DebtRank: Too Central to Fail?
Transcript of DebtRank: Too Central to Fail?
Chair of Systems Design www.sg.ethz.ch
DebtRank: Too Central to Fail?
Stefano BattistonCoupled Climate-Economics Modelling and Data Analysis, ENS Paris
November 23, 2012
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail?
Acknowledgments
1 ETH Chair of Systems Design; OTC - Swiss National Fund
2 FOC - Forecasting Financial Crisis (FET-OPEN)www.focproject.net
3 INET - Systemic Risk Task Force
4 R. Kaushik, M. Puliga, M. Tasca, S. Vitali, J. Glattfelder, F.Schweitzer (ETH Zurich), G. Caldarelli (IMT Lucca),
5 J. Stiglitz and B. Greenwald (Columbia Univ.)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 2 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Introduction
Financial Crises and Financial Networks
1 We live in an interconnected global economy
2 Benefits but also major threats
Systemic crises
1 large social and economiccosts
2 can emerge endogenously,without external shocks
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 3 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Financial Networks and Systemic Risk
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 4 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Financial Networks and Systemic Risk
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 5 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Financial Networks and Systemic Risk
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 6 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Financial Networks and Systemic Risk
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 7 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Interacting Networks and Systemic Risk
General Vision
1 Links or varying nature
2 Frictions: feedback loops and amplifications
3 Individual Risk VS Global risk:
1 emerging properties2 often unexpected3 socially desirable? The role of regulation.
Research Questions as in the following slides:
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 8 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
RQ: Empirical: Topological Structure
Bow-tie, core-peripheryHeterogeneity, extreme concentra-tion
Cross-country, all firms[Glattfelder, Battiston 2009 PRE]
Global, TNC (e.g. financial)[Vitali, Glattfelder, Battiston 2011 PLOS-ONE]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 9 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
RQ: Empirical: Interdependence
Empirical analysis of FEDemergency loans data. DebtRank[Puliga, Battiston, Kaushik, Tasca, Caldarelli (2012) Sci.
Rep. 2: 451]
Pearson, Tail-Correlation and Jointdraw-up probability in CDS’s andbonds[Kaushik, Battiston, http://arxiv.org/abs/1205.0976]
[Puliga, Battiston, Kaushik, Caldarelli, Veredas (2012) in
progress ]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 10 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
RQ: Models of Distress and Defaults
Amplifications and feedbacks:Trade-off: Liaisons can be dangerous
Default Propagation (w/woliquidity)
Distress Propagation -Time-to-Default
[Battiston, Delli Gatti, Gallegati, Stiglitz, Greenwald, 2012 JEDC,
2012 JFS]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 11 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Q4: Models of Procyclicality of Leverage
Bank-bank + bank-assetnetwork, time to default
Positive feedback: leverage -asset price
Roles of: (1) connectivity, (2)capital requirements, (3) pricereaction
[Tasca, Battiston 2011 WP ECSS, 2012 WP ETH Risk
Center]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 12 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Models of Efficiency vs Stability
Incentive to form Links:
Stable networks are notefficient
Tension: Individual profitvs social welfare.
[Koenig, Battiston, Napoletano, Schweitzer,
2011 JEBO, 2012 GEB]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 13 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Empirical examples
SOCIET ELETTRICA
INVESTOR AB
CAPITAL GROUP COMPANIES INC,
ANDRE HOFFMAN AND ANDREA
ABB LTD
SCHWEIZERISCHE
NORTRUST NOMINEES LIMITED
NOVARTIS FOUNDATION FOR EMPLOYEE PARTICIPATION
BZ GRUPPE HOLDING
CANTON OF SAINT GALL
SYNGENTA AG
FRANKLIN RESOURCES, INC.
JP MORGAN CHASE BANK, NA
ADECCO SA
PARGESA HOLDING SA
BRANDES
KUEHNE UND NAGEL INTERNATIONAL AG
PUTNAM INVESTMENT MANAGEMENT INC
CREDIT SUISSE GROUP
ST. GALLER KANTONALBANK
FIDELITY INVESTMENTS LIMITED
CHASE NOMINEES LIMITED
HOLCIM LTD.
