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Clearing Networks

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Presentation at FSC-PSSC Workshop "Systemic risk analysis: interconnectedness within the financial system and market infrastructures", Frankfurt, 17 October 2012 …

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)

Published in: Economy & Finance

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  • 1. FSC-PSSC WorkshopSystemic risk analysis: interconnectednesswithin the financial system and marketinfrastructuresFrankfurt, 17 October 2012Clearing 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) 2
  • 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 3
  • 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
  • 6. Examples of network structures 6
  • 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 7
  • 8. Example of Novation 8
  • 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) 9
  • 10. CCP’s total exposure against all GCMs 10
  • 11. CCP’s expected exposure against a single GCM 11
  • 12. CCP’s largest exposure against a single GCM- Tiering 12
  • 13. CCP’s largest exposure against a single GCM- Concentration 13
  • 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 14
  • 15. Thank you 15
  • 16. Complete results - Exposures 16
  • 17. Complete results - Margins 17