Financial Cartography at Bogazici UniversityKimmo Soramaki
As the financial system becomes more complex, new methods to understand its inherent risks and dynamics are needed. Kimmo Soramäki will discuss how network analysis of large‐scale financial transaction data can be used to improve our understanding systemic risk. He will also show case studies how visual analytics and accurate data driven maps of asset correlations and tail risks can enable a stronger intuition of market dynamics.
Financial Cartography at Bogazici UniversityKimmo Soramaki
As the financial system becomes more complex, new methods to understand its inherent risks and dynamics are needed. Kimmo Soramäki will discuss how network analysis of large‐scale financial transaction data can be used to improve our understanding systemic risk. He will also show case studies how visual analytics and accurate data driven maps of asset correlations and tail risks can enable a stronger intuition of market dynamics.
Is network theory the best hope for regulating systemic risk?Kimmo Soramaki
The presentation is organised around three policy questions:
1. How can we measure the systemic importance of a bank?
2. Can regulators promote a safer financial system by affecting its topology?
3. Is it possible to devise early-warning indicators from real-time data?
Ontology Mapping for Dynamic Multiagent Environment IJORCS
Ontologies are essential for the realization of the Semantic Web, which in turn relies on the ability of systems to identify and exploit relationships that exist between and within ontologies. As ontologies can be used to represent different domains, there is a high need for efficient ontology matching techniques that can allow information to be easily shared between different heterogeneous systems. There are various systems were proposed recently for ontology mapping. Ontology mapping is a prerequisite for achieving heterogeneous data integration on the Semantic Web. The vision of the Semantic Web implies that a large number of ontologies present on the web need to be aligned before one can make use of them. At the same time, these ontologies can be used as domain-specific background knowledge by the ontology mapping systems to increase the mapping precision. However, these ontologies can differ in representation, quality, and size that pose different challenges to ontology mapping. In this paper, we analyzed the various challenges of recently introduced Multi-Agent Ontology Mapping Framework, DSSim and we have integrated an efficient feature called QoS-Web Services Composition with DSSsim. ie we have improved this framework with QoS based Service Compositions Mechanism. From our experimental results, it is established that this developed QoS based Web Services Compositions Mechanism for Multiagent Ontology Mapping Framework minimizing uncertain reasoning and improves matching time, which are encouraging results of our proposed work.
Management High-level overview of the OMG Data Distribution Service (DDS)Gerardo Pardo-Castellote
This document provides a good management-lever introduction to the Data-Distribution Service (DDS) technology and capabilities. It was prepared by the OMG at the request of the US Navy in order to educate on the data-centric software architectural principles of DDS and how they can help meet its agility and cost-control requirements.
Mapping Financial Landscapes @ Norges BankKimmo Soramaki
Financial market turmoil has revealed the interconnected nature of modern financial systems. Industry, regulators and academics agree on the need for better analytical tools that can help monitor and safeguard against systemic risks. Kimmo Soramaki reviews new research in financial network analysis, including how network analysis of large-scale financial transaction data can be used to improve our understanding of how the financial system functions. How can visual analytics of time-series networks bring new insights? How can cross-asset networks enable stronger intuition of market dynamics?
Presented at the annual Financial Risk and Network Theory conference in Cambridge, I discuss recent work by FNA on addressing various financial risks with the help of network analysis.
Presentation at FSC-PSSC Workshop "Systemic risk analysis: interconnectedness within the financial system and market infrastructures", Frankfurt, 17 October 2012
The paper presented here will be published in Journal of Economic Behavior and Organization (http://www.fna.fi/papers/jebo2012gs.pdf)
Is network theory the best hope for regulating systemic risk?Kimmo Soramaki
The presentation is organised around three policy questions:
1. How can we measure the systemic importance of a bank?
2. Can regulators promote a safer financial system by affecting its topology?
3. Is it possible to devise early-warning indicators from real-time data?
Ontology Mapping for Dynamic Multiagent Environment IJORCS
Ontologies are essential for the realization of the Semantic Web, which in turn relies on the ability of systems to identify and exploit relationships that exist between and within ontologies. As ontologies can be used to represent different domains, there is a high need for efficient ontology matching techniques that can allow information to be easily shared between different heterogeneous systems. There are various systems were proposed recently for ontology mapping. Ontology mapping is a prerequisite for achieving heterogeneous data integration on the Semantic Web. The vision of the Semantic Web implies that a large number of ontologies present on the web need to be aligned before one can make use of them. At the same time, these ontologies can be used as domain-specific background knowledge by the ontology mapping systems to increase the mapping precision. However, these ontologies can differ in representation, quality, and size that pose different challenges to ontology mapping. In this paper, we analyzed the various challenges of recently introduced Multi-Agent Ontology Mapping Framework, DSSim and we have integrated an efficient feature called QoS-Web Services Composition with DSSsim. ie we have improved this framework with QoS based Service Compositions Mechanism. From our experimental results, it is established that this developed QoS based Web Services Compositions Mechanism for Multiagent Ontology Mapping Framework minimizing uncertain reasoning and improves matching time, which are encouraging results of our proposed work.