AXA
COMPAGNIE FINANCIERE RICHEMONT
ROCHE HOLDING AG
PARJOINTCO NV
ALLIANZ AKTIENGESELLSCHAFT
MFS INVESTMENT MANA
EMASAN AG
SWISS REINSURANCE COMPANY
DR. H.C. THOMAS SCHMIDHEINY
ZURICH FINANCIAL
SWISSCOM AG
NESTLE S.A.
SONATA SECURITIES SA
UBS AG
THE DEPOSITORY
NOVARTIS AG
KUEHNE KLAUS-MICHAEL
NEUE AARGA
Zurich Stock Market: ownership network and its backbone1.
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 14 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Empirical examples
UK (left) and US (NYSE) (right) stock market networks2.
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 15 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Empirical Examples
China (left) and Japan (right) stock market networks
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 16 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
The financial core of the TNC network
Ownership network around TNC worldwide Left: The core ( 1300nodes). (Right) An example of few top financial institutions involvedin many cycles. [Vitali ea., PLoS-ONE 2011]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 17 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Political Economy and the Art of Pipe Plumbing
Distress propagation: key issue for the stability of financial systems
direct channel: balance sheet interlock (unipartite graph)indirect channel: common asset (bipartite graph)
“Plumbing” aspects
improving stress-test techniques utilized at central banks to designfinancial system more robust to endo/exo shocks
Political economy aspects
distorsion of incentives leading to e.g. excessive risk takingeconomic concentration, influence on enforcement of existing policiesand design of new policies
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 18 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Political Economy and the Art of Pipe Plumbing
Distress propagation: key issue for the stability of financial systems
direct channel: balance sheet interlock (unipartite graph)indirect channel: common asset (bipartite graph)
“Plumbing” aspects
improving stress-test techniques utilized at central banks to designfinancial system more robust to endo/exo shocks
Political economy aspects
distorsion of incentives leading to e.g. excessive risk takingeconomic concentration, influence on enforcement of existing policiesand design of new policies
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 18 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Political Economy and the Art of Pipe Plumbing
Distress propagation: key issue for the stability of financial systems
direct channel: balance sheet interlock (unipartite graph)indirect channel: common asset (bipartite graph)
“Plumbing” aspects
improving stress-test techniques utilized at central banks to designfinancial system more robust to endo/exo shocks
Political economy aspects
distorsion of incentives leading to e.g. excessive risk takingeconomic concentration, influence on enforcement of existing policiesand design of new policies
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 18 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
Political Economy and the Art of Pipe Plumbing
Distress propagation: key issue for the stability of financial systems
direct channel: balance sheet interlock (unipartite graph)indirect channel: common asset (bipartite graph)
“Plumbing” aspects
improving stress-test techniques utilized at central banks to designfinancial system more robust to endo/exo shocks
Political economy aspects
distorsion of incentives leading to e.g. excessive risk takingeconomic concentration, influence on enforcement of existing policiesand design of new policies
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 18 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
From Too-Big-to-Fail to Too-Central-to-Fail
Too-big-to-fail: balance sheet size
Too-connected-to-fail: number of financial inter-linkages
Too-correlated-to-fail: similar portfolios and/or strategies
Too-central-to-fail: impacting those who are important via networkeffects
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 19 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
From Too-Big-to-Fail to Too-Central-to-Fail
Too-big-to-fail: balance sheet size
Too-connected-to-fail: number of financial inter-linkages
Too-correlated-to-fail: similar portfolios and/or strategies
Too-central-to-fail: impacting those who are important via networkeffects
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 19 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
From Too-Big-to-Fail to Too-Central-to-Fail
Too-big-to-fail: balance sheet size
Too-connected-to-fail: number of financial inter-linkages
Too-correlated-to-fail: similar portfolios and/or strategies
Too-central-to-fail: impacting those who are important via networkeffects
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 19 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Financial Networks
From Too-Big-to-Fail to Too-Central-to-Fail
Too-big-to-fail: balance sheet size
Too-connected-to-fail: number of financial inter-linkages
Too-correlated-to-fail: similar portfolios and/or strategies
Too-central-to-fail: impacting those who are important via networkeffects
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 19 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Balance Sheet Structure
Fundamental identity: Assets = Liabilities + Equity
Equity < 0 implies default
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 20 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Balance Sheet Structure
Fundamental identity: Assets = Liabilities + Equity
Equity < 0 implies default
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 20 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Default Cascade
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 21 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Default Cascade
