Invited talk on Network Approaches for Interbank Markets -research conference in Castellon, Spain.

1. Network Approaches for
Interbank Markets
Invited Talk
Dr. Kimmo Soramäki
Founder and CEO
FNA, www.fna.fi
University Jaume I of Castellon, the University of Kiel, and the Kiel Institute
for the World Economy
Castellon, Spain
30 May 2013

2. Systemic risk
Search volume for “systemic risk” in the US, Source: trends.google.com
2
Entered the common vocabulary with the 2008- financial crisis
Is largely understood as an issue for the financial system
Important for regulators, Chief Risk Officers, Enterprise Risk
Managament, ...

3. Systemic risk
Not clearly defined. De Bandt and Hartmann
(2000) provides an early survey.
Here: "The risk that a system composed of many
interacting parts fails due to a shock to some of its
parts" - complex systems approach
In Finance, the risk that a disturbance in the
financial system propagates and makes the system
unable to perform its function – i.e. allocate
capital efficiently
Domino effects, cascading failures, financial
interlinkages, … -> i.e. a process in the
financial network 3
Not:

4. Dragon King
(Sornette 2009)
Black Swan
(Taleb 2001, 2007)
vs.

5. Network Theory is applied widely
Main premise of network theory:
Structure of links between nodes
matters
Large empirical networks are
generally very sparse
Network analysis is not an
alternative to other analysis
methods
Network aspect is an unexplored
dimension of ANY data
5

6. 6
For example:
Entities:
100 banks
Variables:
Balance sheet items
Time:
Quarterly data since 2011
Links:
Interbank exposures
Information on the links
allows us to develop better
models for banks' balance
sheets in times of stress
Networks brings us beyond the Data Cube
" The Tesseract"

7. What does this mean? (Agenda)
• Lots of empirical analysis is needed - 'You can't
manage what you can't measure'
• New models are needed that take into account
interconnectedness and network contagion
• Tools and methods need to be developed that
can conveniently hande all four dimensions
(especially visualization)

8. Empirics

9. First empirics Fedwire Interbank Payment
Network, Fall 2001
Around 8000 banks, 66 banks
comprise 75% of value,25 banks
completely connected
Similar to other socio-
technological networks
Soramäki, Bech, Beyeler, Glass and Arnold (2007),
Physica A, Vol. 379, pp 317-333.
See: www.fna.fi/papers/physa2007sbagb.pdf 9
M. Boss, H. Elsinger, M. Summer, S. Thurner, The
network topology of the interbank market, Santa
Fe Institute Working Paper 03-
10-054, 2003.

10. Extremely
big banks are
more likely
to occur
than the
power law
would
suggest ->
Dragon King
Interbank data generation model available in FNA (Soramaki-Cook 2013)

11. Most central banks have now mapped their
interbank payment systems
11
Agnes Lubloy (2006). Topology of the Hungarian
large-value transfer system. Magyar Nemzeti Bank
Occasional Papers
Embree and Roberts (2009). Network
Analysis and Canada's Large Value Transfer
SystemBoC Discussion Paper 2009-13
Becher, Millard and Soramäki (2008).
The network topology of CHAPS
Sterling. BoE Working Paper No. 355.

12. Example: Oversight Monitor
12
(network is fictional)
http://www.fna.fi/solutions/oversight-monitor

13. Models

14. Degree: number of links
Closeness: distance from/to other
nodes via shortest paths
Betweenness: number of shortest
paths going through the node
Eigenvector: nodes that are linked by
other important nodes are more central,
probability of a random process
Common centrality metrics
Centrality aims to summarize some notion of importance.
Operationalizing the concept is more challenging.

15. Centrality Measures for
Financial Systems
Recently developed financial system
specific metrics:
• Core-Periphery
– Craig and von Peter 2010, Optimal
classification that matches theoritical
core-periphery model
• DebtRank
– Battiston et al, Science Reports 2012,
Cascading failures -model
• SinkRank
– Soramäki and Cook, Kiel Economics
DP, 2012, Absorbing Markov chains
15
World's Ocean Currents
NASA Scientific Visualization Studio

16. Centrality depends on network
process
• Trajectory
– Geodesic paths (shortest paths)
– Any path (visit a given node once)
– Trails (visit a given link once)
– Walks (free movement)
• Transmission
– Parallel duplication
– Serial duplication
– Transfer
Borgatti (2005). Centrality and network flow .
Social Networks 27, pp. 55–71.

17. Systemic Risk in Payment Systems
• Credit risk has been virtually eliminated by system design (real-time
gross settlement)
• Liquidity risk remains
– “Congestion”
– “Liquidity Dislocation”
• Trigger may be
– Operational/IT event
– Liquidity event
– Solvency event
• Time scale is intraday, spillovers possible

18. SinkRank: Distance to Sink
From B
From C
1
2
1
To A
From A
From C
To B
From A
From B
To C
• Soramaki and Cook (2012)
• Markov chains are well-suited to model transfers along walks
• Payments can be modelled as a ramdon walk in the network. We can
calculate the following 'random walk distances':
(100%)
(100%)
(33.3%)
(66.6%)

19. SinkRank
• SinkRank is the average distance
to a node via (weighted) walks
from other nodes
• We need an assumption on the
distribution of liquidity in the
network at time of failure
– Assume uniform ->
unweighted average
– Estimate distribution -> PageRank -
weighted average
– Use real distribution ->
Real distribution are used as weights
SinkRanks on unweighted
networks

20. Payment System Simulation
http://www.fna.fi/solutions/payment-simulator

21. Tools - FNA

25. • Complete documentation with
tutorials and sample scripts
• >200 commands
• Web version & REST API is
free for academic research
• Ongoing collaboration with
several universities

26. Priorities for a Research Agenda

27. Priorities for the Research Agenda
1. Measuring and mapping interconnectedness (network
structure), modelling contagion (network process) and
understanding their interplay

28. 28
Bank projection
Asset projection
Example: Bank-Asset graphs and
projections
Network of bank's asset
interdependencies

29. Priorities for the Research Agenda
1. Measuring and mapping interconnectedness (network
structure), modelling contagion (network process) and
understanding their interplay
2. Developing metrics of systemic importance and early
warning indicators for continuous monitoring of the
financial system

30. Priorities for the Research Agenda
1. Measuring and mapping interconnectedness (network
structure), modelling contagion (network process) and
understanding their interplay
2. Developing metrics of systemic importance and early
warning indicators for continuous monitoring of the
financial system
3. Development of network visualization techniques

31. Financial Cartography
Interactive version: http://www.fna.fi/demos/erm/correlation-tree.html

32. Blog, Library and Demos at www.fna.fi
Dr. Kimmo Soramäki
kimmo@soramaki.net
Twitter: soramaki