Seller Selection of M&A AdvisorsAuthor(s): Hugh ThomasSource: Financial Management, Vol. 22, No. 4 (Winter, 1993), pp. 17-18Published by: Wiley on behalf of the Financial Management Association InternationalStable URL: http://www.jstor.org/stable/3665568 .

Accessed: 12/06/2014 19:07

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp

.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact support@jstor.org.

.

Wiley and Financial Management Association International are collaborating with JSTOR to digitize, preserveand extend access to Financial Management.

http://www.jstor.org

This content downloaded from 185.2.32.109 on Thu, 12 Jun 2014 19:07:27 PMAll use subject to JSTOR Terms and Conditions

FM LETTERS 17

Exhibit 1-2. Regressions of the Stock Price Reaction to Antitakeover Amendments on the Firm's q Ratio and Managerial Share Ownership (p-Values in Parenthe- ses)

Share Constant q Ratio Ownership R2 F-Statistic

All firms 0.662 -0.146 -0.039 3.9% 2.85

n = 145 (0.122) (0.627) (0.031) (0.061)

q > 1 1.481 -0.414 -0.053 8.8% 3.05

n = 66 (0.064) (0.304) (0.042) (0.054)

q < 1 -0.054 0.491 -0.030 1.6% 0.61

n = 79 (0.970) (0.803) (0.273) (0.545)

Exhibit 1-2 presents regression results, including p-values for coefficient esti- mates, for the full sample and for firms classified according to their q ratio in the

year of proposal. In all cases, the coeffi- cient estimate of the q ratio for firms with

q less than one is positive and statistically insignificant. Again, results are inconsis- tent with the prediction of LSW [3]. In addition, q ratio coefficient estimates for firms with q ratios of at least one are also

statistically insignificant. The regressions for the full sample and for firms with q ratios of at least one are statistically signifi- cant. For these samples, the managerial share ownership coefficient estimate is sta-

tistically significant. It is interesting to note that the relation

between the stock price reaction to amend- ment proposals and managerial share own-

ership observed in McWilliams [4] tends to hold for high-q firms, but not for low-q firms. This suggests that the amendments are beneficial (intercepts are positive and

significant) when proposed by firms with low managerial share ownership and high- q ratios, but that this benefit does not exist when the amendments are proposed by firms having low managerial share owner-

ship and low-q ratios. A benefit attributed to antitakeover

amendments is increased bargaining power in the event of a takeover bid. The results of the regression analyses suggest that the market recognizes the amend- ments' benefit for low managerial share ownership/high-q firms, but not for low managerial share ownership/low-q firms. This conclusion is, in a sense, consistent with LSW [3]. Because low-q firms are the

ones that should benefit most from a take- over, it appears that the market does not recognize the amendments as providing increased bargaining power for these firms.

In conclusion, the results of the event- study analyses are inconsistent with LSW's [3] conjecture in that I find no

significant stock price reactions or differ- ences in stock price reactions. The market does not appear to view the amendments as enhancing entrenchment for low-q ratio firms. However, the regression analyses yield results which partially support LSW. The benefit of increased bargaining power attributable to the amendments is not real- ized for the low-q firms.

References 1. S. Brown and J. Warner, "Using Daily Stock

Returns: The Case of Event Studies," Jour- nal of Financial Economics (March 1985), pp. 3-31.

2. Investor Responsibility Research Center, Inc., Antitakeover Charter Amendments: A

Directory of Major American Corpora- tions, Washington, D.C., 1985.

3. L. Lang, R. Stulz, and R. Walkling, "Mana- gerial Performance, Tobin's q, and the Gains from Successful Tender Offers," Journal of Financial Economics (Septem- ber 1989), pp. 137-154.

4. V.B. McWilliams, "Managerial Share Own- ership and the Stock Price Effects of Anti- takeover Amendment Proposals," Journal of Finance (December 1990), pp. 1627- 1640.

Victoria B. McWilliams Assistant Professor

Arizona State University - West Campus Phoenix, AZ

Seller Selection of

M&A Advisors This note reports on the interactive ef-

fect of client and investment bank charac- teristics on the selection of a financial ad- visor in order to shed light on scope econ- omies in investment banking. The analysis follows Hayes et al. [1] in modelling the decision of the selling firm in an M&A transaction using the conditional logit model, whereby the probability of an advi- sor being selected for a transaction is a function of advisor and advisor-transac- tion interaction terms

P[si, j]9= 9(1) Y

e"ei, k

k=lI

where P[si, j] is the probability that the ith transaction's seller engages thejth advisor, wi, j is a row vector of characteristics of the ith transaction's seller interacting with the jth advisor and 3 is a column vector of parameters which are estimated by the model. Each wi, j can be a simple advisor attribute (invariate to transaction) or an interactive effect between the transaction and the advisor. In this study,

wi,.j = aj ci (2)

where aj is a 5 x 1 vector of advisor attri- butes and ci is the 4 x 1 vector consisting of one in the first row and the three trans- action characteristics in the remaining three rows.

