Clearing Networks

Kimmo SoramäkiFounder and CEOFNA, www.fna.fi

Marco GalbiatiECB/Bank of England

FSC-PSSC WorkshopSystemic risk analysis: interconnectedness within the financial system and market infrastructuresFrankfurt, 17 October 2012

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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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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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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

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Clearing Topology

Star 626 topologically different trees

Tiering [0,20]

Conc

entr

ation

[0,1

]

Tiering = N - Number of GCMs - 1Concentration = Gini co-efficient

20 members + CCP

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Examples of network structures

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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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Example of Novation

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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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CCP’s total exposure against all GCMs

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CCP’s expected exposure against a single GCM

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CCP’s largest exposure against a single GCM - Tiering

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CCP’s largest exposure against a single GCM - Concentration

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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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Thank you

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Complete results - Exposures

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Complete results - Margins