variable equals the percent change in shares held by

advising bank X. Independent variables on which we focus include the percent change in shares

held by advising bank Y and the percent change in shares held by non-advising banks. If

advising banks behave similarly, we would expect the percent change in shares held by advising

bank X to be significantly related to the percent change in shares held by advising bank Y.

Additional independent variables include the change in recommendation by advising bank Y, the

change in consensus recommendation by non-advising banks, plus other control variables used in

previous regressions.

Results from this analysis are shown in Table 11. The primary finding from the analysis

is that both advising banks to the acquirer make similar investment decisions following a

recommendation change by one of the advising bank analysts. Changes in advising bank X’s

stockholdings are similar to those of advising bank Y, but unrelated to those of non-advising

banks. Moreover, the relation is concentrated in the post-announcement period.15 These

findings provide additional evidence of information transfers within financial institutions, and

they are consistent with asset management divisions of different banks all facing similar

incentives, unaffected by conflicts of interest. To the extent that the asset management divisions

invest the bank’s own money, it is perhaps not surprising that they are less susceptible to

conflicts of interest. Asset management divisions, however, also manage mutual funds and

individual brokerage accounts for outside investors. The results provide no evidence that the

bank attempts to support the shares of investment banking clients using funds they invest for

outside investors.

30

4. Returns to advising banks’ investment decisions following changes in recommendations

Results in Tables 4 through 11 suggest that the advising 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. The banks’ asset management divisions consider

not only the analyst recommendations, but also the information set and incentives behind these

recommendations. As an approximation of the bank’s level of success in this strategy, we

examine abnormal returns to acquirers following changes in the advising bank’s analyst

recommendations. We partition the sample on both the direction of the recommendation change

and the change in the bank’s shareholdings (of the acquirer), thereby obtaining an estimate of the

banks’ returns from listening to their analysts.

We estimate the abnormal returns using 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 an upgrade or a downgrade by their advising bank.

A firm enters the sample one day following the advising bank analyst recommendation change,

and it stays in the sample for three months. In Panel A of Table 12, we consider portfolios of

firms representing (1) a long position in acquirers in which the advising bank increased shares in

the quarter of the recommendation change, (2) a long position in acquirers in which the advising

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 at row 1 of Panel A, we see zero abnormal returns among acquirers that advising

banks upgraded and purchased. However, acquirers that advising banks upgraded and sold

earned significantly negative abnormal returns over the subsequent three months. These findings

are consistent with the bank’s asset management divisions recognizing certain upgrades by its

31

analysts to be more likely caused by conflicts of interest. Following an upgrade, the difference

in abnormal returns between the acquirers that the advising bank increased its holdings and

acquirers that the advising bank decreased its holdings is 3.06 (z-stat=2.94.) In contrast, row 2 of

Panel A shows no evidence of abnormal returns among those cases where the advising bank

either bought or sold following an analyst downgrade.

Given evidence in the earlier tables that downgrades appear more likely to contain value-

relevant information, it is perhaps surprising to find no evidence the asset managers of the

advising bank benefited by listening to their analysts in these cases. To examine returns in more

detail, we separate firms into portfolios based on the magnitude of changes in shareholdings.

Specifically, firms are placed into terciles based on the change in shareholdings of the advising

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 advising bank, (2) a long position in acquirers in the bottom

tercile based on changes in shareholdings by the advising bank, and (3) a long position in

portfolio 1 combined with a short position in portfolio 2.

Results in which changes of holdings are separated into terciles are shown in Panel B.

Results for upgrades are similar to those shown in Panel A. Turning to downgrades, the results

in row 2 of Panel B indicate that banks that increased their stake in the acquirer following a

downgrade by its analyst earned 1.66% per month. Banks that they decreased their stake of the

acquirer following a downgrade avoided a loss of 2.29% per month. A strategy of purchasing

the acquirers the bank bought the most shares in and shorting those where it sold the most shares

would produce significantly positive abnormal returns of 3.89 (z-stat=3.06).

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

32

untabulated tests we examine returns following all advising bank analyst recommendation

changes, and find no evidence of significantly higher returns following advising bank upgrades

versus downgrades. The finding that changes in the advising bank’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. However,

because we focus on changes in recommendations by advising banks around mergers, it is

possible that our recommendation changes are, on average, more likely affected by conflicts of

interest.

In sum, results from the returns analysis provide some evidence that asset managers can

sort the importance of conflicts of interest versus information flow when deciding whether to

trade on analyst recommendations. Looking at returns around upgrades, the greatest benefits to

the bank are observed in those cases when the advising banks choose to decrease – rather than

increase – their holdings, consistent with the bank realizing the effects of conflicts of interest

among analysts. In contrast, consistent with analyst downgrades being less likely driven by

conflicts of interest, the greatest benefits to the bank are observed in those cases when the

advising banks choose to follow the downgrades and decrease their stake, supporting arguments

of information flow within banks.

