Conflicts of Interest within Investment Banks Analysts and Proprietary Traders

Conflicts of Interest within Investment Banks: Analysts and Proprietary Traders David Haushalter Penn State University E-mail: gdh12@psu.edu Phone: (814) 865-7969 Michelle Lowry Penn State University E-mail: mlowry@psu.edu Phone: (814) 865-1483 March 21, 2008 Abstract: We examine the interaction between an investment bank’s trading, analyst recommendations, and advising activities around mergers Banks advising an acquirer provide higher analyst recommendations to acquirers than non-advising banks around the time of the merger On average the trading of an acquirer by the advisor bank following the announcement of an acquisition is in line with the recommendations made by the advisor’s analyst However, additional tests show that this relation only holds for banks that not rely heavily on investment banking as a source of revenue The results are consistent with arguments that the conflicts faced by analysts differ predictably across firms Traders within an investment bank are cognizant of the incentives of the in-house analysts, and knowledge of such incentives significantly affects the extent to which they rely on their recommendations when making trades  We thank Lubomir Petrasek for excellent research assistance Introduction The potential for conflicts of interest is prevalent within investment banks Nearly all large investment banks offer underwriting services, provide analyst coverage, and have proprietary trading desks, and a wide body of evidence suggests that these divisions not act independently In fact, Leaven and Levine’s (2007) finding of a diversification discount for financial conglomerates and DeLong’s (2001) event study analysis of investment bank mergers suggests a valuation penalty for offering too many services under one roof An understanding of these conflicts is important to institutions, to companies buying services from the banks, and also to the banks themselves To study the conflicts between investment banking activities and other aspects of a bank’s operations, we focus on mergers Although conflicts of interest can be ongoing, they are arguably particularly large when a bank is advising a merger First, analysts can be important in both enabling the bank to land a merger deal and in increasing the probability that the deal will be completed (see, e.g., Becher and Juergens, 2005) Mergers are a large source of revenues for investment banks For example, in 2006 alone, the top 20 investment banks earned almost $35 billion in fees from underwriting mergers and acquisitions.1 This is about half of the total fees that they earned from all investment banking activities Second, the insights of analysts into the expected costs and/or synergies of the merger can make their resulting recommendations particularly valuable The value of companies can change dramatically around mergers, and the ability of analysts within the investment banks to forecast these changes can have dramatic See “The Good Times Roll,” Bloomberg Magazine, April, 2007 effects on their personal reputations.2 The first portion of the paper explores the ways in which analysts support the M&A advisory business Specifically, we examine changes in analyst recommendations prior to, around the time of, and following merger announcements and completions We find that analysts of the advisor firm issue significantly more optimistic recommendations around the merger, compared to non-affiliated analysts This finding is consistent with the findings of Michaely and Womack (1999) and Lin and McNichols (1998), among, others, who find that affiliated analysts are more optimistic than non-affiliated analysts around equity offerings Both of these studies conclude that the affiliated analysts are being overly optimistic to support the investment banking business However, the possibility that affiliated analysts truly have a rosier outlook regarding the prospects of the acquirer company cannot entirely be ruled out It would not be surprising if acquiring companies were more likely to choose an advisor that thought well of the merger in question, as opposed to one that had a more negative outlook The second portion of the paper attempts to distinguish between the potential reasons that affiliated analysts are more optimistic than non-affiliated analysts, i.e., to determine if advisor firm analysts are being overly optimistic in an effort to support the investment banking business or if the advisor firm analysts truly have more positive expectations regarding the merger To shed light on this issue, we contrast the actions of the advisor firm analysts with those of the advisor firm traders It seems reasonable to assume that traders within a given institution would have more information regarding the incentives and pressures that analysts within their own bank face, compared to analysts at other banks If the bank’s traders perceive that their firm’s analysts act independently from their investment banking arm, then we would expect that its traders As shown by Moeller, Schlingemann, and Stulz (2005), returns to acquirers around the announcement of mergers at the 5% and 95% level range from -6% to 7% between 1980 to 1997 and -19% to 13% between 1998 and 2001 would buy more shares of upgraded stocks In contrast, if the bank’s traders perceive analysts to upgrade acquirer stocks in an effort to win or support the