Financial institution network and the certification value of bank loans Christophe J. Godlewski UHA & EM Strasbourg Bulat Sanditov Telecom EM AFFI Conference.

Financial institution network and the certification value of bank loansChristophe J. GodlewskiUHA & EM StrasbourgBulat SanditovTelecom EM

AFFI Conference 2015, Cergy-Pontoise

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Take away• Financial institutions network and reputation

• Certification value of bank loans

• European syndicated loans (2001-11)

• Social network analysis + event study methodologies

• Presence of central and reputable lenders increase

borrower’s stock market reaction to a loan announcement

• Stronger effect when informational frictions are important

• Effect vanishes away during severe distruption in the

functioning of financial markets

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Background & motivations• Banks produce private information on borrowers (Diamond

1984…)• Bank loans bear a certification value => AR > 0 for

borrower’s stock around the date of bank loan announcement (James 1987…)

• Maintaining reputation for diligent screening & monitoring => mitigate informational frictions & agency problems

• Syndicated loans market (4.7 trln $, 2014): lead bank reputation is crucial (Ross 2010…)

• Lead bank = structure deal, negotiate loan terms, organize syndicate

• Reputable leader => enhance monitoring, attract participants, signal quality, reduce agency costs…

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Background & motivations (cont.)• Lender reputation trust & reciprocity = critical forms of

social capital (Song 2009) driven by social networks (Cagno & Sciubba 2010)

• Social network features of syndicated lending market = information & capital networks (Baum et al. 2003, 2004)

• Repeated interactions => trust & reciprocity => solve informational frictions => mitigate agency problems• => important for firms seeking external financing

(Brander et al. 202, Wang & Wang 2012)• => affect pricing and structure of bank loan agreements

(Cai 2009, Godlewski et al. 2012, Gatti et al. 2013)

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Aim & contributions• Do banks’ network/reputation affect certification value of

bank loans?

1. Impact of bank network/reputation on certification value

of bank loan => borrower AR / event study methodology

2. Social network metrics (Centrality centrality) to proxy

reputation => richer / comprehensive measure

3. European focus => bank private debt = main source of

external financing for companies

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Empirical design | Data

• Loan and syndicate characteristics : Bloomberg

• Amount, spread, maturity, announcement date…

• Number of lenders, roles (titles)…

• Borrower characteristics : Factset

• Balance sheet & stock market information

• Country characteristics : GFDD (WB) + Djankov et al. (2007)

• European non-financial companies (24 countries)

• January 2001 – June 2011

• 254 companies / 465 loans / 906 lenders

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Empirical design | SNA methodology• Network = collection of nodes & links• Banks’ participation in syndicated loans = affiliation

network• => bipartite network with 2 types of nodes = actors

(banks) linked with events (deals)• Projection of bipartite network• => links between lead and participant banks• => overlapping moving 3 years windows (Baum et al.

2003…)• 3 classifications of leaders:• Mandated arranger or Lead arranger (1)• + Lead manager, Book runner, Book manager… (2)• + Co / Joint, Managers… (3)

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Empirical design | SNA methodology (cont.)

(a)

(b)

1 2 3 4 5 6 7 8 9 10

A B C

Lenders

Loans

11

D

1

2

3

4

5

6

7

8

9

10

11

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Empirical design | SNA methodology (cont.)• Leaders social network metrics => focus on Centrality

centrality• => how well leader is positioned within a network• => control over the flow of information/capital• => interaction, reciprocity, trust => social capital =>

proxy of reputation• Formally = number of the shortest paths between all pairs

of lenders in a network, which pass through a lender, deflated by the number of alternative shortest paths

• Compute average, median and interquartile of Centrality centrality by syndicate• => 3 measures of centrality + 3 classifications of leaders

= 9 measures of network/reputation

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Empirical design | Event study methodology• Multi-event and multi-country setting• Modified market model (Fuller et al. 2002)• Use local-currency national market indexes (Campbell et al.

