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1 the Bidder's Selection and Retention of His Bank Advisor – Its Positive The bidder’s selection and retention of his bank advisor – Its positive effect on the extension of acquisition sequences and formation of a hierarchical investment banking market Pascal Stock1 Abstract: This paper combines the neoclassical theory of M&As with the theory of the development of hierarchical M&A advisory markets in one empirical framework. Hierarchical M&A advisory markets emerge as banks accumulate different levels of expertise and client relationships. The means to analyze the development of expertise and relationships is the formation of acquisition sequences in which investment banks as M&A advisors accumulate industry specific expertise and form relationships with repeat bidders. The empirical analysis shows that the bidder’s selection of the advising investment bank according to its industry expertise and advisory relationship increases the probability of the current bid being succeeded by another one. The successor bid is more likely to be advised, which enables the advising bank to accumulate further expertise and to foster the client relationship. The probability of a successor transaction increases further the larger the bidder’s set of investment opportunities and profitability are. This interrelated bidder-bank matching results in the formation of acquisition sequences and the hierarchical separation of the M&A advisory market with the experienced bulge-bracket banks at the top and the less experienced but more specialized non- bulge-bracket banks at the bottom. Keywords: Mergers & Acquisitions, Acquisition Sequence, Advisory Expertise JEL classifications: G24, G34 1 Author of correspondence: Pascal Stock, University of Mannheim, Schloss (Castle), SO-205, stock@corporate- finance-mannheim.de, +49(0)621-181-3249. All authors in alphabetic order are from the University of Mannheim. 1 1. Introduction The study combines the literature that analyses investment banks as intermediaries in the market for corporate control with the neoclassical theory of mergers and acquisitions (M&A) and the research in acquisition series in a unified empirical framework. The question whether investment banks as M&A advisors support the bidding companies in the exploitation of their investment opportunities by finding targets for successor M&As is supported by the empirical observations. The hiring of banks as M&A advisors, the retention of familiar advisors and the continuation of acquisition sequences leads to banks’ accumulation of expertise. More experienced banks with stronger client relationships are more likely to be hired again, increasing their chances to be retained as advisors in successor transactions. The loop of M&A advisor choice, retention, acquisition continuation and banks’ expertise and client relationship accumulation is repeated until a hierarchy with the most experienced banks, who maintain the strongest client relationships, at the top emerges. This study empirically examines the theories of (Chemmanur & Fulghieri, 1994) and (Anand & Galetovic, 2006), considering advising banks as partners of serial acquirers along their acquisition sequences. Analyzing the role of serial bidders’ bank advisors complements the research of learning along acquisition sequences (Aktas, Bodt, & Roll, 2009; 2011; Croci & Petmezas, 2009) and M&A sequences as means to exploit investment opportunities according to the neoclassical theory (Alexandridis, Mavrovitis, & Travlos, 2012; Andrade & Stafford, 2004; Andrade, Mitchell, & Stafford, 2001; Mitchell & Mulherin, 1996; Klasa & Stegemoller, 2007; Ahern, 2008; Fuller, Netter, & Stegemoller, 2002). The analyses provide further empirical support for the literature that investigates the structure of bank-bidder advisory relationships and the role of investment banks as financial intermediaries in the market for 2 corporate control (Hunter & Walker, 1990; McLaughlin, 1990; 1992; Hunter & Jagtiani, 2003). (Anand & Galetovic, 2006) argue that banks form relationships with bidders to generate M&A advisory business. The bulge-bracket banks form relationships with the largest and most frequent bidders, such as Cisco Systems that bid for and acquired 98 companies in the sample to grow externally. (Chemmanur & Fulghieri, 1994) and (Anand & Galetovic, 2006) model theoretically the hierarchical separation of the investment banking industry for underwriters, and M&As advisors, as a process of repeated rounds in which banks moving to the top accumulate more skills and experience and match with the bidders that benefit most from their experience. This study shows empirically that this process occurs with a concentration of the strongest client relationships among bulge-bracket banks that are active in almost every (Fama & French, 1997) industry