5. Changes in recommendations by advising banks and stockholdings of non-advisors

We next examine whether the investment decisions by banks not advising the merger are

associated with changes in recommendations by advising bank’s analysts. This analysis is

motivated by our finding that information flow within the advising bank increases the value of

the advising bank’s recommendations, on average, around the time of the client firm merger.

However, prior results also highlight the extent to which conflicts of interest affect certain

33

recommendations. If other (non-advising) banks can identify these conflicts of interest, they will

follow a strategy similar to the advising bank – following that subset of advising bank

recommendations least likely to be biased by conflicts. Under this scenario, changes in

stockholdings by advising banks should be comparable to changes by non-advising banks. If,

however, non-advising banks cannot fully identify these conflicts, changes in stockholdings by

advising banks will differ from those of non-advising banks.

To examine the similarity between the investment decisions of non-advising banks versus

advising banks, we re-estimate the regressions from Tables 5 and 6, using measures of

“abnormal changes” in the advising bank’s holdings of the acquirer. Results are shown in Table

13. In column 1, the abnormal change in advising bank shareholdings equals: percent change in

advising bank shares held net of the average percent change in non-advising bank shares held. In

column 2, the abnormal change in advising bank shareholdings equals: change in the fraction of

advising bank’s total portfolio made up of the acquirer shareholdings minus this change for non-

advising bank’s total portfolios. If other institutions follow a strategy similar to the advising

bank when deciding whether to follow the recommendations of the advising bank’s analyst, the

abnormal changes in the advising bank’s holdings should not be statistically significant in these

regressions.

Notably, the coefficients on the analyst recommendation variables in Table 13 are

comparable to those in Tables 5 and 6. The relation between analyst recommendation changes

and the measures of raw changes in advising bank shareholdings are qualitatively similar to that

between analyst recommendation changes and net changes in advising bank shareholdings.

These findings suggest that, in response to advising bank analyst recommendation changes, the

advising bank changes its positions in the acquirer stock significantly more than other banks.

When combined with the results in Table 12, findings in Table 13 suggest that investment

34

decisions by the advising bank (around recommendation changes by its analysts) are based on

both private and public information, and not replicable by people outside of the bank. In

particular, findings in Table 13 show that the investment decisions by the advising bank differ

from other banks, and Table 12 indicates that these investment decisions are made around

recommendations most likely to contain value-relevant information. Moreover, the higher

returns earned by advising banks (as shown in Table 12) only extend to a three-month horizon.

Therefore, when the advising banks’ holdings are publicly released (six weeks following the end

of the quarter), the opportunity for higher returns no longer exists.

6. Robustness Checks

6.1 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 financial institution. 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 financial

institutions. 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

35

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 extend throughout our sample, we divide our sample into two parts: 1995 – 2000, and

2003 – 2007. Although 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 appear to persist after these regulatory changes.

We note that even in the presence of Chinese walls, people 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

actions.

6.2 Econometric Specifications

The sample underlying many of our regressions represents a panel dataset. As discussed

by Petersen (2008), the appropriate handling of both standard errors and fixed effects in such

samples is paramount. Following Petersen, 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

36

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.

6.3 Advising banks to the Target

Our results suggest that the advising bank analysts obtain inside insight into the value of

the acquirer around the time of the merger. To the extent that the investment banking division of

the target advising bank both obtains and shares value-relevant information with their analysts

and/or asset management divisions, we would expect to see similar relations between analyst

recommendation changes and asset management investments (of the acquirer) within the target

advising bank. Alternatively, the advising bank to the acquirer may learn more about the long-

run acquirer value than the advising bank to the target. For example, in many mergers acquirer

advisers have the opportunity to set up a data room and get proprietary access to target financial

information, thus enabling them to make more accurate long-run projections. However, target

advisers do not require or obtain such reciprocal access to advise the target firm.

To examine whether the analysts working for the target advising bank 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 advising

bank 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

advising bank do not consider their analysts to have abnormally valuable insights into the value

of the acquirer.

37

6.4 Withdrawn Offerings

Out of our sample of 1,413 announced mergers, 154 are withdrawn prior to completion.

Evidence presented throughout the paper suggests that advising bank analysts’ advantage relates

to their information regarding the value of the merger. Following this logic, one might expect

the relevance of their recommendations to decrease when the merger is withdrawn. Among our

sample of 154 withdrawn mergers, there are 39 cases where the advising bank analyst

downgrades the would-be acquirer and 44 cases where the advising bank analyst upgrades,

following the withdrawal date. Although limited sample sizes prevent us from estimating

regressions similar to those in Table 5, we can conduct univariate analyses similar to those in

Table 4. In unreported results, we find no significant difference in the percent of acquirer shares

purchased by the advising bank in the quarter of an upgrade versus those purchased in the quarter

of a downgrade. This finding – although based on a relatively small number of observations – is

consistent with the value of advising bank analysts’ recommendations being more limited

following the withdrawal of the merger.

