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Financial Network Analysis and Visualisation
Kimmo SoramäkiInes Salpico Soramäki
Norges Bank, 30th March 2010
2003 20042003
Growing interest in networks
“... need for new and fundamental understanding of the structure and dynamics of economic networks.”
“Meltdown modeling -Could agent-based computer models prevent another financial crisis?”
“Is network theory the best hope for regulating systemic risk?”
CFA Magazine, July 2009 Nature, August 2009 Science, July 2009
... given the fragile condition of the financial markets at the time, the prominent position of Bear Stearns in those markets, and the expected contagion that would result from the immediate failure of Bear Stearns, the best alternative available was to provide temporary emergency financing to Bear Stearns ...
Minutes of the Board of Governors of the Federal Reserve System, 14 March 2008
It was the ultra-interconnectedness of the nation’s financial institutions that posed the biggest risk of all [...] every firm was now dependent on the others – and many didn’t even know it. If one fell, it could become a series of falling dominoes.
“Too Big to Fail”, Andrew Ross Sorkin 2009
We are talking about systemic risk ≠ systematic risk
• The risk of disruption to a financial entity with spillovers to the real economy
• Risk of a crisis that stresses key intermediation markets and leads to their breakdown, which impacts the broader economy and requires government intervention
• Risk that critical nodes of a financial network cease to function as designed, disrupting linkages
-> some chain of events that starts or gets magnified in the finance sector and makes us all worse off
News articles mentioning “systemic risk”, Source: trends.google.com
“Too big to fail”
“Too interconnected to fail”
+
Federal funds
Bech, M.L. and Atalay, E. (2008), “The Topology of
the Federal Funds Market”. ECB Working Paper No. 986.Iori G, G de Masi, O Precup, G Gabbi and G Caldarelli (2008):
“A network analysis of the Italian overnight money market”,
Journal of Economic Dynamics and Control, vol. 32(1), pages
259-278
Italian money market
Overnight lending networks
Soramaki, K, M.L. Bech, J. Arnold, R.J. Glass and W.E. Beyeler (2007), “The topology of interbank
payment flows”, Physica A, Vol. 379, pp 317-333, 2007.
Payment flows in Fedwire
NETWORK
THEORY
Financial
Network
Analysis
Biological
Network
Analysis
Graph & Matrix
Theory
Social Network
Analysis
Network
Science
Computer
Science
Network theory and related fields
Network terminology– node/vertex
– link/tie/edge/arc
– directed vs undirected
– weighed vs unweighted
– graph + properties = network
Algorithms/measures– Centrality
– Flow
– Community/pattern identification
– Distance, shortest paths
– Connectivity, clustering
– Cascades, epidemic spreading
-> Financial interlinkages, bilateral positions, exposures
-> Systemic importantance
-> Liquidity
-> Contagion
4
1
2
3
-> Bank/banking group
“Homophily”– “Birds of one feather flock together”, “herd
behaviour”– Ideas, attributes, etc tend to cluster together
and enforce each other– Examples: Some obvious (age, social status),
others less (obesity, happiness, divorces) – How about: risk appetite, portfolio decisions,
etc.
“Small world phenomenon”– “Six degrees of separation” (6.6 on MSN
messenger)– The shortest path between any two nodes is
very short– Implications for contagion?
“Robust yet fragile“, “Scale-free networks”– “The removal of "small" nodes does not
alter the path structure of the remaining nodes, and thus has no impact on the overall network topology. “
Degree (log)
Pro
ba
bilit
y (
log
)
Fedwire degree distribution
Spread of obesity
Nicholas A. Christakis, James H. Fowler
New England Journal of Medicine 357 (4): 370–
379 (26 July 2007)
• The properties and behaviour of a node cannot be analysed on the basis its own properties and behaviour alone.
Main premise of network analysis: Structure of links between nodes matters
• To understand the behaviour of one node, one must analyse the behaviour of nodes that may be several links apart in the network.
• Bottom up approach. Generalize and describe.
• Financial context: network of interconnected balance sheets
• Should we let the next Lehman fail?
Degree: number of links
Closeness: distance to other nodes via shortest paths
Betweenness: number of shortest paths going through the node
Eigenvector: nodes that are linked by/toother important nodes are more central
Markov: probability that a randomprocess is at a given node
Systemic importance = “centrality”
Centrality depends on network process
Trajectory: geodesic paths, paths, trails or walks
Transmission: parallel/serial duplication or transfer
Source: Borgatti (2004)
The road ahead
• We need better models of systemic risk and
contagion
• We will have much more frequent and granular
data
• We need better tools that can run the new
models with the new data
• Open source project with a commercial option
• Sponsored byNorges BankEuropean Central BankBank of England
• Version 2.0 will be released in April.
Objective of FNA
• Provide a tool for time series analysis of network data in finance
• Tool for data visualization and exploration
• Platform for building simulation models
• Make available advances in research to policy
The big picture
Additional interfaces for humans and machines
Charts and network layouts
Graph database
Generate
Algorithms
Operate Extract EditCascading
failures
Algorithms Explore
Run-time visualization
Statistics
Network analysis Simulation models Transaction analysis
Visual explorer
Payment simulation
File input/output
Transaction database
File input/output File input/output
Client – server architecture
Visualization
Concept: Visual Representation of information, data and/or knowledge
Information Visualization:
Concept: Visual Representation of information, data and/or knowledge
> Interaction Design > Data Analysis > Graphic Rendering
Visualization
> Representation: Qualitative vs. Quantitative
> Focus: Message vs. Data
> Exploration: Limited vs. Unlimited
Infographics vs. Analytical Visualizations
Europe's Web of DebtBill Marsh/The New York Times Visual
Science Series , May 1, 2010
Visualization
Data - demand for a new understanding
Connected (networks), dynamic, constantly updated, interactive
> Cross-referenced reading
> Implications on Representation
> Cross-referenced reading
> Implications on Representation
> Implications on Policy
Visualization
http://data.gov.uk/
http://www.data.gov/http://www.datamasher.org/
Visualization
New paradigm:
> Qualitative and Quantitative
> Static Output and Explorable Interface
Infographical and Analytical
See blog post:
http://www.financialnetworkanalyzer.com/2011/02/
06/developing-fna-2-0-visualization-tools/
Visualization
FNA - GoalDevelop a tool that integrates
> Data analysis
> Data exploration
> Infographical and Analytical visualization
