Conflicts of Interest in Merger Advisory Services Linda Allen Zicklin School of Business Baruch College, City University of New York
Stavros Peristiani Banking Studies Function Federal Reserve Bank of New York September 2003 Keyword: Relationship banking, investment bank advisors, commercial bank advisors, certification effect, conflict of interest effect, mergers, acquisitions. JEL Classification: G21
Abstract We find evidence of a conflict of interest in combining lending with merger advisory services. That is, when a commercial bank is chosen to advise the acquirer in an acquisition, there is the implicit promise of future lending at preferential, below market terms. The market reacts to this unresolved agency problem by levying an announcement date decrease in the bank’s abnormal returns of approximately 36 basis points. This negative announcement effect is not observed for investment bank advisors of acquiring firms.
Address correspondence to: Linda Allen, Baruch College, 17 Lexington Avenue, Box 10225, New York, New York 10010,
[email protected]. The opinions expressed in this paper are those of the authors, and do not necessarily represent those of the Federal Reserve Bank of New York or the Federal Reserve System.
Conflicts of Interest in Merger Advisory Services Revelations of conflicts of interest in financial analysts’ recommendations have created a crisis of confidence in the trustworthiness of large, complex financial institutions that are subject to the pull of competing interests. Already there are those with second thoughts about the passage of the Gramm-Leach-Bliley Act of 1999 that expanded banking powers to include a broad range of banking, securities, underwriting and insurance activities.1 Adherence to all of the financial conglomerate’s many fiduciary responsibilities may, at times, be compromised by the allure of high fees and increased market share. This is particularly the case if the additional fees are booked immediately (say, in the case of lucrative underwriting contracts), but the conflicts only potentially realized at a later date (e.g., in the poor performance of portfolios constructed following stock pickers’ recommendations).2 Moreover, cyclical fluctuations can make it even more difficult to connect the dots of conflicting interests – rising markets hide a multitude of sins and declining markets may reveal spurious connections. In this paper, we examine the role of financial advisors in mergers and acquisitions. In contrast to previous work by Allen, Jagtiani, Peristiani and Saunders (2003), (hereinafter, AJPS), we focus on the impact of potential conflicts of interest on the financial institution itself, rather than on the merger counterparties. AJPS find that
1
Kanatas and Qi (2003) describe possible conflicts of interest between lending and underwriting and claim that specialized financial intermediaries are more innovative than universal banks. However, Saunders and Stover (2001) find evidence of economies of scope between underwriting and commercial banking when the same bank serves as underwriter and as credit guarantor. 2 Potential conflicts of interest are exacerbated by intra-firm agency conflicts where one division gains at the expense of other divisions. Risk-adjusted internal capital charges, using concepts such as RAROC, may levy a shadow price for these intra-firm conflicts. However, the setting of these capital allocation charges is quite difficult in practice and becomes more difficult the more complex the institution. 2
commercial banks have a net certification effect in advising target firms, stemming from private information gathered over the course of a prior banking/lending relationship. That is, since commercial bank lending and other relationships are often long standing and continuous, requiring the ongoing monitoring of the firm’s activities, thereby producing private information about the firm’s value. The authors find that target firms experience significant positive abnormal returns when they engage their own commercial bank as a financial advisor. However, acquirers experience no such certification gain in hiring their own commercial banks as financial advisors. AJPS also find that acquirers are more likely to use a commercial bank as a financial advisor if they have had a prior lending relationship with the bank. The motivation for this choice is potential access to future financing for the acquirer or for the merged entity.3 Empirical evidence shows that acquirers expect, and are more likely to receive, future financing from the commercial bank chosen to advise the acquirer in a merger if there has been a prior lending relationship between the bank and acquiring firm.4 In this paper, we examine the consequences of this choice for the financial advisor. Tied-in sales, such as the joint offering of financial advice and financing commitments (either explicit or implicit) are not necessarily nefarious. Indeed, one of the primary motivations for the Gramm-Leach-Bliley Act of 1999 was the potential
3