 

 7. Conclusion

We investigate the importance of conflicts of interest and information sharing within

financial institutions by examining an investment bank’s response to recommendations by its

analysts when advising an acquirer in a merger.

Similar to Ljungqvist, Marston, Starks, Wei, and Yan (2007) and with Fang and Yasuda

(2008), our results indicate the value of analyst advice varies in predictable ways. First,

consistent with information flows from the investment banking division to analysts,

recommendations for an acquirer by an advising bank’s analysts are more value-relevant

38

following a merger than before. Second, consistent with conflicts of interest for analysts,

recommendations are more value-relevant for banks that rely less on investment banking as a

source of revenue and for analyst downgrades of an acquirer rather than upgrades.

We find that banks consider this variation in recommendation quality when making their

investment decisions. Changes in advising bank 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. Returns tests suggest that this is a profitable strategy for the

bank.

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.

39

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1 Literature on information sharing within institutions also documents interactions between analysts and the

investment banking division, and the relation between investment banking and affiliated mutual funds, the quality of

merger advice, and the loan terms between commercial and underwriting banks. For example, see 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).

2 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

http://www.bloomberg.com/news/marketsmag/mm_0408_story1.html and Povel and Singh (2009).

3 Spectrum holdings include holdings of at least 10,000 shares or $200,000, by institutions with at least $100 million

under management. Filings include cases where institutions invest in for their own account as well as cases where

institutions exercise investment discretion over the account of another person or entity.

4 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.

5 We thank Leonardo Madureira for providing the dates on which the banks revised recommendations in an effort to

comply with the Global Settlement.

6 As noted previously, non-advisors exclude advisors to both the acquirer and the target firms.

7 We thank the referee for suggesting this alternative interpretation.

8 Across the entire sample of firm quarters, both raw changes and percent changes in advising bank shareholdings

are positive because an increasing number of advising 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).

9 In addition to the specification shown here, we have also estimated regressions including an additional independent

variable that accounts for the relative weight of the acquirer in the advising banks portfolio in period t-1. This

variable is computed as percent of the advisor’s total holdings in the acquirer stock minus the average percent of

non-advisor firm’s total holdings in the acquirer. This variable is significantly negative in regressions. However,

44

inferences for other variables are unaffected, indicating that our main results are not driven by the advisor being

previously underweighted in the acquirer stock.

10 Results in panel A are robust to defining abnormal returns over the (-1,1) interval. We present results using the (-

1,0) interval to mitigate the effects of overlapping returns in the Panel C regressions.

11 If the highest quality analysts are always able to provide more value-relevant recommendations, we would expect

a similar relation between recommendations and investments in the pre-announcement period. Results (untabulated)

provide no support for this conjecture. Even for high-quality analysts, the asset management divisions of the bank

only follow their recommendations in the post-announcement period, when they likely contain more value-relevant

information.

12 While only the coefficient (on the change in analyst recommendation) in the high quality analysts sample is

significantly different from zero, the coefficients in the high quality versus low quality samples are not significantly

different from each other.

13 In unreported results, finding suggest that even high quality analysts are compromised in high IB banks: within

the subsample of high quality analysts working at high IB banks, we find no significant relation between analyst

recommendation changes and asset management decisions

14 However, the coefficients (on the change in analyst recommendation) in the high versus low IB bank samples are

not significantly different from each other.

15 Although the coefficient on change in shares held by advisor Y is only significant in column 4, the coefficients in

columns 3 and 4 are not significantly different from each other.

45

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 advising banks is treated as two advisor-level observations; there are 1,413 advising bank observations across the 1,197 mergers. Mergers are classified into industries based on the Fama-French 12 industry groupings.

Relative Size > 5%

Number of advising bank observations 1,413

Number of unique mergers 1,197

Withdrawn 154

Completed 1,043

Stock 555

Cash 196

Mixed 446

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

2007 52

46

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 advising 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 advising 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 advising bank analyst vs. no advising bank analyst statistics are significantly different, and similarly whether the advising bank institutional ownership vs. no advising bank institutional ownership are significantly different (*, **, *** represent the 10, 5, and 1% levels of significance).

Whole Sample (n=1,197)

Advising Bank Analyst

Following (n=810)

No Advising Bank Analyst

Following (n=387)

Advising Bank

Institutional Ownership

(n=778)

No Advising Bank

Institutional Ownership

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***

47

Table 3: Advising bank’s analyst recommendations and share ownership in the acquirer companies This table provides information on analyst recommendations and ownership in the acquirer company by the advising banks (Advisor), 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 1,413 advisor-level observations in which the advising bank to the acquirer had an analyst following the acquirer. Percent of total recs by advising bank 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 advising bank rec equals the average advising bank analyst recommendation in the acquirer, where recommendations vary from 1 to 5 with 1 being the most positive. Average non-advising bank rec equals the average analyst recommendation in the acquirer, across all non-advising bank analysts. Percent of advisors that own shares represents the percentage of the 1,413 advisor-level observations in which the advising bank to the acquirer owned shares in the acquirer. Advisors as a % of total insts 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 1,413 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.

