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)
1. FSC-PSSC Workshop
Systemic risk analysis: interconnectedness
within the financial system and market
infrastructures
Frankfurt, 17 October 2012
Clearing Networks
Kimmo Soramäki
Founder and CEO
FNA, www.fna.fi
Marco Galbiati
ECB/Bank of England
2. Motivation
• Central counterparties are playing a major role in the financial
reform: G20/Pittsburgh, CPSS/IOSCO, Committee on the Global
Financial System, etc.
• The main function of Central Counterparties (CCPs) is to novate
contracts between trading parties, becoming the ‘seller to every
buyer, and buyer to every seller’
• CCPs eliminate counterparty risk but introduce new risks (risks for
CCP and margin needs for members)
• Question: How does the topology of the clearing system affect the
exposures of the CCP (and the margin needs of all members)
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3. Agenda
• Model : Trading and Exposures matrices, Novation and
Clearing Algorithm
• Variable(s) : Random trading matrices and Clearing
topologies measured by their tiering and concentration
• Results : Distributions of exposures and margin needs
with different topologies
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4. Trading and Exposures
• We consider one contract, traded on a market by N
‘counterparties’
• Trading matrix T presents nominal positions of trader i
against j
• Exposures between i and j are given by the absolute value of
bilateral position of trades
• Example:
Trading matrix Bilateral Netting Exposures 4
5. Clearing Topology
Star 626 topologically different trees
Concentration [0,1]
20 members + CCP Tiering [0,20]
Tiering = N - Number of GCMs - 1
Concentration = Gini co-efficient 5
7. Novation and Clearing
• Novation is the replacement of exposures between non-
adjacent nodes in the clearing network, with other
exposures according to a precise rule
• Clearing consists in applying novation iteratively, until
no further novation is possible
• Some trades are internalized
• Others are brought to CCP
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9. Results - Methodology
• We vary
– Trading matrix (3000 realization)
– Clearing topology (all combinations with 20 counterparties)
• Run the clearing algorithm
• Look at exposure distributions. From these distributions we
focus on
– CCP’s total exposure against all GCMs
– CCP’s expected exposure against a single GCM
– CCP’s largest exposure against a single GCM
• (The paper also looks at margin needs)
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14. Summary
• We developed a model of clearing systems as networks
that transform exposures via novation
• Effects are complex – best topology depends on the
objective
• Topologies with lower tiering are more robust against
tail risks of CCP but worse for expected risks
• Topologies with higher concentration are always better
for CCP
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