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11
Balance Sheet Contagion and Systemic Risk in the Euro Area Financial System: a Network
Approach
Olli Castrén and Ilja Kavonius
ECB Workshop “Recent Advances in Modelling Systemic Risk using Network
Analysis” 5 October 2009
22
Outline of the presentation
• Key concepts and literature
• Part I: Accounting-based network of sector-level exposures
• Data issues • Constructing the network • Simulating balance sheet contagion
• Part II: Risk-based balance sheets and transmission of risk
• The contingent claims approach • Calculation of sector level credit risk indicators • Contagion of risk exposures in the risk-based
network
• Discussion and outlook for future work
33
Key concepts
• The role of balance sheet interlinkages, leverage and asset volatility as key financial vulnerabilities at the sector level
• At the macro-level, contagion and shock propagation can take place via balance sheet cross-exposures, as someone’s assets are someone else’s liabilities
• But accounting-based balance sheet say nothing about accumulation and transmission of risk exposures
• For a richer analysis, a framework is needed to move to risk-based balance sheets
44
Some related literature
Theory contributions to analysis of balance sheet linkages • Credit chains and balance sheet contagion
• Kiyotaki and Moore (JPE 1997, AER 2002)• Liquidity shocks and systemic risk
• Brunnermeier and Pedersen (RFS, 2009), Shin (JFI 2008)
Empirical applications: • Aikman et al (BoE WP #372, 2009), plus work at BIS, IMF• Interbank contagion literature • Growing literature on financial networks
Work on risk-based balance sheets • Gray, Merton and Bodie (2007), Gray and Malone (2008)
Main contributions of this paper: apply sector level data to balance sheet networks and to analysis of risk contagion
66
Data issues
• Euro area financial accounts (EAA): Holdings of various financial instruments by the various sectors, both on the asset and the liability sides
• Use 8 main financial instrument categories and 7 sectors (based on the ESA95 classification)
• Quarterly data for the euro area from 1999 Q1
• A closed system (using the rest of the world sector): each financial liability of a sector is an asset for some other sector
• The financial accounts are linked to the real accounts via the net lending/borrowing positions (net financial wealth)
• Non-financial assets (including housing) have no counterparties on the liability side and are not available on a quarterly basis; excluded from this analysis
77
Some illustrations of the EEA data
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
NFCA
NFCL
MFIA
MFIL
OFIA
OFIL
INSA
INSL
GOVA
GOVL
HHA
HH L RoWA
RoWL
Currency and deposits Debt securities
Loans Shares and other equity
Net equity in life insurance and in pension funds Prepayments of insurance premiums
Other accounts
Breakdown of financial instrument holdings by sector, %
-10
-7.5
-5
-2.5
0
2.5
5
7.5
10
12.5
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
NFC MFI OFI INS GOV HH RoW
Evolution of sector-level net financial wealth
88
Constructing the network of exposures
• The data provide instrument-specific total holdings of assets and liabilities by each sector • Can use information on the relative distribution of the sum elements ai,k and lj,k to estimate the individual elements Xi,j for each instrument category => provides the who-to-whom links• We get bilateral linkages for all 8 instrument categories • Works nicely with non-consolidated data
NNNjN
iNiji
Nj
k
xxx
xxx
xxx
X
1
1
1111
N
jkiij ax
1,
N
ikjij lx
1,
99
Constructing the network of exposures
HH ROW
OFI NFC
MFI GOVT
INS
Cross-sector gross balance sheet exposures in the euro area financial system
The key role played by the banking sector
2009 Q1HH ROW
OFI NFC
MFI GOVT
INS
1999 Q1HH ROW
OFI NFC
MFI GOVT
INS
1010
Propagation of shocks in the network
Transmission of a P&L shock to sector A under mark-to-market accounting
Assets Debt Equity
Disinvestment Loss of equity Channels of transmission
…
…
…
Period 0 1 2 3
C
A
B
C
A
B
C
A
B
1111
Propagation of shocks in the network
Example: a cash-flow shock on the NFC sector that corresponds to a 20% loss in shareholder equity
20% NFC cash flow shock
EUR bn% of financial
assets EUR bn% of financial
assets EUR bn% of financial
assets EUR bn% of financial
assets
NFC 783 5.54 632 4.47 541 3.83 652.00 4.61HH 318 3.00 256 2.42 220 2.07 264.67 2.50MFI 189 0.81 152 0.65 130 0.56 157.00 0.67INS 122 1.98 98 1.60 84 1.37 101.33 1.65OFI 405 4.13 327 3.33 280 2.85 337.33 3.44
GOVT 114 3.97 92 3.20 77 2.74 94.33 3.30ROW 278 3.34 224 2.99 192 2.78 231.33 3.04
Average 315.57 3.25 254.43 2.67 217.71 2.31
Round
Average1 2 3
1212
Propagation of shocks in the network
• In a multi-period framework, agents are expected to balance their accounts after the shock
• In the current context, this would amount to asset dis-investment, or a de-leveraging process
• Need to specify rules for: • Target level of leverage • Assets to be shed • The purchasing party • The impact on the asset price
• The framework allows for simulation of such processes once the rules have been defined
1414
The role of risk-based balance sheets
• The accounting-based network neatly illustrates shock transmission in the system but it says nothing about risk exposures and systemic risk •Yet financial crises are typically a result of accumulated vulnerabilities in the form of risk exposures, triggered by sudden bursts of volatility
• To have early warning properties, the framework should include these characteristics • A solution is to construct stochastic risk-based balance sheets which encompass the deterministic accounting-based model