This may because the commercial bank advisor has gathered private information about the acquiring during the long term banking relationship, thereby giving the bank cost advantages in monitoring the loan. Benveniste, et al. (2003) find evidence of information advantages in the choice of IPO underwriter. In contrast, Fernando, et al. (2003) show that the issuer chooses an underwriter based on reputation and may switch from IPO to SEO if the quality of the issuer has deteriorated. 4 Although we find evidence of conflicts of interest when the bank combines lending with merger advisory activities, Bharadwaj and Shivdasani (2003) find that acquirers earn positive abnormal returns in mergers financed with bank debt. 3
realization of cost and profit synergies that could be obtained from the cross-selling of financial services resulting from the reusability of information (see Chan, Greenbaum, and Thakor (1986) for a discussion of the reusability of information).5 However, if for example, the financial advisor underprices the loans extended to the acquirer in order to win lucrative merger advisory business, then the combination of lending and advisory services may be value reducing, rather than value enhancing.6 This mispricing can persist if there are intra-firm agency conflicts that induce merger advisors to extend implicit promises of discounted future lending so as to maximize advisory fees. That is, the merger advisory department earns credit (say toward the department’s P&L) for the fees earned, but does not bear the cost of subsequent loan losses or inappropriately priced loan commitments. This internal agency problem within the commercial bank creates the possibility that loan commitments extended in the course of providing merger advice to acquiring firms may be mispriced and inappropriately structured. Alleviating this would require deducting from the upfront advisory fees the discount inherent in the loan’s underpricing. The extent of any persistent conflicts of interest in combining lending with merger advisory services reflects unresolved agency problems within large, complex financial institutions.7, 8
5
For a discussion of the debate regarding possible synergistic benefits from expanding banking powers, see Mester (1992, 1996) and Allen and Jagtiani (2000). 6 The Economist (January 11, 2003) reports that there is concern that lead banks are underpricing the yields on syndicated bank loans in exchange for investment banking business. 7 As an example, the potential for conflicts of interest was raised in the case of Lehman Brothers, the advisor for Dynegy, the erstwhile acquirer of Enron Corporation in the context of repayment of a $179 million swap transaction. For example, Citigroup Inc. and JP Morgan Chase & Co. had been acting as both merger advisors and lenders to Enron. After Enron sought bankruptcy-law protection from creditors, those two banking firms were precluded from serving as advisors because of their creditor status (Smith 4
This paper examines the financial advisors’ announcement date equity returns in order to detect market reactions to these potential conflicts of interest in the choice of merger advisor. Our results are consistent with persistent conflicts of interest within commercial banks that provide merger advisory services to acquiring firms only. That is, the market anticipates these agency conflicts whenever an acquirer hires its own commercial bank as an advisor. These conflicts of interest appear to be priced by the market in the form of announcement date declines in abnormal returns. Overall, bank equity returns decline approximately 36 basis points whenever a commercial bank is chosen as a financial advisor by an acquiring firm with which the bank has had a prior lending relationship. The market is therefore alarmed that merger advisory fees may be obtained at the expense of future loan losses. Investment banks that are chosen as financial advisors by acquirers with which there has been a prior lending relationship do not experience this negative market reaction. This may be because there is not the same presumption of future lending by investment banks that is expected of commercial banks.9 Moreover, we find no evidence of a consistent merger announcement date effect when the target firm hires its own commercial bank as financial advisor. Consistent with the AJPS, we find that positive abnormal returns resulting from the commercial bank’s
(2001), “Lehman Faced Possible Conflict as Merger Failed,” Wall Street Journal, December 5, 2001, p. C1, C11). 8 Macey and O’Hara (2003) contend that commercial banks have unique corporate governance problems (due to the existence of the safety net, the high degree of financial leverage and the structure of bank assets/liabilities), thereby preventing the resolution of these agency conflicts. 9 Investment banks may also build lending relationship and obtain private information, for example, in the course of underwriting activities. However, underwriting episodes are discrete and intermittent, corresponding to the relatively short time period surrounding the issue registration, offering period, and after-market support period. 5
certification of the target firm’s value appear to accrue to the target firm only, and not to the target’s commercial bank advisor. Section 2 presents the market return model and describes how we measure the credit/lending explanatory variables used in the regression analysis. Our results are presented in Section 3, and the paper concludes in Section 4.
2.