PANEL A PANEL B Issuance of Recommendations Ownership of Shares

% of Advisors with Recs

% of Total Recs that

are by Advisor

Avg Advising bank Rec

Average non-

Advising bank Rec

% of Advisors that Own

Shares

Advisors as % of

total insts

% of Advisors that

Issue Recs and own Shares

Company Mkt Cap ($mil)

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

48

Table 4: Relation between advisors’ recommendations changes and holdings changes Each panel tabulates the number of quarters in which the advising 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 four measures of changes in advising bank ownership of the acquirer firm: (1) the change in advising bank shares held of the acquirer, from quarter t-1 to quarter t; (2) the percentage change in advising bank 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; (3) the change in the percent of advising bank portfolio, defined as the market capitalization of the advising bank’s holdings in the acquirer divided by the market capitalization of the advising bank’s total holdings in quarter t, minus this same fraction in quarter t-1; (4) the change in percent of advising bank portfolio net of average change in percent of non-advising bank portfolio, defined as measure (3) minus the analogous measure averaged across all non-advising bank institutions. T-tests are for differences between downgrades and upgrades. *, **, *** indicate significance at the 10%, 5%, or 1% level. Panel A: Differences in Advising bank positions from 5 qtrs pre-ann’t – 5 qtrs post-completion

Adv. Downgrade No Adv. Rec

Change Adv. Upgrade T-Test

Number Observations 472 8,708 773

∆ Advising bank Shares Held 44,279 84,621 122,323 1.66*

%∆ Advising bank Shares Held 0.33% 0.46% 0.67% 1.49

Chg pct of advising bank portfolio -0.016% 0.006% 0.11% 2.33**

Chg pct of adv. port., net of avg chg pct of non-adv portfolio 0.0002% 0.006% 0.009% 1.50

Panel B: Differences in Advising bank positions from 5 qtrs pre-ann’t through 1 qtr pre-ann’t

Adv. Downgrade No Adv. Rec

Change Adv. Upgrade T-Test

Number Observations 198 3,732 386

∆ Advising bank Shares Held 79,761 64,709 65,371 0.24

%∆ Advising bank Shares Held 0.61% 0.48% 0.46% 0.42

Chg pct of advising bank portfolio 0.002% 0.004% 0.009% 0.59

Chg pct of adv. port., net of avg chg pct of non-adv portfolio 0.002% 0.007% 0.009% 0.06

Panel C: Differences in Advising bank positions from 1 qtr post-annt through 5 qtrs post-completion

Adv. Downgrade No Adv. Rec

Change Adv. Upgrade T-Test

Number Observations 274 4,976 387

∆ Advising bank Shares Held 18,603 99,567 179,421 2.19**

%∆ Advising bank Shares Held 0.13% 0.45% 0.88% 2.31**

Chg pct of advising bank portfolio -0.032% 0.007% 0.013% 2.37**

Chg pct of adv. port., net of avg chg pct of non-adv portfolio -0.002% 0.007% 0.009% 1.76*

49

Table 5: Determinants of change in acquirer shares held by the advising bank

Dep’t Var = % change in Advising bank Shares Held (in acquirer)

5 qtrs pre-annt through 5 qtrs post-completion

Pre-ann’t period

Post-ann’t period

ΔRec (Advisor) 0.19

(1.63) 0.03 (0.15)

0.31**

(2.55) ΔRec (Non-Advisor) -0.11

(-0.43) -0.33 (-1.06)

0.09 (0.42)

ΔRec (Advisor) * Pre- Merger -0.02

(-0.08)

ΔRec (Advisor) * Post Merger 0.38***

(3.12)

ΔRec (Non-Adv) * Pre Merger -0.35

(-0.99)

ΔRec (Non-Adv) * Post Merger 0.10

(0.43)

Strong Buy Dummy (Advisor) 0.23 (0.86)

0.20 (0.69)

0.56

(1.34) -0.19

(-0.55) Buy Dummy (Advisor) -0.05

(-0.38) -0.09

(-0.57) -0.18

(-0.72) -0.30

(-0.93) Hold Dummy (Advisor) -0.01

(-0.05) -0.04

(-0.14) 0.16

(0.39) -0.46

(-1.34) Pct held by Advt-1 -1.37***

(-7.72) -1.37***

(-7.77) -1.48***

(-11.59) -1.90***

(-5.91) Qtr t-1 Dum*Shares assumed in acquirert=+1 0.60***

(2.71) 0.60***

(2.71) 0.68*** (2.94)

Log(Mkt Cap) 0.03 (0.28)

0.03 (0.23)

0.33 (1.18)

0.21 (1.14)

ΔMkt Cap 13.05** (2.11)

13.26** (2.14)