investment banking business, we expect that its traders would ignore the recommendations of these affiliated analysts Our comparisons focus on the recommendations of and trading in the acquirer firm We find no evidence that the institutional traders of the advisor firm trade in line with their analysts’ recommendations (on the acquirer firm) prior to the merger However this association changes markedly after the merger: there is a significant positive relation between an advisor’s analyst recommendations and its trading following the merger Mergers in which an advising firm’s analyst upgrades the acquirer’s stock are associated with significantly larger increases in share ownership of the acquirer by the advisor bank The finding that traders’ buys and sells are more closely tied to analyst recommendations following the merger is consistent with at least two different scenarios First, advisor firm analysts may provide more accurate recommendations following the merger, perhaps due to better information The in-house traders would be more likely to act on the analyst upgrades or downgrades if they were perceived as higher quality, resulting in a stronger positive relation between recommendations and trades in the quarters following the merger Alternatively, both the analysts and the traders of the advisor bank may face a greater conflict of interest following the merger Suppose both analysts and traders are pressured to support the investment banking business, for example by issuing positive recommendations and by purchasing the stock It is possible that pressure from the investment banking business causes analyst upgrades and inhouse purchases of the stock at the same time, thereby producing a positive relation between the two in the quarters following the merger To distinguish between these alternative explanations, we attempt to classify investment banks into those for which the conflict of interest from investment banking is likely to be more or less severe Specifically, we classify investment banks into those that rely heavily on investment banking revenues versus those for which investment banking is less important If there exists some expectation that the traders and analysts both support the investment banking arm, then this expectation should be greater in those firms for which investment banking is a relatively more important source of revenue That is, we would expect the post-merger relation between analyst recommendations and in-house trading to be strongest in investment banks that rely most heavily on investment banking as a source of revenue Alternatively, if traders perceive the analysts to have more accurate forecasts following the merger (due to more available information), then we would expect this increase in accuracy to be greatest among those banks where the conflict of interest from investment banking is particularly low In this case, we would expect the post-merger relation between analyst recommendations and in-house trading to be strongest in those investment banks that rely least on investment banking as a source of revenue We find that the positive relation between analyst recommendation changes and in-house trading is only significant among those investment banks that rely least on investment banking as a source of revenue, i.e., in those banks where analysts are likely to face the lowest conflicts of interest Within these banks, traders’ actions indicate that they perceive analysts’ post-merger recommendations to be particularly valuable In contrast, in banks where investment banking revenue is an important source of revenue, i.e., where the conflict of interest faced by analysts is likely to be quite high, the traders show no significant tendency to buy and sell in line with analyst recommendations The in-house traders are evidently aware of the conflicts faced by analysts, and as a result they disregard their recommendations We also find that the relation between analyst recommendations and in-house trading varies according to the percentage of investment bank revenue that comes from trading activities Among those banks that rely most heavily on trading as a source of revenue, there is a significantly stronger relation between analyst recommendation changes and in-house trading These findings are consistent with an interpretation that analysts’ objective functions differ in predictable ways across institutions Within investment banks that rely most heavily on trading, analysts are expected to provide the most accurate recommendations, and consequently traders within these institutions are much more likely to act on these recommendations In contrast, within banks that rely most heavily on investment banking as a source of revenue, analysts are expected to support the investment banking business, and consequently the in-house traders pay little heed to their recommendations Our findings contribute to several streams of literature First, our study relates to the debate regarding analyst incentives and the extent to which conflicts of interest cause analysts to issue overly forecasts and recommendations Michaely and Womack (1999), Dugar and Nathan (1995), and Lin and McNichols (1998), among others, find that analysts employed by underwriters of security offerings tend to be more optimistic than other analysts However, Cowen, Groysber, and Healy (2006), Jacob, Rock and Weber (2003), Clarke, Khorana, Patel, and Rau (2004), and Agrawal and Chen (2005) find no evidence that conflicts of interest from investment banking make analysts more optimistic or less precise We take a new approach to this problem, by considering the ways in which analyst incentives are likely to vary both over time and across investment banks Second, although there are a number of papers on analyst actions around equity issues, there is relatively little evidence on analyst actions around mergers and acquisitions M&A activity is a substantial source of revenues for many investment banks, and our study increases our understanding on the ways in which investment banks potentially compete for this business Our paper proceeds as follows Section reviews prior literature on conflicts of interest within investment banking Section outlines the data Section describes analyst recommendations and institutional ownership around the merger Section includes empirical tests on the relation between analyst recommendations and institutional trades, by the advisor investment bank Section investigates how the relation between analyst recommendations and institutional trades varies depending on the likely magnitude of the conflict of interest faced by analysts Finally, Section concludes Related Literature A substantial body of literature has examined the value of analyst recommendations Givoly and Lakonishok (1979), Stickel (1991), Womack (1996), Barber, Lehavy, McNichols and Trueman (2001), Jegadeesh, Kim, Krische, and Lee (2004), Loh and Mian (2005), and Busse and Green (2002) all show that analysts’ earning forecasts and stock recommendations have investment value Consistent with analyst recommendations being value relevant, research by Jackson (2005), Hong and Kubik (2003), and Mikhail, Walther, and Willis (1999) shows that analysts are motivated to increase their reputations by issuing the most informative forecasts and recommendations.3 In the merger framework, Becher and Juergens (2005) find that analysts have insight into the value of a merger, and as a result they can impact the outcome of a merger Although considerable evidence suggests that analyst recommendations have value, there is also a large literature on the conflicts of interest that analysts face Specifically, as discussed Ljungqvist, Malloy and Marston (2006) find that the importance of accuracy for career outcomes has become more limited in recent years in detail by Mehran and Stulz (2007), analysts face pressure from within their firm to issue overly optimistic forecasts and recommendations to support the investment banking business While there is broad consensus that analysts face conflicts of interest, the effects of such conflicts are disputed Lin and McNichols (1998), and James and Karceski (2006), among others, find that analysts employed by underwriters of security offerings tend to be more optimistic than other analysts Findings of Michaely and Womack (1999), Aggarwal, Purnanandam, and Wu (2005), Barber, Lehavy, and Trueman (2007) suggest that this optimism contributes to inflated stock prices The findings of Dugar and Nathan (1995) and McNichols, O’Brien, and Pamukcu (2006) similarly show that affiliated analysts are more optimistic However, they find that the market discounts the affiliated analysts’ recommendations Agrawal and Chen (2005) and Bradley, Jordan and Ritter (2006) reach similar conclusions Finally, papers by Cowen, Groysber, and Healy (2006) and Jacob, Rock and Weber (2003) find no evidence that a conflict of interest from investment banking causes analysts to issue overly optimistic or less precise forecasts Similarly, Agrawal and Chen (2004) find no evidence that accuracy or bias in earnings forecasts are related to the importance of investment banking as a source of revenue to the financial institution.4 Part of the inconsistency in these streams of prior literature is potentially related to the fact that not all analysts face the same conflicts at all times with respect to all stocks Ljungqvist, Marston, Starks, Wei, and Yan attempt to address this issue by separating stocks by the level of institutional ownership Analysts’ career paths are largely influenced by the All-Star rankings, Note that Agrawal and Chen’s (2004) examination of earnings forecasts shows no evidence of a conflict of interest from investment banking resulting in overly optimistic forecasts In contrast, Agrawal and Chen’s (2005) study of analyst recommendations yields the opposite conclusion This difference is consistent with Mehran and Stulz’s observation that more evidence exists suggesting that recommendations are biased and less evidence suggesting that earnings forecasts are biased This potentially reflects the fact that earnings forecasts are more verifiable and potentially have greater effects on an analyst’s reputation which are based on institutional investor feedback Consequently, it follows that an analyst’s incentives to provide unbiased, accurate recommendations are highest in those stocks with the highest institutional ownership Consistent with this conjecture, the authors find that recommendations relative to consensus are positively related to investment banking relationships and negatively related to ownership by institutional investors Although all of the above studies examine analyst conflicts and are therefore obviously related to our research question, there are only a few prior papers that link analyst recommendations