Management High-level overview of the OMG Data Distribution Service (DDS)Gerardo Pardo-Castellote
This document provides a good management-lever introduction to the Data-Distribution Service (DDS) technology and capabilities. It was prepared by the OMG at the request of the US Navy in order to educate on the data-centric software architectural principles of DDS and how they can help meet its agility and cost-control requirements.
Mapping Financial Landscapes @ Norges BankKimmo Soramaki
Financial market turmoil has revealed the interconnected nature of modern financial systems. Industry, regulators and academics agree on the need for better analytical tools that can help monitor and safeguard against systemic risks. Kimmo Soramaki reviews new research in financial network analysis, including how network analysis of large-scale financial transaction data can be used to improve our understanding of how the financial system functions. How can visual analytics of time-series networks bring new insights? How can cross-asset networks enable stronger intuition of market dynamics?
Presented at the annual Financial Risk and Network Theory conference in Cambridge, I discuss recent work by FNA on addressing various financial risks with the help of network analysis.
Presentation at FSC-PSSC Workshop "Systemic risk analysis: interconnectedness within the financial system and market infrastructures", Frankfurt, 17 October 2012
The paper presented here will be published in Journal of Economic Behavior and Organization (http://www.fna.fi/papers/jebo2012gs.pdf)
Global Trends in Large Value Payment SystemsKimmo Soramaki
We discuss 10 main trends in the settlement of large-value interbank payments;
1. Diffusion of Real Time Gross Settlement
2. Take Off of Hybrid Systems
3. Emergence of Cross Border and Offshore Payment Systems
4. The Rise of CLS
5. Increasing Settlement Values and Volumes
6. Shrinking Average Payment Size
7. Falling Number of System Participants
8. Extended Operating Hours
9. Declining Transaction Fess
10. Adoption of Common Standards for LVPS
As the financial system becomes more complex, new methods to understand the inherent risks and dynamics are needed. Kimmo Soramäki will discuss how network analysis of large‐scale financial transaction data can be used to improve our understanding systemic risk. He will also show case studies how visual analytics and accurate data driven maps of asset correlations and tail risks can enable a stronger intuition of market dynamics.
Global Network of Payment Flows - Presentation at Commerzbank Cash ForumKimmo Soramaki
The presentation summarizes results from the research paper by Samantha Cook and myself on "The Global Network of Payment Flows" and discusses other applications of payment data for gaining business insights or for improving risk models.
Applications of Network Theory in Finance and ProductionKimmo Soramaki
In recent years, network theory has proved useful in applications ranging from cancer research to the social graph. Applications of network theory are becoming ever more present also in economics and finance, with network analysis providing answers to questions where traditional analysis methods are weak, and leading to improved models across wide types of risks. This presentation discusses three real-world applications of network theory: identifying pivotal countries and payment corridors from the global network of payment flows, using industry level value chains for casualty risk modeling, and using asset correlation networks for detecting emerging and systemic risks.
Financial Networks and Financial StabilityKimmo Soramaki
The recent global financial crisis has illustrated the role of financial linkages as a channel for the propagation of shocks. It also brought to the fore the concept that institutions may be “too interconnected to fail”, in addition to the traditional concept of being “too big to fail”.
Financial Network Analysis - Talk at Oslo University 25 March 2011Kimmo Soramaki
Kimmo will introduce research in financial network analysis. He will talk about recent research on networks across various disciplines and discuss how network analysis can be used to gain a better understanding of the financial system and enhance its stability. He will also present a new open source tool ( www.financialnetworkanalyzer.com ) that can help policymakers and researchers in the area.