1.51 (0.16)

8.67 (1.52)

Dividend Decrease Dummy 1.07*** (3.94)

1.08*** (3.93)

0.10 (0.32)

1.40** (2.36)

Indus Adj EBIT/TA 1.89 (1.43)

1.99 (1.52)

-1.12 (-0.97)

1.49 (0.93)

Net of Mkt Return 0.25 (1.01)

0.25 (1.03)

-0.29 (-0.77)

-0.02 (-0.09)

N Obs 8,622 8,622 4,055 4,966 This table shows firm fixed effects maximum likelihood regressions, where the dependent variable is percent change in advising 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 1,413 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 advising bank analyst recommendation of the acquirer company (measured over the same quarter

50

but observed prior to the measurement of institutional ownership), and the second independent variable is the change in average non-advising bank recommendation. In column 2, these recommendation changes are interacted with both a pre-merger dummy and a post-merger dummy (equal to 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 advising bank 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 advising bank 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=+1 equals the number of shares held by the advising bank in the target firm in the previous quarter; for all other firm quarters this variable equals 0. The log(mkt cap) and change in mkt cap refer to the market capitalization of the acquirer in quarter t. The dividend decrease dummy equals one in firm quarters where the acquirer decreased the normal dividend, zero otherwise. Industry adjusted EBIT/TA equals acquirer EBIT/TA for quarter t, minus median EBIT/TA across firms in the same Fama-French 48 industry in quarter t. Net of market return equals acquirer market return during quarter t, minus the value-weighted market return in the same quarter. Standard errors are clustered by calendar year, and Z-statistics are shown in parentheses. *, **, *** indicate significance at the 10%, 5%, or 1% level.

51

Table 6: Determinants of change in portfolio weights of the advising bank

This table shows firm fixed effects maximum likelihood regressions, where the dependent variable is the change in percent of advising bank’s portfolio, defined as the market capitalization of the advising bank’s holdings in the acquirer divided by the market capitalization of the advising bank’s total holdings in quarter t, minus this same fraction in quarter t-1. Regressions are estimated over the 1,413 advising bank-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). Percent of portfoliot-1 equals the market capitalization of the advising bank’s holdings in the acquirer divided by the market capitalization of the advising bank’s total holdings in quarter t-1. All other independent variables are defined in Table 5. Standard errors are clustered by calendar year, and Z-statistics are shown in parentheses. *, **, *** indicate significance at the 10%, 5%, or 1% level.

Dep’t Var = change in % (in acquirer) of Advising bank Portfolio

5 qtrs pre-annt through 5 qtrs post-completion

Pre-ann’t period

Post-ann’t period

ΔRec (Advisor) 0.18*** (4.17) 0.06

(0.59) 0.23***

(3.58) ΔRec (Non-Advisor) -0.09

(-0.97) -0.01 (-0.11)

-0.01 (-0.52)

ΔRec (Advisor) * Pre- Merger 0.04

(0.52)

ΔRec (Advisor) * Post Merger 0.29***

(3.96)

ΔRec (Non-Adv) * Pre Merger 0.05

(0.37)

ΔRec (Non-Adv) * Post Merger -0.20

(-1.68)

Strong Buy Dummy (Advisor) 0.35** (2.17)

0.32 (1.89)

0.18 (0.78)

0.11 (0.32)

Buy Dummy (Advisor) 0.13 (0.85)

0.11 (0.64)

0.15 (1.27)

-0.04 (-0.12)

Hold Dummy (Advisor) 0.17 (1.353)

0.15 (1.25)

0.08 (0.53)

0.01 (0.06)

Pct of Adv Portfoliot-1 -4.46*** (-6.64)

-4.46*** (-6.64)

-3.93*** (-2.81)

-5.21*** (-7.05)

Qtr t-1 Dum*Shares assumed in acquirert=+1 0.30***

(3.73) 0.30***

(3.67) 0.22*** (4.27)

Log(Mkt Cap) 0.16 (1.60)

0.15 (1.52)

0.13 (1.07)

0.34*** (2.75)

ΔMkt Cap 29.19*** (2.75)

29.22*** (2.75)

29.88*** (3.39)

34.85*** (2.88)

Dividend Decrease Dummy -0.25*** (-2.42)

-0.26** (-2.38)

-0.14** (-2.52)

-0.43*** (-3.14)

Indus Adj EBIT/TA -11.00 (-1.33)

-1.12 (-1.38)

0.07 (0.20)

-1.80 (-1.38)

Net of Mkt Return 0.23 (1.50)

0.23 (1.48)

0.03 (0.44)

0.17 (1.38)

N Obs 6,499 6,499 3,146 3,664

52

Table 7: Determinants of change in acquirer shares held by the advising bank, Upgrades vs Downgrades

This table shows firm fixed effects maximum likelihood regressions, where the dependent variable is percent change in advising 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 across the 1,413 advising bank-level observations, for five quarters prior to merger announcement through five quarters post-merger completion (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 advising bank recommendation was a strong buy). Column 2 includes firm quarters with an analyst downgrade or no recommendation change. Independent variables are defined in Table 5. Standard errors are clustered by calendar year, and Z-statistics are shown in parentheses. *, **, *** indicate significance at the 10%, 5%, or 1% level.