with institutional trading, as we Chen and Cheng (2002) find that quarterly institutional trades are correlated with consensus stock recommendations However, they compare all institutional trading with consensus recommendations, rather than matching institutions with their own recommendations, as we The paper potentially most closely related to our own is Chan, Chang, and Wang (2005) Similar to us, they match quarterly trades of financial firms with in-house recommendations However, their specification as well as the focus differs considerably from ours The primary objective of our study is to examine conflicts of interest within investment banking As discussed previously, we believe that quarters around mergers provide an ideal setting to examine such issues In contrast, Chan et al focus more solely on the value relevance of recommendations in a more general setting, and correspondingly they examine all recommendations, not just those around a corporate event Consistent with the analyst recommendations having value, they find that in-house trade is more positive around upgrades than downgrades Differences between their findings and our own are discussed in more detail later Data Our data consists of mergers and acquisitions between 1995 and 2004, 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 analysts, as listed on the IBES recommendation database, and to have institutional ownership, as listed in the Spectrum 13(f) filings, one year prior to the announcement of the acquisition Our analysis necessitates merging the SDC merger data, the IBES recommendation data, and the Spectrum institutional holdings data For each merger, we identify the advisory investment bank from SDC We match by hand the identity of this bank with the IBES broker code and with the Spectrum institutional name In matching the institutions between the SDC, IBES, and Spectrum databases, we are careful to account for both mergers between investment banks and for banks reporting under different names (e.g., Smith Barney Inc and Smith Barney & Co) We attempt to match every investment bank that served as an advisor in at least 10 deals over our sample period The only banks that were not matched were those such as Houlihan, Lokey, Howard & Zukin and Greenhill & Co, LLC, neither of which have either a trading desk or analysts Mergers in which the advisor either did not have an advisory arm (i.e., wasn’t listed in IBES), didn’t have a trading arm (i.e., wasn’t listed in Spectrum), or served as an advisor in less than ten deals are omitted from our sample For our analysis of analyst recommendations, we obtain advisor firm recommendations and consensus recommendations from IBES The summary data are available monthly, on the most informative recommendations, presumably to help the traders, rather than the most optimistic recommendations that might aid the investment banking business Finally, the regression in column shows that inferences on the importance of investment banking revenue and of trading revenue are robust to including interaction terms for both within a single regression Conclusion Conflicts of interest are pervasive within investment banks Prior literature has not reached a consensus on the extent to which such conflicts affect analyst recommendations We take a new approach to this problem, by examining the interaction between analyst recommendations and in-house trading In addition, we broaden the examination of conflicts of interest, by looking at the extent to which such conflicts affect both the analysts and the proprietary traders Because we are interested in conflicts of interest, we choose a setting in which such conflicts are likely to be severe: mergers and acquisitions We find that advisor firm analysts tend to be significantly more optimistic about the acquirer firms than non-advisor analysts Moreover, the advisor-firm trading desk buys and sells on advisor firm analyst recommendations around the time of the merger However, findings suggest that this positive relation is restricted to those settings where the conflict faced by analysts is likely to be less severe In the banks that rely most on investment banking business, traders are significantly less likely to listen to their analysts In contrast, in banks that rely most heavily on trading as a source of revenue, traders rely significantly more on their analysts’ recommendations, suggesting that these analysts’ recommendations are less biased 24 References Aggarwal, R., Purnanandam, A., Wu G., 2005 Underwriter manipulation in initial public offerings Unpublished working paper, University of Minnesota Agrawal, A., Chen, M., 2004 Analyst conflicts and research quality Unpublished working paper, University of Alabama Agrawal, A., Chen, M., 2004 Do analyst conflicts matter? evidence from stock recommendations Forthcoming, Journal of Law and Economics Barber, B., Lehavy, R., McNichols, M., Trueman, B., 2006 Buys, holds, and sells: the distribution of investment banks’ stock ratings and the implications for the profitability of analysts’ recommendations Journal of Accounting and Economics 41, 87-117 Barber, B., Lehavy, R., Trueman, B., 2007 Comparing the stock recommendation performance of investment banks and independent research firms Journal of Financial Economics 85, 490-517 Barth, M., Kasznik, R., McNichols, M., 2001 Analyst coverage and intangible assets Journal of Accounting Research 39, 1-34 