COMMUNICATIONS OF THE ACM November 2004Vol. 47, No. 11 15.docxmonicafrancis71118
COMMUNICATIONS OF THE ACM November 2004/Vol. 47, No. 11 15
N
etworks are hot. The
Internet has made it pos-
sible to observe and mea-
sure linkages
representing relationships of
all kinds. We now recognize
networks everywhere: air
traffic, banking, chemical
bonds, data communications,
ecosystems, finite element
grids, fractals, interstate
highways, journal citations,
material structures, nervous
systems, oil pipelines, orga-
nizational networks, power
grids, social structures, trans-
portation, voice communica-
tion, water supply, Web
URLs, and more.
Several fields are collabo-
rating on the development of
network theory, measurement,
and mapping: mathematics
(graph theory), sociology (net-
works of influence and communi-
cation), computing (Internet), and
business (organizational net-
works). This convergence has pro-
duced useful results for risk
assessment and reduction in com-
plex infrastructure networks,
attacking and defending networks,
protecting against network con-
nectivity failures, operating busi-
nesses, spreading epidemics
(pathogens as well as computer
viruses), and spreading innova-
tion. Here, I will survey the fun-
damental laws of networks that
enable these results.
Defining a Network
A network is usually defined as a
set of nodes and links. The nodes
represent entities such as persons,
machines, molecules, documents,
or businesses; the links represent
relationships between pairs of
entities. A link can be directed
(one-way relationship) or undi-
rected (mutual relationship). A
hop is a transition from one node
to another across a single link
separating them. A path is a series
of hops. Networks are very gen-
eral: they can represent any kind
of relation among entities.
Some common network
topologies (interconnection pat-
terns) have their own names:
clique or island (a connected sub-
network that may be isolated
from other cliques), hierarchical
network (tree structured), hub-
and-spoke network (a special
node, the hub, connected directly
to every other node), and multi-
hub network (several hubs con-
nected directly to many nodes).
Some network topologies are
planned, such as the electric grid,
the interstate highway system, or
Network Laws
M
IC
H
A
EL
S
LO
A
N
Peter J. Denning
Many networks, physical and social, are complex and scale-invariant.
This has important implications from the spread of epidemics and
innovations to protection from attack.
The Profession of IT
16 November 2004/Vol. 47, No. 11 COMMUNICATIONS OF THE ACM
the air traffic system; others are
unplanned. In his seminal papers
about the Internet, Paul Baran
proposed that a planned, distrib-
uted network would be more
resilient to failures than a hub-
and-spoke network.
A host of physical systems eas-
ily fit a network model. Perhaps
less obvious is that human social
networks also fit the model. The
individuals of an organization are
linked by their relationships—
who emails whom, who seeks
advice from whom, or who influ-
ences w.
Discussion of "Google matrix of world trade" @ DNBKimmo Soramaki
Discussion of “Google matrix of the world trade network"
(http://arxiv.org/abs/1103.5027) by L. Ermann and D.L .Shepelyansky at
De Nederlandsche Bank conference "Complex systems: Towards a better
understanding of financial stability and crises"
(http://bit.ly/tj6G2h)
A MALICIOUS USERS DETECTING MODEL BASED ON FEEDBACK CORRELATIONSIJCNC
The trust and reputation models were introduced to restrain the impacts caused by rational but selfish
peers in P2P streaming systems. However, these models face with two major challenges from dishonest
feedback and strategic altering behaviors. To answer these challenges, we present a global trust model
based on network community, evaluation correlations, and punishment mechanism. We also propose a
two-layered overlay to provide the function of peers’ behaviors collection and malicious detection.
Furthermore, we analysis several security threats in P2P streaming systems, and discuss how to defend
with them by our trust mechanism. The simulation results show that our trust framework can successfully
filter out dishonest feedbacks by using correlation coefficients. It can effectively defend against the
security threats with good load balance as well.
Presentation held at the 5th Risk Summit organized by Center for Risk Studies at the University of Cambridge. See http://www.risk.jbs.cam.ac.uk/news/events/risksummits/risksummit2014.html
Slides from a PRMIA Webinar broadcast on 9 October 2013 by Alan Laubsch and me.
Description from PRMIA Website:
This webinar will apply advanced network visualization techniques to detect emerging systemic stress scenarios.
We will start with an introduction of the Adaptive Stress Testing framework, which harnesses network intelligence in the stress testing process. We'll show how Adaptive Stress Testing can be used to design credible scenarios and monitor emerging risks.
We review historical case studies, and then discuss potential emerging threats in the current market environment by using network visualization.
System shock analysis and complex network effectsKimmo Soramaki
Joint presentation with Michelle Tuveson and Dr Andrew Coburn from Cambridge Risk Center at the Conference Board Global Risk Conference in New York, 8 May 2013.