1515
The contingent claims approach to macro-financial risk analysis
• Contingent claims analysis (CCA) measures the expected losses of balance sheet items• Idea: model debt of the sector as a put and equity as a call option, and estimate the market value of assets • The balance sheet of sector i then becomes
Ai= Bi - Pi+ Ji
Ai = market value of assetsBi = book value of debt (distress point)Pi = expected loss on debt (put option)Ji = junior claim (equity, call option)
• The model captures several key financial stability factors: leverage, volatility and non-linearity •By assuming that volatility is zero, the framework collapses to the accounting-based model
1616
Input data
• To estimate the risk-based balance sheets, we need balance sheet data on equity and other liabilities, plus market data on equity volatility, asset returns and interest rates
• Using the techniques developed by Moody’s KMV, market value of assets and asset volatility are estimated at an intermediate stage, once distress points have been estimated
• Equity is measured by shareholder equity plus net financial wealth. Data on equity volatility are implied volatilities of the relevant sector-level stock indices. • For the household and government sector (no equity issued), government bond yield volatility is used
1717
Output: Distance to distress
Households
0
5
10
15
20
25
30
1999Q1 2001Q1 2003Q1 2005Q1 2007Q1 2009Q1
Non-financial firms
0
2
4
6
8
10
12
1999Q1 2001Q1 2003Q1 2005Q1 2007Q1 2009Q1
MFI (banks)
0
2
4
6
8
10
12
14
1999Q1 2001Q1 2003Q1 2005Q1 2007Q1 2009Q1
Government
0
2
4
6
8
10
12
14
16
18
1999Q1 2001Q1 2003Q1 2005Q1 2007Q1 2009Q1
1818
Output: “Network” of pair-wise correlations between sector-level distances-to-distress
2007-2008
HH ROW
OFI NFC
MFI GOVT
INS
1999-2006
HH ROW
OFI NFC
MFI GOVT
INS
Note: The thick link shows correlation between sector-specific distance-to-distress measures that exceeds 0.75, the intermediate link shows correlation between 0.5 and 0.75 and the thin link between 0.25 and 0.5.
1919
Discussion and future work
• Network models applied to the macro level provide new information about sector-level linkages and shock transmission channels
• Can detect important risks and vulnerabilities that might go undiscovered in sector-specific analysis
• Including risk exposures shows how correlations and contagion risk change over time
• Complements the outputs from other models, including those using sector and firm-level information • More work is needed to refine the propagation mechanisms and the CCA balance sheets
2121
Background 1: Output: Market leverage
Non-financial corporations
0.4
0.5
0.6
0.7
0.8
0.9
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
Households
0.1
0.15
0.2
0.25
0.3
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
MFI
0.65
0.66
0.67
0.68
0.69
0.7
0.71
0.72
0.73
0.74
0.75
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
OFI
0.5
0.55
0.6
0.65
0.7
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
INS
0.7
0.75
0.8
0.85
0.9
0.95
1
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
Govt
0.15
0.2
0.25
0.3
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
RoW
0.4
0.45
0.5
0.55
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
0
0.2
0.4
0.6
0.8
1
1999Q1 2000Q3 2002Q1 2003Q3 2005Q1 2006Q3 2008Q1
NFC HHMFI OFIINS GOVTROW
2222
Background 2: Output: Asset volatility
Non-financial corporations
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
Households
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
MFI
0
0.01
0.02
0.03
0.04
0.05
0.06
1999Q1 2000Q3 2002Q1 2003Q3 2005Q1 2006Q3 2008Q1
OFI
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
Insurance
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
1999Q1 2000Q3 2002Q1 2003Q3 2005Q1 2006Q3 2008Q1
Government
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0.045
0.05
1999Q1 2000Q3 2002Q1 2003Q3 2005Q1 2006Q3 2008Q1
Rest of the world
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
1999Q1 2000Q2 2001Q3 2002Q4 2004Q1 2005Q2 2006Q3 2007Q4
NFC HH MFI OFI INS GOVT ROW
2323
Background 3: Use of networks for broader financial stability analysis
HH ROW
OFI NFC
MFI GOVT
INS
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Assets Liabilit ies
Currency Deposits Debt securit ies
Short -term loans Long-term loans Shares and other equity
Other accounts
How the dislocation of a bank’s balance sheet can spread
Bank A
i) interbankmarket
ii) sectors
iii) countries
Fir
m-l
evel
data
Macro
-fi
nan
cia
l
2424
Background 4: The structure of integrated accounts
Uses Resources
A B
D E
I
K=I*J+G G H
J
Other changes
Assets Liabilities
M N
O=R*S+M P=T*U+N
R S T U
Stock in period t-1 Other changes Stock in period t-1 Other changes
All the received (credit) transactions of financial accounts
Financial accounts
Net wealth
O-P=Q
Non-financial accounts
All the paid transactions of the use of disposable income account
All the received transactions of the use of disposable income account
C-D+E=F
Capital stock in period t
Capital stock in period t-1
All the paid transactions from the production account to the secondary distribution of income account
All the paid transactions of the capital account
All the received transactions from the production account to the secondary distribution of income
account
B-A=C
Disposable income
Liablity stock in period t
M-N=L
All the received transactions of the capital account
Domestic economy/an invidual sector
All the paid (debit) transactions of financial accounts
Asset stock in period t
Net lending/borrowing
F-G+H=L
Saving