every year. Non-bulge-bracket banks are usually specialized boutiques active in a few industries. In the first step of the repeated process the choice of a particular bank as advisor increases by 9.15% if the bank has advised one more deal in the last three years in the target’s industry. Having advised the bidder in one more transaction in the past three years increases the bank’s selection probability by 33.32%. A one standard deviation higher ranking in the SDC M&A Top-50 League Tables increases the bank’s visibility in the advisory market and chance to be chosen by 28.26%. The unconditional initial selection probability in the SDC M&A universe with 45 to 392 banks per year is 0.36 percentage points. Being chosen initially increases the advising bank’s unconditional likelihood of 4.53% to be retained as advisor. A stronger client relationship, one more advised deal in the past three years, increases the bank’s retention probability relatively by 60.47%. Banks familiar with the bidder also pitch deals and are selected as advisors if the bidder accepts the deal proposal. The interrelatedness results in a simultaneous decision of advisor retention and acquisition sequence continuation. Being 3 familiar with the bidder from previously advised deal in terms of a standard deviation greater advisory relationship increase the likelihood to be retained as advisor in the current bid by 11.89% and the successor bid probability of 66.59% relatively by 5.25%. The industry expertise in the target industry, being a standard deviation greater, increases the probability to be retained as old advisor by 27.29% and the continuation probability of the acquisition sequence by 12.04%. The advising bank’s advisory relationship strength and target industry expertise work indirectly on the bidder’s M&A series continuation as well through the retention probability, which itself increases the successor bid probability by 15.65%. Finally being retained as old advisor improves the bank’s target industry expertise by 34.47%, which going back to the first step enhances their chances to be initially chosen as M&A advisor from the set of all possible bank advisors. Besides the influence of the advising investment bank bidders with above industry average profitability and investment opportunities operating in large industries are more likely to continue making bids and acquisitions (Jovanovic & Rousseau, 2002; Servaes, 1991; Lang, Stulz, & Walkling, 1989). The process starts all over, being a loop of simultaneous and interrelated decisions that are self-enforcing. Through this process empirically modeled along the theoretical arguments of (Anand & Galetovic, 2006) and (Chemmanur & Fulghieri, 1994) a few banks with strong client relationships and industry expertise emerge at the top, while the majority of non-bulge- bracket banks or boutiques focus on few industries and arms-length relationships. Goldman Sachs alone advised 4,472 deals in the SDC M&A sample and 654 deals in the final sample of 8,886 bid-bank matches, followed by Merrill Lynch with 514 advisory mandates. The Top-10 M&A advisors account for 3,335 bid-bank matches, or 37.53%, of the 8,886 ones. The analysis uses a panel of 31,954 observations, one to six for advised deals, in sequences of 1 to 98 M&As from 1979 to 2006 by 10,280 bidders, which is constructed from the SDC M&A and Compustat databases. 4 A problem in the analyses is the selection bias and simultaneity caused by banks self-selecting themselves into advising more complex and larger transactions of the largest acquirers that make many acquisitions (Anand & Galetovic, 2006; Chemmanur & Fulghieri, 1994; Golubov, Petmezas, & Travlos, 2012; Bao & Edmans, 2011). The selection bias along the acquisition sequence is modeled with selection indicator dummies in the context of Chamberlain probit panel models including (Mundlak, 1978) fixed effects of the likelihood of retaining an old advisor and a successor transaction (Nijman & Verbeek, 1992; Wooldridge, 2002a; 2002b; Verbeek & Nijman, 1992)2. Finally the interrelated decisions are estimated within biprobit simultaneous equation systems (Heckman, 1978)3. Within the simultaneous equation systems the interrelated decisions of hiring a familiar bank advisor with greater expertise and the M&A sequence continuation are estimated (Sibilkov & McConnell, 2013). For robustness checks biprobit models with selection and instrumental variables (IV) probit models are used (Vella, 1993; 1998; Greene, 2008a; 2008b)4. In which way these results are obtained is elaborated in the following sections. Section 2 summarizes the literature and the hypothesis development. Section 3 follows with the panel description. Section 4 contains the description of the variables, section 5 the univariate analysis, section 6 the multivariate analysis
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