Links to conference website: http://www.conference-board.org/conferences/conferencedetail.cfm?conferenceid=2456
Identifying systemically important banks in payment systemsKimmo Soramaki
Talk at 'Systemic Risk Conference - Economists meet Neuroscientists' in Frankfurt on 18 September 2012. The conference was organized by House of Finance and Frankfurt Institute for Advanced Studies.
how can i use my minded pi coins I need some funds.DOT TECH
If you are interested in selling your pi coins, i have a verified pi merchant, who buys pi coins and resell them to exchanges looking forward to hold till mainnet launch.
Because the core team has announced that pi network will not be doing any pre-sale. The only way exchanges like huobi, bitmart and hotbit can get pi is by buying from miners.
Now a merchant stands in between these exchanges and the miners. As a link to make transactions smooth. Because right now in the enclosed mainnet you can't sell pi coins your self. You need the help of a merchant,
i will leave the telegram contact of my personal pi merchant below. 👇 I and my friends has traded more than 3000pi coins with him successfully.
@Pi_vendor_247
Even tho Pi network is not listed on any exchange yet.
Buying/Selling or investing in pi network coins is highly possible through the help of vendors. You can buy from vendors[ buy directly from the pi network miners and resell it]. I will leave the telegram contact of my personal vendor.
@Pi_vendor_247
how to sell pi coins in all Africa Countries.DOT TECH
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
how to sell pi coins on Bitmart crypto exchangeDOT TECH
Yes. Pi network coins can be exchanged but not on bitmart exchange. Because pi network is still in the enclosed mainnet. The only way pioneers are able to trade pi coins is by reselling the pi coins to pi verified merchants.
A verified merchant is someone who buys pi network coins and resell it to exchanges looking forward to hold till mainnet launch.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
US Economic Outlook - Being Decided - M Capital Group August 2021.pdfpchutichetpong
The U.S. economy is continuing its impressive recovery from the COVID-19 pandemic and not slowing down despite re-occurring bumps. The U.S. savings rate reached its highest ever recorded level at 34% in April 2020 and Americans seem ready to spend. The sectors that had been hurt the most by the pandemic specifically reduced consumer spending, like retail, leisure, hospitality, and travel, are now experiencing massive growth in revenue and job openings.
Could this growth lead to a “Roaring Twenties”? As quickly as the U.S. economy contracted, experiencing a 9.1% drop in economic output relative to the business cycle in Q2 2020, the largest in recorded history, it has rebounded beyond expectations. This surprising growth seems to be fueled by the U.S. government’s aggressive fiscal and monetary policies, and an increase in consumer spending as mobility restrictions are lifted. Unemployment rates between June 2020 and June 2021 decreased by 5.2%, while the demand for labor is increasing, coupled with increasing wages to incentivize Americans to rejoin the labor force. Schools and businesses are expected to fully reopen soon. In parallel, vaccination rates across the country and the world continue to rise, with full vaccination rates of 50% and 14.8% respectively.
However, it is not completely smooth sailing from here. According to M Capital Group, the main risks that threaten the continued growth of the U.S. economy are inflation, unsettled trade relations, and another wave of Covid-19 mutations that could shut down the world again. Have we learned from the past year of COVID-19 and adapted our economy accordingly?
“In order for the U.S. economy to continue growing, whether there is another wave or not, the U.S. needs to focus on diversifying supply chains, supporting business investment, and maintaining consumer spending,” says Grace Feeley, a research analyst at M Capital Group.
While the economic indicators are positive, the risks are coming closer to manifesting and threatening such growth. The new variants spreading throughout the world, Delta, Lambda, and Gamma, are vaccine-resistant and muddy the predictions made about the economy and health of the country. These variants bring back the feeling of uncertainty that has wreaked havoc not only on the stock market but the mindset of people around the world. MCG provides unique insight on how to mitigate these risks to possibly ensure a bright economic future.
how to swap pi coins to foreign currency withdrawable.DOT TECH
As of my last update, Pi is still in the testing phase and is not tradable on any exchanges.
However, Pi Network has announced plans to launch its Testnet and Mainnet in the future, which may include listing Pi on exchanges.
The current method for selling pi coins involves exchanging them with a pi vendor who purchases pi coins for investment reasons.
If you want to sell your pi coins, reach out to a pi vendor and sell them to anyone looking to sell pi coins from any country around the globe.
Below is the contact information for my personal pi vendor.