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 21 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Default Cascade
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 21 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Default Cascade
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 21 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Devaluation Effect
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 22 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Devaluation Effect
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 22 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Devaluation Effect
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 22 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Devaluation Effect
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 22 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Distress Propagation: DebtRank
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 23 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Distress Propagation: DebtRank
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 23 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Distress Propagation: DebtRank
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 23 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Shock to a Common External Asset
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 24 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Shock to a Common External Asset
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 24 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? Network Effects
Shock to a Common External Asset
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 24 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
DebRank is a novel indicator to identify
SIFI (Systemically Important Financial Institutions)groups of SIFI
Propagation of distress from an institution to another is a key issuefor the stability of financial systems.
Propagation channels
direct: balance sheet interlock (unipartite graph)indirect: common asset (bipartite graph)
DebtRank overcomes some limitations in
standard stress-test techniques at central banksstandard complex network mesures (e.g. betweenness, centrality etc.)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 25 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
DebRank is a novel indicator to identify
SIFI
(Systemically Important Financial Institutions)groups of SIFI
Propagation of distress from an institution to another is a key issuefor the stability of financial systems.
Propagation channels
direct: balance sheet interlock (unipartite graph)indirect: common asset (bipartite graph)
DebtRank overcomes some limitations in
standard stress-test techniques at central banksstandard complex network mesures (e.g. betweenness, centrality etc.)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 25 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
DebRank is a novel indicator to identify
SIFI (Systemically Important Financial Institutions)groups of SIFI
Propagation of distress from an institution to another is a key issuefor the stability of financial systems.
Propagation channels
direct: balance sheet interlock (unipartite graph)indirect: common asset (bipartite graph)
DebtRank overcomes some limitations in
standard stress-test techniques at central banksstandard complex network mesures (e.g. betweenness, centrality etc.)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 25 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
DebRank is a novel indicator to identify
SIFI (Systemically Important Financial Institutions)groups of SIFI
Propagation of distress from an institution to another is a key issuefor the stability of financial systems.
Propagation channels
direct: balance sheet interlock (unipartite graph)indirect: common asset (bipartite graph)
DebtRank overcomes some limitations in
standard stress-test techniques at central banksstandard complex network mesures (e.g. betweenness, centrality etc.)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 25 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
DebRank is a novel indicator to identify
SIFI (Systemically Important Financial Institutions)groups of SIFI
Propagation of distress from an institution to another is a key issuefor the stability of financial systems.
Propagation channels
direct: balance sheet interlock (unipartite graph)indirect: common asset (bipartite graph)
DebtRank overcomes some limitations in
standard stress-test techniques at central banksstandard complex network mesures (e.g. betweenness, centrality etc.)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 25 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
DebRank is a novel indicator to identify
SIFI (Systemically Important Financial Institutions)groups of SIFI
Propagation of distress from an institution to another is a key issuefor the stability of financial systems.
Propagation channels
direct: balance sheet interlock (unipartite graph)indirect: common asset (bipartite graph)
DebtRank overcomes some limitations in
standard stress-test techniques at central banksstandard complex network mesures (e.g. betweenness, centrality etc.)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 25 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
more central = moresystemically important
not just a ranking
systemic economic loss(e.g., euros) due to distresson one or more nodes
extension/adaptation tosocial/biological contagion?
[Battiston, Puliga, Kaushik, Tasca, Caldarelli, DebtRank:Too-central-to-fail? (2012) Sci Rep. 2:541]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 26 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
more central = moresystemically important
not just a ranking
systemic economic loss(e.g., euros) due to distresson one or more nodes
extension/adaptation tosocial/biological contagion?