Dep’t Var = % change in Advising bank Shares Held (in

acquirer) Upgrades Downgrades

ΔRec (Advisor) * Pre- Merger -0.24 (-0.95)

0.19 (0.53)

ΔRec (Advisor) * Post Merger 0.09 (0.44)

0.51** (1.95)

ΔRec (Non-Adv) * Pre Merger -0.47 (-0.89)

-0.53 (-1.33)

ΔRec (Non-Adv) * Post Merger -0.13 (-0.69)

0.05 (0.17)

Strong Buy Dummy (Advisor) 0.41

(1.31) Buy Dummy (Advisor) -0.21

(-1.52) 0.02

(0.08) Hold Dummy (Advisor) -0.11

(-0.44) 0.02

(0.06) Pct held by Advt-1 -1.67***

(-6.45) -1.43***

(-8.13) Qtr t-1 Dum*Shares assumed in acquirert=+1 0.84

(1.25) 0.45**

(2.41)

Log(Mkt Cap) 0.19 (1.54)

0.04 (0.38)

ΔMkt Cap 24.45** (2.52)

15.18** (2.38)

Dividend Decrease Dummy 0.55** (2.09)

1.19*** (3.98)

Indus Adj EBIT/TA -0.16 (-0.74)

2.73* (1.85)

Net of Mkt Return -0.01 (-0.02)

0.30 (1.03)

N Obs 5,719 7,970

53

Table 8: Abnormal Returns to Analyst Recommendation Changes This table shows the abnormal returns to analyst recommendation changes. Abnormal returns are computed as the cumulative return to the stock around days -1 to 0, 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. Panel B shows the number of upgrades and downgrades in the pre-announcement and post-announcement periods, and the number of cases where the advising bank led other analysts, defined as a non-advising bank analyst issuing a similar recommendation within the subsequent 14 days. Panel C shows a regression of CARs (days -1 to 0) at recommendation changes on a dummy equal to 1 if there was a similar recommendation change by another analyst within the past 14 days, a dummy equal to 1 if there was a similar recommendation change by another analyst on the same day, a dummy equal to 1 if the recommendation change was by an analyst at the advising bank prior to the merger announcement, and a dummy equal to 1 if the recommendation change was by an analyst at the advising bank following the merger announcement. The sample in column 1 (2) includes all upgrades (downgrades) by advising bank and non-advising bank analysts of the acquirer from 5 quarters prior to merger announcement through 5 quarters following merger completion. *, **, *** indicate significance at the 10%, 5%, or 1% level. Panel A:

Pre-Announcement Post-Announcement T-statistic

All Rec Changes (abs. value of AR)

4.15% 5.66% 3.83***

Upgrades (abnormal return)

1.73% 2.06% 0.87

Downgrades (abnormal return)

-3.30% -6.00% -2.91***

Panel B:

Upgrades Downgrades

Pre-Announcement Post-Announcement Pre-

Announcement Post-

Announcement

# rec chgs by advisors 383 390 201 275

# (%) where non-advisors followed advisor’s rec change

78 20.4%

101 23.9%

21 10.5%

80 26.2%

54

Panel C

Dep’t Var = CAR at rec change Upgrades Downgrades

Intercept 0.009***

(22.03) -0.015***

(-16.84) Similar rec chg in past 14 days -0.001

(-1.54) 0.008***

(4.62) Similar rec chg on same day 0.021***

(16.67) -0.096***

(-46.16) Advising bank dummy*pre-annt dummy 0.008***

(3.58) -0.017***

(-2.93)

Advising bank dummy*post-annt dummy 0.012***

(5.31) -0.015***

(-2.85)

N Obs 12,101 11,358

55

Table 9: Analyst Recommendations, conditional on conflicts of interest and analyst quality proxies

This table shows an OLS cross-sectional regression of advising bank analyst recommendations on the percent of total bank revenue from investment banking, the average prior forecast error of the analyst, and control variables. Analyst recommendations in each firm are measured at the end of the first quarter following the merger announcement. Recommendations are ordered from 1 to 5, with 5 being the most positive. Control variables include: acquirer market capitalization measured one quarter prior to merger completion, the number of shares held by the advising bank in the acquirer company measured at the end of the previous quarter, abnormal market return to the merger announcement, 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. *, **, *** indicate significance at the 10%, 5%, or 1% level.

