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.
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.
European Government Bond Correlation Dynamics: Taming Contagion RisksPeter Schwendner
In the timeframe from 2004-2015, the European government bond market experienced several different economic phases driven by the Euro convergence, but also by unequal sovereign credit capacity and fiscal imbalances. The market substantially repriced these imbalances after the financial crisis of 2008.
The phases in the market perception of sovereign risk are reflected in a pronounced time structure of the correlation matrix.
"Core" and "peripheral" bonds cluster themselves into a block-like structure, but the relationship between the blocks is time-dependent.
Using noise-filtered partial correlation networks, the time dependency can be visualized and evaluated using quantitative metrics.
Our results support the view that market-implied contagion risks decreased since the European rescue and stability architecture came into force in 2012.
In 2015 during the negotiations around the third Greece bailout, contagion risks reappeared in the yield correlations, but did not materialize in the form of large movements in the absolute yield levels of the other periphery countries.
The correlation influences seem to be a helpful information to construct dynamical hedging strategies for a European bond portfolio.
A presentation of Apache TinkerPop's Gremlin language with running examples over the MovieLens dataset. Presented August 19, 2015 at NoSQL NOW in San Jose, California.
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.
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.
European Government Bond Correlation Dynamics: Taming Contagion RisksPeter Schwendner
In the timeframe from 2004-2015, the European government bond market experienced several different economic phases driven by the Euro convergence, but also by unequal sovereign credit capacity and fiscal imbalances. The market substantially repriced these imbalances after the financial crisis of 2008.
The phases in the market perception of sovereign risk are reflected in a pronounced time structure of the correlation matrix.
"Core" and "peripheral" bonds cluster themselves into a block-like structure, but the relationship between the blocks is time-dependent.
Using noise-filtered partial correlation networks, the time dependency can be visualized and evaluated using quantitative metrics.
Our results support the view that market-implied contagion risks decreased since the European rescue and stability architecture came into force in 2012.
In 2015 during the negotiations around the third Greece bailout, contagion risks reappeared in the yield correlations, but did not materialize in the form of large movements in the absolute yield levels of the other periphery countries.
The correlation influences seem to be a helpful information to construct dynamical hedging strategies for a European bond portfolio.
A presentation of Apache TinkerPop's Gremlin language with running examples over the MovieLens dataset. Presented August 19, 2015 at NoSQL NOW in San Jose, California.
NetworkX is a Python language software package and an open-source tool for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. NetworkX can load, store and analyze networks, generate new networks, build network models, and draw networks. It is a computational network modelling tool and not a software tool development. The first public release of the library, which is all based on Python, was in April 2005.
Learn about potential of Social Network Analysis in achieving better understanding of inter customer relationship, influence and management of big data. Take a sneak peak at SNA implementation at Mobilink in this case study.
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.
Slide deck from my presentation at NYC's #Pydata 2012 conference - http://nyc2012.pydata.org/abstracts/#gephi
Talk abstract:
Are you interested in working with social data to map out communities and connections between friends, fans and followers? In this session I'll show ways in which we use the python networkx library along with the open source gephi visualization tool to make sense of social network data. We'll take a few examples from Twitter, look at how a hashtag spreads through the network, and then analyze the connections between users posting to the hashtag. We'll be constructing graphs, running stats on them and then visualizing the output.
Slides Επιστήμης Δικτύων για υπολογισμούς με την Python στα πλαίσια του μεταπτυχιακού μαθήματος των Ψηφιακών Τεχνολογιών στην Εκπαίδευση του Μαθηματικού Τμήματος του Πανεπιστημίου Πατρών κατά το χειμερινό εξάμηνο 2014-5.
Τα slides αυτά θα γίνονται συνεχώς updated ως το τέλος του εξαμήνου (τέλη Δεκεμβρίου 2014). Η ημερομηνία του update γράφεται στην πρώτη σελίδα των slides.
Social networks are not new, even though websites like Facebook and Twitter might make you want to believe they are; and trust me- I’m not talking about Myspace! Social networks are extremely interesting models for human behavior, whose study dates back to the early twentieth century. However, because of those websites, data scientists have access to much more data than the anthropologists who studied the networks of tribes!
Because networks take a relationship-centered view of the world, the data structures that we will analyze model real world behaviors and community. Through a suite of algorithms derived from mathematical Graph theory we are able to compute and predict behavior of individuals and communities through these types of analyses. Clearly this has a number of practical applications from recommendation to law enforcement to election prediction, and more.
The basics of Python are rather straightforward. In a few minutes you can learn most of the syntax. There are some gotchas along the way that might appear tricky. This talk is meant to bring programmers up to speed with Python. They should be able to read and write Python.
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?
NetworkX is a Python language software package and an open-source tool for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. NetworkX can load, store and analyze networks, generate new networks, build network models, and draw networks. It is a computational network modelling tool and not a software tool development. The first public release of the library, which is all based on Python, was in April 2005.
Learn about potential of Social Network Analysis in achieving better understanding of inter customer relationship, influence and management of big data. Take a sneak peak at SNA implementation at Mobilink in this case study.
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.
Slide deck from my presentation at NYC's #Pydata 2012 conference - http://nyc2012.pydata.org/abstracts/#gephi
Talk abstract:
Are you interested in working with social data to map out communities and connections between friends, fans and followers? In this session I'll show ways in which we use the python networkx library along with the open source gephi visualization tool to make sense of social network data. We'll take a few examples from Twitter, look at how a hashtag spreads through the network, and then analyze the connections between users posting to the hashtag. We'll be constructing graphs, running stats on them and then visualizing the output.