Becher, D., Juergens, J., 2005 Analyst recommendations and mergers: analysts matter? Unpublished working paper, Arizona State University Bradley, D., Jordan, B., Ritter, J., 2006 Analyst behavior following IPOs: the ‘bubble period’ evidence Review of Financial Studies, forthcoming Busse, J., Green, T.C., 2002 Market efficiency in real time Journal of Financial Economics 65, 415-437 Carhart, M., 1997 On persistence in mutual fund performance Journal of Finance 52, 57-82 25 Chan, K., Chang, C., Wang, A., 2005 Put your money where your mouth is: financial firms follow their own recommendations? Unpublished working paper, Cornell Unversity Chen, X., Cheng, Q., 2002 Institutional holdings and analysts’ stock recommendations Unpublished working paper Clarke, J., Khorana, A., Patel, A., Rau, R., 2004 The good, the bad and the ugly? Differences in analyst behavior at investment banks, brokerages, and independent research firms Unpublished working paper, Purdue University Cowen, A., Groysberg, B., Healy, P., 2006 Which types of analyst firms are more optimistic? Journal of Accounting and Economics 41, 119-146 DeLong, G., 2001 Stockholder gains from focusing versus diversifying bank mergers Journal of Financial Economics 59, 221-252 Dugar, A., Nathan, S., 1995 The effects of investment banking relationships on financial analysts’ earnings forecasts and investment recommendations Contemporary Accounting Research 12, 131-160 Fama, G., French, K., 1993 Common risk factors in the returns on stocks and bonds Journal of Financial Economics 33, 3-56 Givoly, D., Lakonishok, J., 1979 The information content of financial analysts’ forecasts of earnings: some evidence on semi-strong inefficiency Journal of Accounting and Economics 1, 165-185 Gompers, P and A Metrick, 2001 Institutional investors and equity prices Quarterly Journal of Economics 116, 229-259 26 Hong, H., Kubik, J.D., 2003 Analyzing the analysts: career concerns and biased earnings forecasts Journal of Finance 58, 313-351 Jackson, A.R., 2005 Trade generation, reputation, and sell-side analysts Journal of Finance 60, 673-717 Jacob, J., Rock, S., Weber, D., 2003 Do analysts at independent research firms make better earnings forecasts? Unpublished working paper, University of Colorado, Boulder James, C., Karceski, J., 2006 Strength of analyst coverage following IPOs Journal of Financial Economics 81, 1-34 Jegadeesh, N., Kim, J., Krische, S., Lee, C., 2004 Analyzing the analysts: when recommendations add value? Journal of Finance 59, 1083-1124 Leaven, L., Levine, R., 2007 Is there a diversification discount in financial conglomerates? Journal of Financial Economics 85, 331-367 Lin, H.-W., McNichols, M., 1998 Underwriting relationships, analysts’ earnings forecasts and investment recommendations Journal of Accounting and Economics 25, 101-127 Ljungqvist, A., Marston, F., Starks, L, Wei, K., Yan, H., 2007 Conflicts of interest in sell-side research and the moderating role of institutional investors Journal of Financial Economics 85, 420-456 Loh, R., Mian, G.M., 2005 Do accurate earnings forecasts facilitate superior investment recommendations? Journal of Financial Economics, forthcoming McNichols, M., O’Brien, P., Pamukcu, O., 2006 That ship has sailed: unaffiliated analysts’ recommendation performance for IPO firms Unpublished working paper, Stanford University 27 Mehran, H., Stulz, R., 2007 The economics of conflicts of interest in financial institutions Journal of Financial Economics 85, 267-296 Michaely, R., Womack, K., 1999 Conflict of interest and the credibility of underwriter analyst recommendations Review of Financial Studies 12, 653-686 Mikhail, M., Walther, B., Willis, R., 1999 Does forecast accuracy matter to security analysts? Accounting Review 74, 185-200 Mitchell, M., Stafford, E., 2000 Managerial decisions and long-term stock price performance Journal of Business 73, 287-329 Moeller, S., Schlingemann, F., Stulz, R., 2005 Wealth destruction on a massive scale? a study of acquiring-firm returns in the recent merger wave Journal of Finance 60, 757-782 Ramnath, S., Rock, S., Shane, P., 2006 A review of research related to financial analysts’ forecasts and stock recommendations Unpublished working paper, Georgetown University Stickel, S., 1991 Common stock returns surrounding earnings forecast revisions: more puzzling evidence Accounting Review 66, 402-416 Womack, K., 1996 Do brokerage analysts’ recommendations have investment value? Journal of Finance 51, 137-167 28 Table 1: Descriptive Statistics on M&A Sample The sample consists of 726 mergers over the 1995 to 2004 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 In addition, the target market capitalization must be at least 5% of the combined market capitalization of the target plus acquirer, where all market capitalizations are measured one month prior to the merger announcement A merger with two advisors is treated as two advisor-level observations; there are 816 advisor observations across the 726 mergers Mergers are classified into industries based on the Fama-French 12 industry groupings Relative Size > 5% Number of advisor observations 816 Number of unique mergers 726 Stock 403 Cash 96 Mixed 227 Year # Mergers Industry # Mergers 1995 71 Consumer Nondurables 13 1996 72 Consumer Durables 1997 120 Manufacturing 65 1998 126 Oil, gas, coal extraction 40 1999 85 Chemicals and allied products 14 2000 80 Business Equipment 149 2001 47 