Methodology This paper uses the AJPS terminology to identify the credit/lending relationship
between bank advisor and merger participants (target and acquirers).10 In particular, we employ four different dummy variables. The binary indicator TBBT takes on the value 1 if the target’s advisor is a commercial bank and if the bank advisor had a prior relationship with the target (i.e., the Target is advised by a Bank and the Bank has lent money to the Target). Similarly, TBBA is 1 if the target’s advisor is a commercial bank and if the bank advisor had a prior relationship with the acquirer (the Target is advised by a Bank and the Bank has lent money to the Acquirer). The variable ABBT indicates the acquirer’s advisor is a commercial bank and if the bank advisor had a prior relationship with the target (the Acquirer is advised by a Bank and the Bank has lent money to the Target). Finally, ABBA takes on the value 1 if the acquirer’s advisor is a commercial bank and if the bank advisor had a prior relationship with the acquirer (the Acquirer is advised by a Bank and the Bank has lent money to the Acquirer).11
10
A credit/lending relationship exists if the bank has made loans to either merger counterparty at some date prior to the merger announcement date. The precise empirical definition of a credit/lending relationship is presented in Section 3. 11 More than one of these variables could take on the value of one for any given observation. Thus, if TBBT = TBBA = 1 then the target advisor has had prior lending relationships with both target and acquirer. 6
We then take the cross product term of the four relationship dummy variables (TBBT, TBBA, ABBT and ABBA) multiplied with the two dummy variables indicating whether we are examining the equity returns of the target firm’s advisor (ADVT=1) or the acquirer’s advisor (ADVA=1). Thus, for example, if TBBA_ADVT=1, the equity returns are those of the target firm’s advisor to a deal in which the target’s advisor is a commercial bank and the bank advisor had a prior relationship with the acquirer. Since financial institutions advise many different merger counterparties, it is inappropriate to use the standard event study methodology to determine the merger announcement effect on the advisors’ equity returns. Thus, we utilize the regression approach proposed by Schipper and Thompson (1983) and Brown and Warner (1985). The return model is defined as follows:
Rit = β m Rmt + β r Dit × RVit • + β c Dti × CVit • + ε it
(1)
where Rit is the daily equity return of financial advisor (i ) obtained from CRSP over the period January 1, 1995 through December 31, 2000, Rmt is the CRSP equally weighted
index of daily equity returns, Dit is the merger announcement event dummy which takes on a value of 1 for the [ -1,+1] days around the merger announcement and 0 otherwise. The explanatory vector RVit • represents a vector of relationship variables. In addition to relationship variable defined previously, we use cross product dummy variables relating the relationship variables to the length of the prior lending relationship, the purpose of the loans and the intensity of the borrower-advisor relationship. Similarly, the vector CVit • controls for merger characteristics such as the deal size, and source of funds.
7
The panel regression model defined by equation (1) is estimated using least squares. However, our empirical findings are robust to other methods of estimation. In particular, we obtained similar regression estimates using GMM estimation that corrects for the possibility of heteroskedastic error covariance structure. Because bank stock returns are likely to be correlated across time, we also estimated the panel regression using a seemingly unrelated regression (SUR) system of equations (one for each financial advisor). Although there were some convergence problems, the results did not change qualitatively. Results for the SUR and GMM estimations are available from the authors upon request.
3. Sample and Data Mergers and acquisitions data were obtained from the Thomson Financial Securities Data Corporation (SDC) database. All mergers and acquisitions involving U.S. target firms over the period January 1, 1995 through December 31, 2000 were identified. We excluded all mergers involving financial firms as either target or acquirer.12 We formed a subset of deals consisting of merger transactions in which either side of the transaction (target or acquirer) or both list a commercial bank (or its subsidiary) as an advisor.13 We then conducted a Lexis/Nexis search on each of the
12
This provides a cleaner test of the impact of prior lending relationships on merger returns because lending between financial institutions may be short-term and therefore have less information content (e.g., overnight Fed funds lending and repo transactions). 13
Several commercial bank holding companies themselves acquired investment firms during the sample period. We included acquisitions advised by the investment firm as acquisitions advised by commercial banks if the deal was announced after the commercial bank acquired the investment firm. For instance, in April 1997 Alex-Brown & Company was acquired by Bankers Trust. Prior to that date, acquisitions advised by Alex-Brown were considered to be non-bank advised mergers. After that date, they were classified as bank advised mergers.