2010)• Bank loan announcement date = event date (day 0)• Excluding contaminated events• Compute three-day period CAR (-1,1)• Multivariate analysis relies on OLS (robust s.e. clustered at

loan level) :

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Results | (some) Descriptive statistics

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 201102468

101214161820

Year

Perc

enta

ge

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0.0300

avg Betweenness (1) med Betweenness (1) iqr Betweenness (1)

Year

Cent

ralit

y

Loan

sSy

ndic

ate

cent

ralit

y

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Results | (more) Descriptive statisticsVariable Mean SD MedianY = CAR (-1,1) 0.0544 0.0776 -0.0035avg. Centrality (1) 0.0185 0.0133 0.0173med. Centrality (1) 0.0100 0.0144 0.0046iqr. Centrality (1) 0.0224 0.0181 0.0208Loan amount (mln $) 1300.0000 1900.0000 729.0000Maturity (y) 5.5236 3.3988 5.0000Term loan 0.5125 0.4999 1.0000Secured 0.2022 0.4017 0.0000Covenants 0.1639 0.3702 0.0000Syndicate (n) 19.4737 23.0466 13.0000Tranches (n) 2.2484 2.4971 2.0000League table 0.4865 0.4999 0.0000First loan 0.5899 0.4919 1.0000

Loan

var

iabl

esCe

ntra

lity

varia

bles

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Results | (more) Descriptive statisticsVariable Mean SD Median

Rating 0.3287 0.4698 0.0000

Sales (mln $) 12200.0000 24400.0000 5440.0000

Debt ratio 0.3225 0.1741 0.3240

Ebitda margin -1.5600 94.2942 0.1140Stock market 0.9289 0.4273 0.8945

Private credit 1.3470 0.4557 1.2992

French law 0.5297 0.4992 1.0000

German law 0.1405 0.3475 0.0000

Creditor rights 2.1323 1.3658 2.0000

Bank Z score 14.5010 6.6430 13.8325

Bank concentration 0.6806 0.1665 0.6558

Crisis 0.2022 0.4017 0.0000

Coun

try

varia

bles

Borr

ower

va

riabl

es

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Results | Main regression results

Variable avg. Centrality med. Centrality iqr. Centrality1 2 3 4 5 6 7 8 9

Baseline results (loan & syndicate var.)

Centrality 2.0545 2.1096 2.4473 2.3471 2.7250 2.7259 0.3337 -0.0505 -0.6432

With firm characteristics

Centrality 1.0409 0.8847 0.8788 0.4168 0.3827 0.2190 0.2902 0.3967 0.3133

With country characteristics

Centrality 2.8043 2.2539 2.5384 2.5948 2.4133 2.5824 0.9349 -0.4434 -0.8280

OLS regressions, Y = CAR(-1,1), robust s.e. clustered at loan levelControls = loan currency, purpose, year; borrower industry, countryBold coef. = significant at 10% min. (*)

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Results | Interaction terms

Variable Small loan

Short maturity Secured Covenants Small

syndicate League table

avg Centrality (1) 0.6244 2.1705 2.0629 3.8361 -3.9506 3.5214avg. Centrality (1) x Variable 2.2794 -0.4267 -0.0232 -9.8643 6.5792 -3.6920

Variable Low sales Low debt Low

profitavg Centrality (1) -0.2916 0.4310 1.0274avg. Centrality (1) x Variable 1.8076 1.0551 0.0530

VariableLow stock

marketLow private

creditLow bank

z scoreHigh bank

concentrationWeak

creditorrights

Crisis

avg Centrality (1) 2.0932 4.5575 10.0746 3.3854 0.7350 3.2628avg. Centrality (1) x Variable 1.9213 -3.4674 -12.8608 -2.0184 5.1910 -4.3345

Ibid.Interaction variable = dummy (use of sample median for cont. Variables)

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Conclusion• Syndicate centrality / reputation matter for certification

value of bank loans in Europe• Presence of central / reputable leaders increase stock

market reaction (AR) to a loan announcement• Impact on AR reinforced when informational frictions are

important but effect vanishes away during financial crisis of 2008

• Contribution to recent literature on the role of reputation and networks in financial intermediation

• Important for the development of credit markets, especially in Europe

• Limits = potential endogeneity in matching of borrowers and lenders