Telephone & TV transmission 19 2002 34 Utilities 22 2003 56 Wholesale, Retail 55 2004 35 Healthcare, Med Eqpt, Drugs 60 Finance 221 Other 60 29 Table 2: Descriptive Statistics – 5% sample – Medians Descriptive statistics are provided for the sample of 726 mergers over the 1995 – 2004 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 shortterm and long-term debt divided by the total firm market value, where total firm market value equals total assets plus market value of equity minus the book value of equity Total assets, sales, sales/TA, EBIT/TA, and WC/TA are computed using the relevant Compustat data items Relative merger size equals the target market capitalization divided by the combined market capitalization of the target plus acquirer, where all market capitalizations are measured one month prior to the merger announcement Statistics are computed for the whole sample, conditional on whether or not the advisor bank to the acquirer firm has an analyst issuing recommendations on the acquirer, as listed on IBES, and conditional on whether or not the advisor bank to the acquirer firm owns shares in the acquirer firm, as reported on Spectrum Asterisks denote whether the advisor analyst vs no advisor analyst statistics are significantly different, and similarly whether then advisor institutional ownership vs no advisor institutional ownership are significantly different (*, **, *** represent the 10, 5, and 1% levels of significance) Whole Sample Advisor Analyst Following (n=473) No Advisor Analyst Following (n=253) Advisor Institutional Ownership (n=443) No Advisor Institutional Ownership N=283) Market Cap (mil) 1,855 2,274 1,201*** 3,007 906*** Total Assets (mil) 1905 1974 1806* 2832 1,141*** Sales (mil) 865 1,007 1,329 496*** Sales / TA 0.64 0.67 0.57 0.65 0.64 MB 2.52 2.57 2.36 2.64 2.20*** Book leverage 0.20 0.21 0.18 0.21 0.18 Market leverage 0.13 0.13 0.12 0.13 0.13 EBIT / TA 0.08 0.08 0.07* 0.08 0.07 WC / TA 0.21 0.22 0.21 0.18 0.24** Relative Merger Size 28% 27% 32%** 29% 646*** 27% 30 Table 3: Incidence of advisor recommendations and share ownership in the acquirer companies This table provides information on the incidence of advisor recommendations and advisor institutional ownership in the acquirer company, from five quarters prior to the announcement of the merger to five quarters following the completion of the merger Percent of advisors represents the percentage of the 816 advisor-level observations in which the advisor bank to the acquirer had an analyst following the acquirer Average number of recs per company represents the average number of analysts covering each acquirer firm Percent of total recs by advisor equals the number of advisors covering each firm divided by the total number of recs in each firm, averaged across the 726 mergers Percent of advisors that own shares represents the percentage of the 816 advisor-level observations in which the advisor bank to the acquirer owned shares in the acquirer Average # insts invested in co equals the total number of institutions invested in each acquirer firm, averaged across all mergers Advisors as a % of total equals the number of advisors owning shares in each firm divided by the total number of institutions owning shares in each firm, averaged across the 726 mergers Percent of advisors that issue recs and own shares equals the percent of the 816 advisors to the acquirer firms that both have an analyst following the acquirer and own shares in the acquirer Company mkt cap equals the median market capitalization of the acquirer firm Issuance of Recommendations Ownership of Shares % of Advisors that Issue Recs and own Shares % of Advisors Avg # Recs per Company % of Total Recs that are by Advisor % of Advisors that Own Shares Avg # Insts invested in co Advisors as % of total insts qtrs pre- ann’t qtrs pre- ann’t qtrs pre- ann’t qtrs pre- ann’t qtrs pre- ann’t 52% 57% 60% 64% 68% 10.3 10.5 10.8 11.2 11.4 7.8% 8.3% 8.9% 9.1% 9.4% 58% 59% 59% 61% 62% 173.9 180.1 187.2 195.3 202.6 0.58% 0.55% 0.52% 0.52% 0.48% 27% 34% 37% 39% 43% $1,537 $1,637 $1,747 $1,800 $1,995 qtr post-completion qtrs post-completion qtrs post-completion qtrs post-completion qtrs post-completion 73% 76% 79% 81% 82% 11.5 12.1 12.5 12.7 13.0 10.3% 10.3% 10.2% 9.9% 9.7% 66% 68% 69% 70% 69% 241.9 247.1 250.2 251.3 250.3 0.43% 0.43% 0.45% 0.46% 0.47% 51% 53% 55% 58% 58% $2,495 $2,571 $2,602 $2,592 $2,698 Company Mkt Cap ($mil) 31 Table 4: Changes in the characteristics of advisor recommendations and share ownership in the acquirer companies In Panel A, statistics are computed one month prior to the merger announcement, one month after the merger announcement, and one month following the merger completion For each time period, analyst upgrades and downgrades are relative to the prior month (i.e., for the one month after completion row, upgrades are relative to the month preceding merger completion) An analyst upgrade represents a case where an analyst changed its recommendation on the acquirer company to be more positive (e.g., from a to 1, which represents a buy to a strong buy) In Panel B, statistics are computed one quarter prior to the merger announcement, one quarter after the merger announcement, and one quarter following the merger completion For each time period, the percent of institutions that purchase additional shares or sell shares is measured relative to the previous quarter, similar to Panel A Asterisks