Dep’t Var Adv Rec

Constant -2.23***

(-24.11)

%Rev from IB 0.59** (2.35)

Analyst forecast error 0.08 (1.21)

Acquirer Mcap 4.01* (2.65)

Shrs Held Advt-1 1.03 (0.26)

M&A annt AR 0.25 (0.59)

Stock dummy 0.24*** (2.68)

Cash dummy -0.20 (-1.51)

Relative Size -0.03 (-0.37)

N Obs 418

Adj R-squared 5.1%

56

Table 10: Change in advising bank shares of acquirer, conditional on conflicts of interest and analyst quality proxies This table shows firm fixed effects maximum likelihood regressions, where the dependent variable is percent change in advising 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 advisor-level observations that have data on both advising bank source of revenue and prior analyst forecast accuracy, for one quarter following the merger announcement to five quarters following the merger completion (or through the withdrawal date for non-completed mergers). Column 1 includes all advisors with available data, column 2 (3) includes those advising bank analysts with above median (below median) prior forecast accuracy. Column 4 (5) includes advising bank analysts working at banks that receive an above median (below median) percent of revenues from investment banking. The change in the advising bank analyst recommendation of the acquirer company is measured over the same quarter but observed prior to the measurement of institutional ownership. All recommendation changes are multiplied by negative 1, such that increases in recommendations can be interpreted as more optimistic. All other control variables are defined in Table 5. Standard errors are clustered by calendar year, and Z-statistics are shown in parentheses. *, **, *** indicate significance at the 10%, 5%, or 1% level. Dep’t Var = % change in Advising bank Shares Held (in acquirer)

Analysts at All Banks High quality analysts Low quality analysts Analysts at

High IB Banks Analysts at

Low IB Banks ΔRec * (Advisor) 0.67***

(3.34) 0.45*

(1.64) 0.71

(1.57) 0.60

(1.33) 0.78***

(3.61) ΔRec * (Non-Adv) -0.11

(-0.30) -0.05 (0.10)

-0.12 (-0.26)

-0.05 (-0.12)

-0.10 (-0.19)

Strong Buy Dummy (Advisor) 0.74 (1.29)

0.85 (1.09)

0.33 (0.30)

-0.31 (-0.35)

1.83**

(2.19) Buy Dummy (Advisor) 0.82*

(1.72) 0.32

(0.52) 1.11

(1.38) -0.03

(-0.05) 1.89***

(2.61) Hold Dummy (Advisor) 0.33

(0.79) -0.20

(-0.42) 0.53

(0.68) -0.10

(-0.17) 1.03

(1.50) Pct held by Advt-1 -2.55***

(-8.63) -2.55***

(-6.61) -2.86***

(-7.82) -3.17***

(-6.92) -2.34***

(-5.23) Qtr t-1 Dum*Shares assumed in acquirert=+1

1.00*** (3.45)

0.44*** (4.00)

1.39** (2.31)

0.75***

(4.01) 1.38**

(2.01) Log(Mkt Cap) -0.02

(-0.07) -0.49

(-1.15) 0.24

(0.56) 0.26

(0.63) -0.30

(-0.63) ΔMkt Cap 8.67

(1.38) 17.08* (1.92)

3.14 (0.36)

13.59*

(1.85) 0.38

(0.03) Dividend Decrease Dummy 2.54*

(1.74) 2.85*

(1.77) 2.34

(1.07) 2.68***

(3.14) 2.22

(0.65) Indus-Adj EBIT/TA 3.75**

(1.96) 0.04

(0.01) 4.39*

(1.80) 7.21

(1.64) 1.62

(0.70) Net of Mkt Return 0.29

(0.74) 0.84

(1.29) -0.12

(-0.27) -0.22

(-0.59) 0.93

(1.15)

N Obs 2,693 1,336 1,357 1,461 1,232

57

Table 11: Deals with Multiple Advising banks This table shows OLS cross-sectional regressions. The sample consists of firm quarters in which at least one advising bank analyst (advising bank Y) made a recommendation change, among deals with multiple advising banks (referred to as advising bank X and advising bank Y). The dependent variable equals the percent change in shares held by advising bank X in the acquirer. Independent variables include the percent change in shares held by advising bank Y in the acquirer, the average percent change in shares held by non-advising bank institutions in the acquirer, the change in recommendation by the analyst associated with advising bank Y, the change in consensus recommendation by all other analysts, plus other control variables defined in Table 5. *, **, *** indicate significance at the 10%, 5%, or 1% level.