[Battiston, Puliga, Kaushik, Tasca, Caldarelli, DebtRank:Too-central-to-fail? (2012) Sci Rep. 2:541]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 26 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
DebtRank
more central = moresystemically important
not just a ranking
systemic economic loss(e.g., euros) due to distresson one or more nodes
extension/adaptation tosocial/biological contagion?
[Battiston, Puliga, Kaushik, Tasca, Caldarelli, DebtRank:Too-central-to-fail? (2012) Sci Rep. 2:541]
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 26 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Impact Matrix and Debtrank definition
exposure of i to j , Aij (e.g. lending, bond, stock shares).core capital of i , Ei .
1 Relative exposure of i to j , w.r.t. total exposure,Aij∑j Aij
, is generally
small (sum up to 1)
2 Relative exposure of i to j , w.r.t. core capital: Zij =Aij
Ei, (sum can
easily exceed 1)
Direct Impact of i on j defined as the exposure that j has towardsi : Wij = Zji , W = ZT
DebtRank: A node i is more central if it impacts strongly (largeWij) many other central nodes: recursive!Each node propagates its distress only once (we tamereverberations)all formulas at doi:10.1038/srep00541widgets and infographics at:http://ethz.focproject.net:8080/widgetCoupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 27 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Inspired by Network Centrality
Adapting notion of Feedback Centrality to financial distress: a nodeis more important if it impacts on many high value and importantnodes
ci =∑j
Wijvj +∑j
Wijcj
c = (I −W )−1Wv
where v = e.g. total asset
Issues: need λ(W ) < 1, but imposing row-stochasticity we couldnot compare values across time
Strategy: keep impact matrix as is and tame cycles by excludingwalks already visited
Result: we obtain not just a ranking but an estimate of fraction oftotal economic value in distress
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 28 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Debt Rank Dynamics
A node i is more central if it impacts strongly (large Wij) manyother central nodes: recursive!
Each node propagate its distress only once (we tamereverberations).
hi (t) = min
{1, hi (t − 1) +
∑j
Wjihj(t − 1)
}, where j | sj(t − 1) = D
si (t) =
D if hi (t) > 0 & si (t − 1) 6= II if hi (t − 1) > 0U otherwise,
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 29 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Applications: SIFI
In several countries, Central Banks maintain a database of:
Balance sheet interlocking exposures between banksExposures to external assetsCore capital
Build the impact matrix under various scenarios possibly taking intoaccount market values
Run DebtRank and GroupDebtRank to assess systemic impact ofone or more institutions
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 30 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Applications: Counterparty Risk
Investors usually do not know the mutual exposures amongcounterparties. However,
One can generate an ensemble of viable networks of exposuresusing available information
Run DebtRank and GroupDebtRank on each network of theensemble
Obtain distribution of losses across counterparties, conditional to agiven shock
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 31 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Application: an exercise on FED data + BvDdata
Take banks’ investment in each others equity share as a proxy of allexposures
Focus on the largest borrowers from the FED in 2008-2010
22 inst., peak lending 1.2 USD trillions, total assets 20 USD trillions)
Incorporate dynamics of core capital (take market capitalization asa proxy of core capital)
Recipe
1 market capitalization as proxy of core capital
2 investments in equity as proxy of financial exposures
3 rescaling factor α, conservative scenario: in good the times everybank can sustain the default of at least 5 counterparties
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 32 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Application: an exercise on FED data + BvDdata
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 33 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Application: an exercise on FED data + BvDdata
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 33 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Debt Rank vs other Measures
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Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 34 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Debt Rank vs other Measures