represent significant differences between the advisor and non-advisors for each catetgory different (*, **, *** represent the 10, 5, and 1% levels of significance) Statistics in Panel C are similar to those in Panel B, except that non-advisors only include investment banks in our sample (as opposed to all institutions) Panel A: Advisor vs Non-Advisor Analyst recommendations – All Analysts Average Recommendations mth prior to ann’t mth after ann’t mth after completion Advisor Non-Advisor 1.88 1.88 1.85 2.04*** 2.01*** 1.99*** % Analysts with upgrades NonAdvisor Advisor 1.1% 2.3%** 1.7% 5.5%*** 3.9% 2.6% % Analysts with downgrades Advisor Non-Advisor 1.8% 1.4% 2.5% 2.3% 3.9%*** 2.3% Panel B: Advisor vs Non-Advisor Institutional Ownership – All Institutions Average Ownership by: qtr prior to ann’t qtr after ann’t qtr after completion Total Institutional Ownership 59.0% 60.9% 60.5% Advisor 0.47% 0.47% 0.46% NonAdvisor 0.47 0.45 0.37** % Inst’s that purchased additional shares % Inst’s that sold shares Advisor NonAdvisor Advisor NonAdvisor 55% 54% 63% 39%*** 39%*** 66% 41% 42% 37% 38%* 38%* 27%*** 32 Table (cont.) Panel C: Advisor vs Non-Advisor Institutional Ownership – Investment Bank Institutions Only Average Ownership by: qtr prior to ann’t qtr after ann’t qtr after completion Total Institutional Ownership 57.3% 59.1% 59.1% Advisor 0.47% 0.47% 0.46% NonAdvisor 0.43% 0.43% 0.36% % Inst’s that purchased additional shares % Inst’s that sold shares Advisor NonAdvisor Advisor 55% 54% 63% 44%*** 46%*** 67%*** 41% 42% 37% NonAdvisor 42% 42% 29%*** 33 Table 5: Relation between advisors’ recommendations and institutional holdings For Panel A, each quarter, from three quarters prior to the merger announcement to five quarters following the merger completion, we compute the total number of advisor analyst upgrades (i.e., upgrades to the acquirer stock by the investment bank that is advising the acquirer) relative to the end of the previous quarter For each of these upgrades, we compute the percentage of cases in which the advisor firm sold shares in the acquirer stock vs bought shares in the acquirer stock during that same quarter Panel B shows analogous statistics for advisor analyst downgrades Panel A: Changes in Advisors’ institutional holdings when Advisor analysts Upgrade the acquirer Quarter -3 -2 -1 Sell Shares 44% 40% 27% 27% 32% 53% 47% 37% Buy Shares 50% 60% 67% 73% 68% 47% 53% 63% 18 20 15 37 28 17 19 16 N Obs Panel B: Changes in Advisors’ institutional holdings when Advisor analysts Downgrade the acquirer Quarter -3 -2 -1 Sell Shares 47% 31% 18% 38% 65% 50% 67% 46% Buy Shares 47% 63% 76% 62% 23% 40% 28% 46% 15 16 17 29 26 20 40 35 N Obs 34 Table 6: Determinants of change in acquirer shares held by the advisor investment bank This table shows fixed effects regressions, where the dependent variable is the change in shares owned by the advisor investment bank in the acquirer company Regressions are estimated over the 816 advisor-level observations, for five quarters prior to the merger announcement to five quarters following the merger completion, excluding those quarters in between the announcement and completion The first independent variable is the change in the advisor analyst recommendation of the acquirer company (measured over the same quarter but observed prior to the measurement of institutional ownership) This recommendation is interacted with both a pre-merger dummy and a post-merger dummy (equal in in the quarters prior to and following the merger completion, respectively, otherwise) Dummies for the level of the advisor recommendation at the beginning of the quarter are included (strong buy, buy, and hold) The change in market capitalization represents the change in the market capitalization of the acquirer company over the quarter The last column also includes the change in the consensus recommendation of the non-advisor analysts over the quarter and the level of the consensus recommendation among non-advisor analysts at the beginning of the quarter All recommendation variables are multiplied by negative 1, such that higher recommendations and increases in recommendations can be interpreted as more positive recommendations T-statistics are shown in parentheses Model Model Model Rec * Pre- Merger dummy (Advisor) 0.30 (0.78) 0.34 (0.87) Rec * Post Merger dummy (Advisor) 0.75*** (3.07) 0.63** (2.52) Rec (Advisor) 0.57*** (2.75) Rec * Pre Merger dummy (Non-Adv) 1.80** (2.56) Rec * Post Merger dummy (Non-Adv) -0.02 (-0.05) Strong Buy Dummy (Advisor) Buy Dummy (Advisor) Hold Dummy (Advisor) 0.63 (0.68) 0.39 (0.44) 0.04 (0.05) 0.64 (0.70) 0.43 (0.49) 0.11 (0.12) Rec level non-advisor Mkt Cap R-Squared N Obs 0.19 (0.20) 0.10 (0.12) -0.06 (-0.07) 0.92*** (2.61) 0.02* (1.85) 12% 3876 0.02* (1.85) 12% 3876 0.02* (1.72) 13% 3846 35 Table 7: Determinants of change in acquirer shares held by the advisor investment bank, Quarters following the merger completion This table shows fixed effects regressions, where the dependent variable is the change in shares owned by the advisor investment bank in the acquirer company Regressions are estimated over the 816 advisor-level observations, over the first five quarters following the merger completion The first independent variable is the change in the advisor analyst recommendation of the acquirer company (measured over the same quarter but observed prior to the measurement of institutional ownership