Bank Distress During the Credit Crisis:Contagion, or Common Shocks?

Mark Mink

Discussion by Nadia MassoudNorges Bank finstab-conference 2010

Main Objective of the paper

To disentangle the impact of contagion and common shocks on banking sector stability during the credit crisis of 2007-2009.

The underlying presumption is that a default of one bank would cause other banks to suffer losses as well; contagion hypothesis, an increase in a bank's

default probability should lead to a decline in the other banks' stock market valuations.

Main findings

A change in one bank's default probability or CDS-spread hardly affects the market's valuation of any other banks.

This finding implies that correlated declines in banks' asset values during the credit crisis were mainly due to common shocks affecting the banking sector as a whole, and were only to a very small amount driven by interbank contagion.

Methodology

Proposed contagion model

Where M indicates a market factor excluding any contagion effects. M is hard to observe and propose this model

Methodology: Concerns

Probability of default is assessed based on changes in the value of the assets of the banks

Contagion effects is more relevant when the default event is unexpected

There are many defaulting event that can be accounted for in the model

The history of US bank failures

Year

Number of Bank Failures Year

Number of Bank Failures Year

Number of Bank Failures

2009 140 1999 8 1989 534

2008 30 1998 3 1988 470

2007 3 1997 1 1987 262

2006 0 1996 6 1986 204

2005 0 1995 8 1985 180

2004 4 1994 15 1984 106

2003 3 1993 50 1983 99

2002 11 1992 181 1982 119

2001 4 1991 271 1981 40

2000 7 1990 382 1980 22

Another Approach

To determine whether bank failures have a contagion effect:

1. Detect any contagion effect of banks that ultimately failed.

2. Define unanticipated unfavorable information has a contagion effect.

3. Examine any abnormal performance of various bank portfolios at the time of those events.

Sample

The paper use data on banks' market value between January 1st 2007 and December 31st 2009 obtained from Thomspon Datastream.

The Sample includes the 96 banks: 26 US Banks 60 are from countries in the European

Union.

Sample, Cont’d

Sample size is very small Representative sample Power of the test especially for conducting

tests within groups

Sample selection bias, it only includes relatively large bank with market data

Contagion effect might be more severe for smaller banks

Sample, Cont’d

Contagion might be more severe for banks operating in the same region/country since banks may interact with each other much more.