Dep’t Var = % change in Shares Held by Advising bank X, in acquirer

Pre-Ann’t Post-Ann’t Qtrs -5 thru -2 Qtrs -1 thru +5 after completion

Intercept 0.18 (0.48)

-0.58 (-1.39)

0.26 (0.66)

-0.70 (-1.80)

% Δ in shrs held by Adv Y, in acquirer 0.13*

(1.89) 0.21**

(2.52) 0.09

(1.30) 0.27***

(3.27)

%Δ in shrs held by non-advs, in acquirer 0.41

(0.90) -0.65

(-1.07) 0.95

(1.51) -0.38

(-0.87)

ΔRec by Adv Y 0.32 (1.22)

-0.29 (-1.18)

0.60** (2.14)

-0.42* (-1.75)

ΔRec by non-advisors 0.91 (1.06)

0.93 (0.96)

1.08 (1.25)

0.80 (0.80)

Pct held by Adv Xt-1 2.44 (0.12)

-32.51 (1.57)

2.69 (0.10)

-10.64 (-0.62)

Qtr t-1 Dum*Shares assumed in acquirert=+1 6.63***

(4.60) 6.40*** (4.29)

Div Decrease dummy 0.11 (0.07)

2.93 (1.30)

-0.18 (-0.07)

3.26 (2.19)

Indus Adjusted EBIT/TA 11.79 (1.27)

-3.25 (-0.34)

16.16 (1.51)

-2.24 (-0.27)

AR over prior qtr 1.43 (1.19)

3.61***

(2.80) 0.63

(0.47) 3.20***

(2.73) Chg Mcap 134.01***

(3.70) 20.06 (0.87)

147.40*** (3.76)

23.99 (1.01)

Log(Mcap) -0.11 (-0.67)

0.38***

(2.71) -0.26

(-1.44) 0.39***

(2.90)

N Obs 231 177 186 218

58

Table 12: Returns to acquirers, conditional on changes in shareholdings of the advising bank 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 advising bank’s analyst recommendation and in the advising bank’s holdings of the acquirer. Returns are sorted by the change in the advising banks shareholdings in the quarter of the change in analyst recommendation. Panel A shows results in which acquirers are sorted on whether the advising bank bought or sold the stock. Panel B requires that a change in the advising bank’s stockholdings be in the top or bottom tercile of the sample. T-statistics are shown in parentheses. *, **, *** indicate significance at the 10%, 5%, or 1% level.

Panel A: Alphas following upgrades and downgrades: increases versus decreases in holdings, 3-mth horizon

Increase Decrease Increase – Decrease

Upgrades 0.92 (1.55)

-2.13*** (-2.66)

3.06*** (2.94)

Downgrades 0.45

(0.64) -0.30

(-0.25) 0.75

(0.56)

Panel B: Alphas following upgrades and downgrades: Top versus bottom tercile changes in shareholdings, 3-mth horizon

Highest tercile Lowest tercile Highest - Lowest

Upgrades 0.09 (0.08)

-3.99*** (-3.40)

4.09**

(2.60)

Downgrades 1.66*

(1.95) -2.29**

(-2.14) 3.89***

(3.06)

59

Table 13: Determinants of change in acquirer shares held by the advising bank, net of change in shares held by other institutions This table shows firm fixed effects maximum likelihood regressions. In column (1) the dependent variable is percent change in advising bank ownership in the acquirer net of average percent change in non-advising bank ownership in the acquirer. In column (2) the dependent variable is the change in the percent of advising bank portfolio (defined as the market capitalization of the advising bank’s holdings in the acquirer divided by the market capitalization of the advising bank’s total holdings in quarter t, minus this same fraction in quarter t-1) net of the average change in percent of non-advising bank portfolio (defined similarly and averaged across non-advising bank institutions). Regressions are estimated over the 1,413 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). Independent variables are defined in Tables 5 and 6. Standard errors are clustered by calendar year, and Z-statistics are shown in parentheses. *, **, *** indicate significance at the 10%, 5%, or 1% level.

5 qtrs pre-annt through 5 qtrs post-completion

Dep’t Var = % change in Advising bank Shares Held - %

change in non-advising bank shares held

Dep’t Var = chg in % of advising bank portfolio, net of chg in % of

avg non-adv portfolio

ΔRec (Advisor) * Pre- Merger -0.11 (-0.52)

0.01 (0.22)

ΔRec (Advisor) * Post Merger 0.31**

(2.24) 0.26***

(4.22) ΔRec (Non-Adv) * Pre Merger -0.28

(-0.82) 0.06

(0.44) ΔRec (Non-Adv) * Post Merger 0.29

(1.16) -0.16

(-1.31) Strong Buy Dummy (Advisor) 0.29

(1.05) 0.30*

(1.77) Buy Dummy (Advisor) -0.10

(-0.64) 0.10

(0.61) Hold Dummy (Advisor) 0.01

(0.02) 0.14

(1.19) Pct held by Advt-1 -1.35***

(-7.82) -4.43***

(-6.60) Qtr t-1 Dum*Shares assumed in acquirert=+1

0.56*** (2.67)

0.26*** (3.98)

Log(Mkt Cap) 0.07 (0.57)

0.16 (1.55)

ΔMkt Cap 17.77*** (2.87)

3.14 (0.24)

Dividend Decrease Dummy 0.99*** (3.43)

-0.20* (-1.93)

Indus Adjusted EBIT/TA 1.47 (1.01)

-0.59 (-0.66)

Net of Market Return -0.21 (-0.91)

0.02 (0.11)

N Obs 8,611 6,499