Dummies for the level of the advisor recommendation at the beginning of the quarter are included (strong buy, buy, and hold) Rec non-advisor equals the change in the consensus recommendation of the non-advisor analysts over the quarter, and Rec level non-advisor equals the level of the consensus recommendation among non-advisor analysts at the beginning of the quarter The change in market capitalization represents the change in the market capitalization of the acquirer company over the quarter, and the level of market capitalization equals the acquirer company market capitalization measured at the beginning of the quarter The stock dummy equals if the merger was paid for with stock, otherwise The cash dummy is measured analogously 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 All recommendation variables are multiplied by negative 1, such that higher recommendations and increases in recommendations can be interpreted as more positive recommendations Tstatistics are shown in parentheses Model Model Model Rec (Advisor) 0.76** (2.48) 0.78** (2.52) 0.59* (1.88) Strong Buy Dummy (Advisor) 0.51 (0.35) 1.19 (0.88) 0.22 (0.17) 0.57 (0.39) 1.23 (0.91) 0.23 (0.18) -0.36 (-0.25) 0.53 (0.39) -0.11 (-0.08) Buy Dummy (Advisor) Hold Dummy (Advisor) Rec non-advisor 0.61 (1.06) Rec level non-advisor 2.64*** (3.94) Mkt Cap 0.02* (1.82) Mkt Cap 0.02* (1.75) -0.02 (-0.93) 2.67 (0.16) 2.45 (0.13) -4.28 (-0.15) Stock dummy Cash dummy Relative merger size R-Squared N Obs 0.03** (2.03) 20% 2112 20% 2112 21% 2100 36 Table 8: Analyst Recommendations, conditional on source of investment bank revenue Average analyst rankings of the acquirer company by the advisor investment bank are compared across categories of investment banks Low (high) IB banks represents those banks whose investment banking revenues as a percent of total revenues fall below (above) the median (when ranked across all investment banks in that year) Average rankings are reported over the entire event period (five quarters prior to the merger announcement through five quarters after the merger completion), the pre-merger period (the five quarters prior to the merger announcement), and the post-merger period (the five quarters following the merger completion) The last column reports the difference in recommendation level, between low IB banks and high IB banks Asterisks report the significance of the difference (*, **, *** represent the 10, 5, and 1% levels of significance) Low IB Banks High IB Banks Difference All Quarters 2.00 1.87 0.12*** Pre-Merger 1.96 1.90 0.06 Post-Merger 2.04 1.86 0.17*** 37 Table 9: Determinants of change in acquirer shares held by the advisor investment bank, Conditional on sources of advisor investment bank revenue This table shows fixed effects regressions, where the dependent variable is the change in shares owned by the advisor investment bank in the acquirer company Regressions are estimated over the 816 advisor-level observations for which we are able to obtain sources of revenue data for the advisor investment bank, over the first five quarters following the merger completion The first independent variable is the change in the advisor analyst recommendation of the acquirer company (measured over the same quarter but observed prior to the measurement of institutional ownership) The recommendation change is interacted with a high IB dummy, equal to one if the advisor bank’s investment banking revenues as a fraction of total revenues fell above the median (when ranked across all investment banks in that year) for the year of the merger, and zero otherwise The recommendation change is also interacted with a high Trade dummy, equal to one if the advisor bank’s trading revenues as a fraction of total revenues fell above the median (when ranked across all investment banks in that year) for the year of the merger, and zero otherwise Similarly, recommendation changes are also interacted with low IB dummies and low trade dummies Dummies for the level of the advisor recommendation at the beginning of the quarter are included (strong buy, buy, and hold) The change in market capitalization represents the change in the market capitalization of the acquirer company over the quarter T-statistics are shown in parentheses Model Rec (Advisor) Model Model 0.55* (1.90) Model -0.87* (-1.67) Rec * Low IB (Advisor) 0.94** (2.50) Rec * High IB (Advisor) 0.14 (0.37) 1.58*** (2.82) Rec * Low Trade (Advisor) 0.24 (0.69) Rec * High Trade (Advisor) 1.06** (2.49) 1.63*** (2.81) Strong Buy Dummy (Advisor) 0.01 (0.01) -0.01 (-0.01) -0.08 (-0.06) -0.22 (-0.17) Buy Dummy (Advisor) 1.04 (0.89) 1.06 (0.91) 0.93 (0.80) 0.88 (0.76) Hold Dummy (Advisor) 0.07 (0.06) 0.12 (0.10) -0.11 (-0.09) -0.18 (-0.16) Mkt Cap 0.02 (1.48) 0.02 (1.60) 0.02 (1.34) 0.02 (1.45) R-Squared N Obs 20% 1388 20% 1388 20% 1388 21% 1388 38 ... examination of conflicts of interest, by looking at the extent to which such conflicts affect both the analysts and the proprietary traders Because we are interested in conflicts of interest, we... those investment banks that rely least on investment banking as a source of revenue, i.e., in those banks where analysts are likely to face the lowest conflicts of interest Within these banks, traders? ??... for conflicts of interest is prevalent within investment banks Nearly all large investment banks offer underwriting services, provide analyst coverage, and have proprietary trading desks, and