Five variables are used as advisor attri- butes: research expertise, M&A capability, capital markets capability, book value of equity and percent of assets invested in corporate securities. Based on a separate study [2], three transaction characteristics are used: transaction value, transaction value relative divided by seller's equity, and institutional investor ownership. Advi- sor attribute data are obtained from Insti- tutional Investor's "All American Re- search Team," Greenwich Associates an- nual poll of investment banking services, and SEC broker dealer filings. Transac- tions data consist of 279 sales of significant assets and changes in control ranging in size from $13.4 billion to $5 million from

This content downloaded from 185.2.32.109 on Thu, 12 Jun 2014 19:07:27 PMAll use subject to JSTOR Terms and Conditions

18 FINANCIAL MANAGEMENT / WINTER 1993

the Securities Data Corporation M&A Database, 1988 through 1990.

The estimated parameters of the model, shown in Exhibit 2-1, are robust. Although the change of control and the asset sales

subsamples produce significantly different coefficients (according to a Wald test), none of the coefficients that are significant in the total sample change sign in either of the subsamples. The results in Exhibit 2-1 are not sensitive to the exclusion of any one advisor. In a test of the independence of irrelevant alternatives hypothesis, when each of the nine advisors (Bear Steams, First Boston, Goldman Sachs, Kidder Pea-

body, Lehman Brothers, Merrill Lynch, Morgan Stanley, Salomon Brothers and Smith Barney Harris Upham) is dropped in turn from the sample, there is no statisti-

cally significant alteration of the model's

parameters. Advisor attributes alone do not explain

the propensity of clients to select specific advisors. Statistically (using a likelihood ratio test comparing Exhibit 2-1's re- stricted model with the unrestricted model), the model with advisor and trans- action-advisor interactive effects has more

explanatory power than that with advisor attributes only. Practically, different sellers look for different attributes in an advisor. M&A capability is valued more highly the

higher the institutional ownership of the seller. Research expertise is only important as the absolute size of the transaction in- creases. Expertise in capital markets activities is detrimental to obtaining advi-

sory mandates, but this adverse effect is

increasing (for capital markets expertise) only in the relative value of the transaction. The size of the advisor's book in corporate securities is increasingly detrimental to se-

curing an advisory assignment the larger is the transaction.

Given these mixed effects, the advisor

may question what it should do to increase

general market share. Mathematically, marginal effects are functions of the prob- ability of selection and the model's param- eters interacting with transaction and advi- sor characteristics:

8P[si, j]

~ta

= P[si,

j] (1 -P[si, j])Oci (3)

Exhibit 2-1. Estimated Parameters of the Model

Advisor Attributes and Interactive Effects Advisor Attributes Only

(Unrestricted Model) (Restricted Model)

Variable Coefficient t-statistic Coefficient t-statistic

RESEARCH -0.0010 -0.15 0.0079 3.21**

CAPITAL MARKETS CAPABILITY 0.0423 1.09 -0.0249 -1.62

M&A CAPABILITY -0.0655 -2.33* 0.0520 4.35**

EQUITY 0.0119 0.42 0.0256 2.38*

PERCENT CORPORATE SECURITIES -0.0329 -0.66 -0.0303 1.72

VALUE x RESEARCH 0.0019 2.72**

VALUE x CM CAPABILITY 0.0047 1.67

VALUE x M&A CAPABILITY -0.0026 -0.85

VALUE x EQUITY 0.0019 1.39

VALUE x PERCENT COR SEC -0.0117 -2.69*

RELVAL x RESEARCH 0.0010 0.68

RELVAL x CM CAPABILITY -0.0258 -2.56*

RELVAL x M&A CAPABILITY 0.0196 2.46

RELVAL x EQUITY 0.0057 0.95

RELVAL x PERCENT COR SEC 0.0146 1.28

II HOLDING x RESEARCH 0.0000 0.08

H HOLDING x CM CAPABILITY -0.0012 -1.34

II HOLDING x M&A CAPABIILTY 0.0028 4.06**

II HOLDING x EQUITY 0.0000 0.07

II HOLDING x PERCENT COR SEC 0.0004 0.41

Notes: *Coefficient is significant at the 5% level in a two-tail test. **Coefficient is significant at the 1% level in a two-tail test.

where 0 is the lx 4 subvector of P' contain-

ing the attributes of interest and ci is the 4 x 1 vector describing the ith transaction, as embodied in Equation (2).

The regression results suggest that

greater equity increases the likelihood of

being selected, but that increasing equity by $100 million only increases the proba- bility of being selected by 0.002. The ef-

fects of greater M&A expertise and greater research expertise are also generally posi- tive. In contrast, an increase of one percent in the percentage of assets invested in cor-

porate securities decreases the probability of selection by 0.004. Moreover, for some transactions and some advisors, the mar-

ginal effect is considerably greater (up to

-0.10). Capital markets capability has an

ambiguous marginal effect: while on aver-

age, it makes no difference to the prospects of being hired, in certain circumstances, it

can make a considerable (and usually neg- ative) difference.

References 1. S.L. Hayes III, A.M. Spence, and D.V.P.

Marks, Competition in the InvestmentBank- ing Industry, Cambridge, MA, Harvard Uni- versity Press, 1983.

2. H. Thomas, "Effects of Ownership Struc- ture on Hiring of Advisors in M&A Trans- actions," Working Paper, McMaster Uni- versity, 1993.

Hugh Thomas Assistant Professor of Finance

DeGroote School of Business McMaster University

Hamilton, Ontario Canada

This content downloaded from 185.2.32.109 on Thu, 12 Jun 2014 19:07:27 PMAll use subject to JSTOR Terms and Conditions