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targets and acquirers to determine whether there was a prior lending relationship with any of the bank advisors. In this search, we examined SEC 10K, 10Q, and 8K filings, as well as annual reports, prospectuses, and other registered filings that dated back to January 1990 in order to determine whether the bank advisors had any prior credit/lending relationship with either of the parties to the merger. If the bank advisor was listed in any of the SEC filings of the merger parties, we recorded a bank relationship dummy variable of one.14 If there was no mention of the bank advisor, but there was a description of other bank relationships, we recorded a bank relationship dummy variable of zero.15 If there was any ambiguity in defining the bank relationship for either the target or the acquirer, we recorded the relationship as missing and the observation was dropped from the analysis. Using this procedure, we constructed the four dummy variables that distinguish among the four possible lending relationships: the target's bank advising the target (TBBT), the acquirer's bank advising the target (TBBA), the target's bank advising the acquirer (ABBT), and the acquirer's bank advising the acquirer (ABBA). To fill in the gaps and add additional detail to the description of bank relationships, we obtained data on loan syndications from Loan Pricing Corporation (LPC). If LPC showed that a financial advisor participated in loan syndication in any capacity (i.e., as an agent, arranger, or participant) prior to the merger announcement date, then we recorded that as a prior lending relationship. The LPC database includes
14
Because the SEC does not require firms to reveal specific details about their banking relationships, we could not utilize more detailed data about the nature of the relationship. Data obtained from Loan Pricing Corporation contained more detailed descriptions of the lending relationship. 15 We therefore avoided the problem of recording no relationship for companies that chose not to report any of their banking arrangements. Unless there was a systematic attempt to omit the names of merger advisors from firm disclosures of lending relationships, this should result in an unbiased sample. 9
description of the role of the lender, the origination date of the loan syndication, and the purpose of the loan, among other descriptive variables. We used these as control variables to analyze the intensity of the lending relationship for the subset of deals that were included in the LPC database.16 Our sample includes only those firms whose shares were traded on NYSE, AMEX, or NASDAQ. We verified the SDC announcement date using the Wall Street Journal, and used the date in the Wall Street Journal whenever there was a discrepancy. We estimated the market model defined by equation (1) over the period January 1, 1995 through December 31, 2000 for the 20 (publicly traded) commercial bank and investment bank advisors most active in the mergers and acquisitions. The group of commercial banks includes Citicorp (before Travelers), Citigroup, FleetBoston, BankBoston (before Fleet), Bankers Trust (before Deutschebank), Chase Manhattan (before merger with JP Morgan), JP Morgan (before Chase), Nationsbank (including period after merger with Bank of America), Bank of America (before merger with Nationsbank), and Canadian Imperial Bank of Commerce (CIBC). The group of investment bank firms were classified into two categories: top-tier and mid-tier. The list of top-tier investment banks includes Alex Brown, Salomon Brothers (before merger with Citigroup), Merrill Lynch, Goldman Sachs, and Morgan Stanley. The remaining investment bank firms (Bear Stearns, Donaldson Lufkin and Jenrette, Lehman Brothers, and Hambrecht Quist) were classified into the mid-tier category. Table 1 summarizes the sample of deals included in our analysis. Overall, our
16
Although LPC focuses on syndicated loans, it also includes some private placements and underwritten debt. However, since the SEC filings consider all bank-lending relationships, we used the LPC database to fill in the missing observations from the more comprehensive Lexis/Nexis. 10
sample of large commercial banks and investment banks collectively advised 588 deals from January 1995 to December 2000. The table shows average market capitalization of targets and acquirers was roughly $2.6 billion and $13.5 billion, respectively. Approximately 31.4 percent of acquirers hired bank advisors. Out of the 588 mergers, 15.13% commercial and investment bank target advisors had a prior lending relationship with the target and 14.3% of these target advisors had an existing relationship with acquirers. Table 1 also shows that roughly 24% of the acquirer advisors had prior lending relationships with either the target (10.88%) or the acquirer (13.94%).