Slides Επιστήμης Δικτύων για υπολογισμούς με την Python στα πλαίσια του μεταπτυχιακού μαθήματος των Ψηφιακών Τεχνολογιών στην Εκπαίδευση του Μαθηματικού Τμήματος του Πανεπιστημίου Πατρών κατά το χειμερινό εξάμηνο 2014-5.
Τα slides αυτά θα γίνονται συνεχώς updated ως το τέλος του εξαμήνου (τέλη Δεκεμβρίου 2014). Η ημερομηνία του update γράφεται στην πρώτη σελίδα των slides.
Social networks are not new, even though websites like Facebook and Twitter might make you want to believe they are; and trust me- I’m not talking about Myspace! Social networks are extremely interesting models for human behavior, whose study dates back to the early twentieth century. However, because of those websites, data scientists have access to much more data than the anthropologists who studied the networks of tribes!
Because networks take a relationship-centered view of the world, the data structures that we will analyze model real world behaviors and community. Through a suite of algorithms derived from mathematical Graph theory we are able to compute and predict behavior of individuals and communities through these types of analyses. Clearly this has a number of practical applications from recommendation to law enforcement to election prediction, and more.
The basics of Python are rather straightforward. In a few minutes you can learn most of the syntax. There are some gotchas along the way that might appear tricky. This talk is meant to bring programmers up to speed with Python. They should be able to read and write Python.
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?
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.
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)
Transhuman Crypto Cloudminds
Melanie Swan, Technology Theorist, Philosophy Department, Purdue University USA, Founder, Institute for Blockchain .
Studies and DIYgenomics.
Abstract
Considering the mutual benefits of blockchain and transhumanism, this essay
proposes crypto cloudminds as a safe mechanism by which the human mind might
transcend its unitary limitations by permissioning partial resources to join a multiparty mind (comprised of human and machine minds) in a cloud-based
environment. Cloudminds could have diverse purposes including problem solving
(addressing future-of-work issues with Maslow Smart Contracts), learning,
experience, exploration, innovation, artistic expression, and other personal
development activities. Crypto cloudminds could be multicurrency, operating with
payment remuneration, security, and (especially) ideas as the denominations of
measure. For thriving in the future, mind node peers could enter “Yes-and”
Payment Channels with one another for collaborative idea development. For
surviving in the future, good-player behavior could be game-theoretically enforced
with the simultaneous privacy-transparency property of blockchains, together with
the immutable peer-confirmed consensus algorithm and audit-log checks and
balances system. Overall, blockchains might serve as an institutional technology
that is the basis for treaties and progress in a multi-species society of human,
algorithm, and machine, guiding the way to positive transhuman futures.
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.
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.
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
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)
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?
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
when will pi network coin be available on crypto exchange.DOT TECH
There is no set date for when Pi coins will enter the market.
However, the developers are working hard to get them released as soon as possible.
Once they are available, users will be able to exchange other cryptocurrencies for Pi coins on designated exchanges.
But for now the only way to sell your pi coins is through verified pi vendor.
Here is the telegram contact of my personal pi vendor
@Pi_vendor_247
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
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.
what is the best method to sell pi coins in 2024DOT TECH
The best way to sell your pi coins safely is trading with an exchange..but since pi is not launched in any exchange, and second option is through a VERIFIED pi merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and pioneers and resell them to Investors looking forward to hold massive amounts before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade pi coins with.
@Pi_vendor_247
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
how can I sell pi coins after successfully completing KYCDOT TECH
Pi coins is not launched yet in any exchange 💱 this means it's not swappable, the current pi displaying on coin market cap is the iou version of pi. And you can learn all about that on my previous post.
RIGHT NOW THE ONLY WAY you can sell pi coins is through verified pi merchants. A pi merchant is someone who buys pi coins and resell them to exchanges and crypto whales. Looking forward to hold massive quantities of pi coins before the mainnet launch.
This is because pi network is not doing any pre-sale or ico offerings, the only way to get my coins is from buying from miners. So a merchant facilitates the transactions between the miners and these exchanges holding pi.
I and my friends has sold more than 6000 pi coins successfully with this method. I will be happy to share the contact of my personal pi merchant. The one i trade with, if you have your own merchant you can trade with them. For those who are new.
Message: @Pi_vendor_247 on telegram.
I wouldn't advise you selling all percentage of the pi coins. Leave at least a before so its a win win during open mainnet. Have a nice day pioneers ♥️
#kyc #mainnet #picoins #pi #sellpi #piwallet
#pinetwork
The Evolution of Non-Banking Financial Companies (NBFCs) in India: Challenges...beulahfernandes8
Role in Financial System
NBFCs are critical in bridging the financial inclusion gap.
They provide specialized financial services that cater to segments often neglected by traditional banks.
Economic Impact
NBFCs contribute significantly to India's GDP.
They support sectors like micro, small, and medium enterprises (MSMEs), housing finance, and personal loans.
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
Scope Of Macroeconomics introduction and basic theories
Network Approaches for Interbank Markets
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:
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)
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.
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
25. • Complete documentation with
tutorials and sample scripts
• >200 commands
• Web version & REST API is
free for academic research
• Ongoing collaboration with
several universities
27. Priorities for the Research Agenda
1. Measuring and mapping interconnectedness (network
structure), modelling contagion (network process) and
understanding their interplay
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