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Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 34 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Debt Rank vs other Measures
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Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 34 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Debt Rank vs other Measures
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Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 34 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Group DebtRank
Recipe
1 A selected group of institutions is hit by a shock: for each a certainfraction φi < 1 of equity vanishes
2 Propagate distress according to impact matrix as before (closedwalks traversed only once)
3 Test various values of φ and impact scaling factor α
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 35 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
GroupDebtRank
100 200 300 400 500 600 700 800 900 10000
0.2
0.4
0.6
0.8
1G
roup D
ebtR
ank
100 200 300 400 500 600 700 800 900 1000
40
60
80
Avg. M
ark
et C
ap. (U
SD
bill
ion)
Time(Days)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 36 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
GroupDebtRank
100 200 300 400 500 600 700 800 900 10000
0.2
0.4
0.6
0.8
1G
roup D
ebtR
ank
100 200 300 400 500 600 700 800 900 1000
40
60
80
Avg. M
ark
et C
ap. (U
SD
bill
ion)
Time(Days)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 36 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Conclusions
Network effects matter for distress propagation: SIFI andcounterparty risk
DebtRank is a centrality-inspired algorithm to assess SIFI innetwork context, overcoming some limitations of state-of-the-artstress-testing
From Too-Big-to-Fail to Too-Central-to-Fail
Currently: a new method to evaluating VAR and ES in a networkcontext
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 37 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Financial Networks: a research agenda
1 Empirics: network structure
2 Link formation: evolution to stable/efficient structures
3 Node dynamics: propagation (e.g., information, distress)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 38 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Financial Networks: a research agenda
1 Empirics: network structure
2 Link formation: evolution to stable/efficient structures
3 Node dynamics: propagation (e.g., information, distress)
Meta-level
1 Feedback from structure onto incentives: political economy aspect
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 38 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Financial Networks: a research agenda
Financial networks
1 Topology, Link formation, Node dynamics:e.g., FOC, various INET grants
2 Interacting networks: MULTIPLEX
3 Feedback from structure onto incentives:INET TaskForce on Systemic Risk (Stiglitz) - Working Group onFinancial Interlinkages (Haldane, Battiston)
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 39 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
The FOC Project
Forecasting Financial Crises (FOC)
European project funded by FET-OPEN
13 partners (including ECB), coordinated by Guido Caldarelli atIMT Lucca
Information:www.focproject.netwidgets: http://ethz.focproject.net:8080/
Related events
FOC-CRISIS School on Complex Financial Networks, IMT Lucca,October 24-27 2012
INET Conference False Dichotomies, Waterloo, November 15-172012
NetSci 2013
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 40 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
Debt Rank Dynamics
Centrality computation plus contraints on walks is equivalent tofollowing algorithm.
continuous variable hi ∈ [0, 1].
3 possible states, undistressed, distressed, inactive: si ∈ {U, D, I}.Sf : set of nodes in distress at time 1. hi (1) = ψ ∀i ∈ Sf ;hi (1) = 0∀i /∈ Sf , and si (1) = D , ∀i ∈ Sf ; si (1) = U ∀i /∈ Sf .
hi (t) = min
{1, hi (t − 1) +
∑j
Wjihj(t − 1)
}, where j | sj(t − 1) = D
si (t) =
D if hi (t) > 0 & si (t − 1) 6= II if hi (t − 1) > 0U otherwise,
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 41 / 41
Stefano Battiston Chair of Systems Design www.sg.ethz.chDebtRank: Too-Central-to-Fail? DebtRank
43
1
2
65
7 8
h=1
h=0
h=0
h=0
h=0 h=0
h=0 h=0
43
1
2
65
7 8
h=1
h=0.5
h=0.5
h=0.5
h=0 h=0
h=0 h=0
43
1
2
65
7 8
h=1
h=0.5
h=0.5
h=0.5
h=0.25 h=0.25
h=0 h=0
43
1
2
65
7 8
h=1
h=0.5+
0.125
h=0.5
h=0.5
h=0.25+
0.125
h=0.25
h=0.125 h=0.125
43
1
2
65
7 8
h=1
h=0.5+
0.125
h=0.5
h=0.5
h=0.25+
0.125
h=0.25
h=0.125 h=0.125
Coupled Climate-Economics Modelling and Data Analysis, ENS Paris November 23, 2012 42 / 41