4. Empirical Results Table 2 presents results for the narrow regression model that focuses solely on the banking existence of the banking relationship. The coefficient on the ABBA_ADVA variable is significantly negative (at the 5% level) for commercial bank advisors. This reflects an average decline of 35 basis points in the acquirer’s advising bank’s daily equity returns upon the announcement that the commercial bank has been chosen to advise the acquirer in a merger with which the bank has had a prior lending relationship. On the surface, the magnitude of the 3-day decline in the advisor’s return may not appear that large, but what is important here is that statistical significance of the regression coefficient indicates that the market has a negative view of this pre-existing credit relationship. This result is consistent with the presence of conflicts of interest when commercial banks advise their borrowers as acquirers in mergers and acquisitions. The coefficient on the ABBA_ADVA variable is insignificantly different from zero for investment bank advisors, suggesting that the market does not anticipate conflicts of interest in the investment banking relationship with acquirers. Moreover, the market does not anticipate conflicts of interest in the acquirer’s advisor’s returns when there is a prior 11
lending relationship between the target and the target’s bank advisor, as shown by the positive and significant (at the 10% level) coefficient on the TBBT_ADVA variable for commercial banks. Thus, it is only the combination of past lending relationships and advisory services for acquiring firms that results in the anticipation of conflicts of interest for commercial bank advisors. This result is robust through all forms of the regression analysis. As expected, the market return variable is highly significant, with the average market beta for commercial banks shown as 1.235 in Table 2. In contrast, the market beta for investment banks averages 1.855. All other control variables are either weakly significant or insignificantly different from zero. The size of the deal, measured here the log market capitalization of the target firm, is positive and statistically significant. Presumably, target size is a fairly good proxy of the fee business generated by the merger deal. Table 3 presents the results of the wider regression analysis that incorporates variables that control for the intensity and duration of the prior lending relationships between merger counterparties and financial advisors. None of these additional control variables are significant for investment bank advisors. However, the Lender_TBBT variable is significantly positive (at the 5% level) for commercial bank advisors, consistent with the positive certification effect found by AJPS. That is, abnormal returns are higher when target firm’s hire as advisors with whom they have had an informationproducing prior lending relationship. As in Table 2, the coefficient on the ABBA_ADVA variable is significantly (at the 5% level) negative in the wider regressions shown in Table 3, consistent with the presence of conflicts of interest for commercial bank advisors of acquiring firms. Moreover, the Source of Funds variable is significantly (at the 10% 12
level) negative for investment bank advisors, suggesting that advisor returns decline when the merger is financed using borrowed funds. This result offers additional support for the conflicts of interest hypothesis resulting from combining borrowing with merger advisory activity.
5. Conclusion Our findings demonstrate that the market is concerned about a potential conflict of interest as commercial bank advisors provide lending to acquirers in return for merger advisory fees. The advisor’s implicit (or explicit) promise to provide credit is viewed as a potential conflict of interest by the market and weakens any perceived profits resulting from merger advisory fees; i.e., losses on future loan commitments (as well as related adverse reputational effects) may more than offset merger advisory fees. Using the Enron-Dynegy merger as an example, from the Wall Street Journal, November 28, 2001, page C15: JP Morgan and Citigroup, who have served as the top underwriters of [Enron’s] debt, would rather avoid being blamed for letting Enron’s debt go bad. Even more importantly, they also hold their own portion of that debt. Thus, both banks recently provided an additional credit line to Enron totaling $1 billion….[S]peaking privately, bankers concede that a failure of the Enron deal would smart beyond what the damage might be to the banks’ loan portfolio. ‘If it falls apart,’ says Mr. Hayes, the Harvard professor, ‘it will be a source of embarrassment.’ Of course, the Enron-Dynegy deal did subsequently fall apart in November 2001, thereby validating the market’s concerns about bank conflicts of interest when banks provide merger advice to their own clients in the course of an acquisition. Indeed, on the day after the announcement of the Enron bankruptcy filing, Citigroup’s stock price declined more than 2% and JP Morgan Chase’s stock price fell by more than 3%.