Telegram: @Pi_vendor_247
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
Empowering the Unbanked: The Vital Role of NBFCs in Promoting Financial Inclu...Vighnesh Shashtri
In India, financial inclusion remains a critical challenge, with a significant portion of the population still unbanked. Non-Banking Financial Companies (NBFCs) have emerged as key players in bridging this gap by providing financial services to those often overlooked by traditional banking institutions. This article delves into how NBFCs are fostering financial inclusion and empowering the unbanked.
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
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how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
If you are looking for a pi coin investor. Then look no further because I have the right one he is a pi vendor (he buy and resell to whales in China). I met him on a crypto conference and ever since I and my friends have sold more than 10k pi coins to him And he bought all and still want more. I will drop his telegram handle below just send him a message.
@Pi_vendor_247
1. Understanding Financial Catastrophe Risk:
Developing a Research Agenda
Centre for Risk Studies, University of Cambridge
9 April 2013
Financial Networks and
Cartography
Dr. Kimmo Soramäki
Founder and CEO
FNA, www.fna.fi
2. Map of 1854 Broad Street cholera
outbreak by John Snow
3. Agenda
Networks "connect the dots". They operationalize the
concept of financial interconnectedness that underpins
systemic risk .
The epidemiology of finance is the study of contagion.
Contagion models are often based on network models. The
goal is often to identify and contain "super-spreaders" or
"systemically important banks"
Network visualizations allow us to "map the financial
system". Maps are intelligence amplification, they aid in
decision making and build intuition
4. Systemic risk ≠ systematic risk
News articles mentioning “systemic risk”, Source: trends.google.com
The risk that a system composed of many interacting
parts fails (due to a shock to some of its parts).
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.
Not:
Domino effects, cascading failures, financial
interlinkages, … -> i.e. a process in the
financial network
4
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. Networks brings us beyond the Data Cube
" The Tesseract"
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 6
7. 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), M. Boss, H. Elsinger, M. Summer, S. Thurner, The
Physica A, Vol. 379, pp 317-333. network topology of the interbank market, Santa
See: www.fna.fi/papers/physa2007sbagb.pdf Fe Institute Working Paper 03-
7
10-054, 2003.
8. Most central banks have now mapped their
interbank payment systems
Becher, Millard and Soramäki (2008). Agnes Lubloy (2006). Topology of the Hungarian
The network topology of CHAPS large-value transfer system. Magyar Nemzeti Bank
Sterling. BoE Working Paper No. 355. Occasional Papers
Embree and Roberts (2009). Network
Analysis and Canada's Large Value Transfer
SystemBoC Discussion Paper 2009-13
8
9. Centrality Measures for
Financial Systems
Metrics developed in other fields and
with other network processes in
mind:
• Degree, Closeness, Betweenness,
PageRank, etc.
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
World's Ocean Currents
DP, 2012, Absorbing Markov chain NASA Scientific Visualization Studio 9
11. Inferring Networks
Calculate pairwise Control for common Keep statistically
correlations factors (e.g. market) significant correlations
Correct for multiple Convert to network Visualize as tree
comparisons
12. Map on cross asset correlations
and volatilities
Nodes (circles) represent assets and Node color indicates
links (lines) represent correlations identified community
between the linked assets
Node sizes scale with
the variance of the Mapping multiple
return: assets with dimensions of the same
larger nodes have more Low correlation
data set on a single map
(long link)
variable returns
allows visual inference
of connections.
Shorter links indicate higher One can focus on
correlations. High correlation
(short link) details - while
maintaining an
overview.
Interactive version at www.fna.fi/demos/crc/viz/asset-tree.html
13. Priorities for research agenda
1. Measuring and mapping interconnectedness (network
structure), modelling contagion (network process) and
understanding their interplay
15. Priorities for research agenda
1. Measuring and mapping interconnectedness (network
structure), modelling contagion (network process) and
understanding their interplay
2. Developing early warning indicators and visual analytics
systems for continuous monitoring of the financial
system
16. Example: Oversight Monitor
(network is fictional)
The monitor will allow the identification of
systemically important banks and evaluation
of the impact of bank failures on the system
http://www.fna.fi/solutions/oversight-monitor 16
17. Priorities for research agenda
1. Measuring and mapping interconnectedness (network
structure), modelling contagion (network process) and
understanding their interplay
2. Developing early warning indicators and visual analytics
systems for continuous monitoring of the financial
system
3. Taking into account the 'social psychology' aspect of the
financial system