13
Table 1. Descriptive Statistics for Merger Deals Number of deals included in the panel sample: 588 deals Characteristics
Summary Statistics
Market Capitalization of Acquirer ($ billions)
13.5
Market Capitalization of Target ($ billions)
2.6
Withdrawn Deals Source of Funds: Percent Borrowing Target advisor is a bank with a prior relationship with the target (TB_BT) Target advisor is a bank with a prior relationship with the acquirer (TB_BA) Acquirer advisor is a bank with a prior relationship with target (AB_BT) Acquirer advisor is a bank with a prior relationship with acquirer (AB_BA)
14
74 (12.58%) 56 deals (9.52%) 89 deals (15.13%) 71 deals (12.07%0 64 deals (10.88%) 82 deals (13.94%)
Table 2 The Impact of Merger Advice on Advisors’ Abnormal Returns Variable
All Deals
Market Index RVti• : Relationship Controls TBBT_ADVA TBBA_ADVA ABBT_ADVA ABBA_ADVA TBBT_ADVT TBBA_ADVT ABBT_ADVT ABBA_ADVT
1.516*** (77.55)
Commercial Bank Advised Deals 1.235*** (54.16)
Investment Bank Advised Deals 1.855*** (55.97)
-0.082 (-0.383) -0.138 (-0.565) -0.058 (-0.325) -0.264* (-1.701) 0.214 (1.340) -0.283 (-1.550) -0.331 (-1.462) -0.042 (-0.202)
0.408* (1.682) 0.123 (0.455) -0.150 (-0.745) -0.355** (-2.140) 0.012 (0.069) -0.244 (-1.203) -0.295 (-1.204) 0.420 (1.353)
-0.638 (-1.617) -0.443 (-0.971) -0.062 (-0.180) 0.029 (0.083) 0.474 (1.631) -0.387 (-1.114) -0.435 (-1.268) -0.182 (-0.605)
-0.292** (-2.006) 0.026*** (3.249) -0.152 (-1.151) 23,625
-0.141 (-0.787) 0.015* (1.662) -0.141 (-1.355) 13,255
-0.401* (-1.705) 0.034** (2.125) -0.160 (-0.747) 10,370
0.205
0.184
0.235
CVti• : Merger Deal Control Variables Source of Funds: %Borrowing Log(Target Size) Deal Event NOBS R2
Notes: *, **, *** indicate significance at the 10%, 5% and 1% levels, respectively. tvalues are in parentheses. The pooled return generating function was estimated for 20 advisors over the period January 1995 – December 2000 (or whatever subset was relevant for each bank). 11 of the advisors were classified as commercial banks and 9 of the advisors were classified as 15
investment banks. The dependent variable is the percent daily return (including dividends) for each financial advisor. The independent variables are: TBBT_ADVA = 1 if the dependent variable’s bank advised the acquirer and the target’s advisor had a prior banking relationship with the target firm. TBBA_ADVA = 1 if the dependent variable’s bank advised the acquirer and the target’s advisor had a prior banking relationship with the acquiring firm. ABBT_ADVA = 1 if the dependent variable’s bank advised the acquirer and the acquirer’s advisor had a prior banking relationship with the target firm. ABBA_ADVA = 1 if the dependent variable’s bank advised the acquirer and the acquirer’s advisor had a prior banking relationship with the acquiring firm. TBBT_ADVT = 1 if the dependent variable’s bank advised the target and the target’s advisor had a prior banking relationship with the target firm. TBBA_ADVT = 1 if the dependent variable’s bank advised the target and the target’s advisor had a prior banking relationship with the acquiring firm. ABBT_ADVT = 1 if the dependent variable’s bank advised the target and the acquirer’s advisor had a prior banking relationship with the target firm. ABBA_ADVT = 1 if the dependent variable’s bank advised the target and the acquirer’s advisor had a prior banking relationship with the acquiring firm. Market Index = the CRSP equally weighted index of daily returns (percent). Source of Funds = 1 if the merger was financed using borrowed funds. Deal Size = the sum of the log market capitalization of the acquirer and target firms.
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Table 3 Controlling for the Intensity of Banking Relationships Variable
All Deals
Market Index RVti• : Relationship Controls TBBT_ADVA TBBA_ADVA ABBT_ADVA ABBA_ADVA TBBT_ADVT TBBA_ADVT ABBT_ADVT ABBA_ADVT Lender_ABBA Lender_ABBT Lender_TBBA Lender_TBBT Duration_ABBA Duration_ABBT Duration_TBBA Duration_TBBT
1.517*** (77.57)
Commercial Bank Advised Deals 1.235*** (54.16)
Investment Bank Advised Deals 1.858*** (55.97)
-0.108 (-0.495) -0.104 (-0.421) -0.059 (-0.326) -0.315* (-1.880) 0.180 (1.106) -0.203 (-1.080) -0.322 (-1.417) -0.078 (-0.370) -0.192 (-0.248) -0.181 (-0.371) -0.640 (-0.852) 2.571*** (2.774) -0.026 (-0.296) 0.011 (0.191) -0.153 (-1.311) -0.613** (-2.377)
0.380 (1.553) 0.147 (0.536) -0.138 (-0.675) -0.436** (-2.501) 0.071 (0.360) -0.077 (-0.360) -0.324 (-1.079) 0.376 (1.195) 0.925 (0.937) -0.164 (-0.333) -0.973 (-1.276) 2.451** (2.314) 0.001 (0.011) 0.066 (1.052) -0.182 (-1.318) -0.388 (-1.187)
-0.790* (-1.944) -0.357 (-0.751) -0.043 (-0.123) 0.034 (0.092) 0.468 (1.602) -0.422 (-1.243) -0.422 (-1.243) -0.179 (-0.582) -1.117 (-0.928) -0.321 (-0.271) -1.781 (-0.864) 1.103 (0.620) -0.045 (-0.318) -0.056 (-0.428) -0.126 (-0.557) -0.548 (-1.270)
17
(TABLE 3 Continued) Variable
0.342 (0.406) -0.147 (-0.295) 1.135 (1.219) -1.046 (-1.138)
Commercial Bank Advised Deals -0.750 (-0.708) -0.358 (-0.727) 1.373 (1.321) -1.802 (-1.605)
Investment Bank Advised Deals 1.213 (0.870) 0.182 (0.142) 2.587 (1.266) 0.945 (0.579)
-0.322** (-2.182) 0.026*** (3.272) -0.134 (-1.331)
-0.159 (-0.872) 0.019** (2.052) -0.141 (-1.337)
-0.437* (-1.651) 0.032** (2.004) -0.144 (-0.673)
NOBS
23,625
13,255
10,370
R2
0.206
0.185
0.235
Purpose_ABBA Purpose_ABBT Purpose_TBBA Purpose_TBBT CVti• : Merger Deal Control Variables Source of Funds Log(Target Size) Deal Event
All Deals
Notes: *, **, *** indicate significance at the 10%, 5% and 1% levels, respectively. tvalues are in parentheses. The pooled return generating function was estimated for 20 advisors over the period January 1995 – December 2000 (or whatever subset was relevant for each bank). 11 of the advisors were classified as commercial banks and 9 of the advisors were classified as investment banks. The dependent variable is the percent daily return (including dividends) for each financial advisor. All variables are as defined in Table 2. In addition, the following variable definitions apply to Table 3: Lender_TBBT (Lender_ABBT) = 0 if the target firm has no banking relationships with the target (acquirer) advisor; =1 if the target’s bank acted as a participant in a loan syndication to the target (acquiring) firm prior to the deal announcement date; =2 if the target’s bank acted as an agent or arranger for a loan syndication to the target (acquiring) firm prior to the deal announcement date. Lender_TBBA (Lender_ABBA) = 0 if the acquirer has no banking relationships with the target (acquirer) advisors; =1 if the acquirer’s bank acted as a participant in a loan syndication to the target (acquiring) firm prior to the deal announcement date; =2 if the 18
acquirer’s bank acted as an agent or arranger for a loan syndication to the target (acquiring) firm prior to the deal announcement date. Duration_TBBT (Duration_ABBT) = the length of time (in years) between the origination of the earliest loan syndication to the target by the target (acquirer) advisor. Duration_TBBA (Duration_ABBA) = the length of time (in years) between the origination of the earliest loan syndication to the acquirer by the target (acquirer) advisor. Purpose_TBBT (Purpose_ABBT) = 0 if there were no prior loan syndications to the target firm involving the target (acquirer) advisor; =1 if the purpose of the loan syndication by the target (acquirer) advisor to the target firm was related to an acquisition; = 2 if the purpose of the loan syndication by the target (acquirer) advisor to the target firm was for general business purposes. Purpose_TBBT (Purpose_ABBT) = 0 if there were no prior loan syndications to the target firm involving the target (acquirer) advisor; =1 if the purpose of the loan syndication by the target (acquirer) advisor to the target firm was related to an acquisition; = 2 if the purpose of the loan syndication by the target (acquirer) advisor to the target firm was for general business purposes.
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References
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