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Systemic Risk in Markets with Multiple Central Counterparties

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  • Inaki Aldasoro
  • Luitgard A M Veraart

Abstract

We provide a framework for modelling risk and quantifying payment shortfalls in cleared markets with multiple central counterparties (CCPs). Building on the stylised fact that clearing membership is shared among CCPs, we show how this can transmit stress across markets through multiple CCPs. We provide stylised examples to lay out how such stress transmission can take place, as well as empirical evidence to illustrate that the mechanisms we study could be relevant in practice. Furthermore, we show how stress mitigation mechanisms such as variation margin gains haircutting by one CCP can have spillover effects on other CCPs. The framework can be used to enhance CCP stress-testing, which currently relies on the "Cover 2" standard requiring CCPs to be able to withstand the default of their two largest clearing members. We show that who these two clearing members are can be significantly affected by higher-order effects arising from interconnectedness through shared clearing membership. Looking at the full network of CCPs and shared clearing members is therefore important from a financial stability perspective.

Suggested Citation

  • Inaki Aldasoro & Luitgard A M Veraart, 2022. "Systemic Risk in Markets with Multiple Central Counterparties," BIS Working Papers 1052, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:1052
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    References listed on IDEAS

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    1. Boissel, Charles & Derrien, François & Ors, Evren & Thesmar, David, 2017. "Systemic risk in clearing houses: Evidence from the European repo market," Journal of Financial Economics, Elsevier, vol. 125(3), pages 511-536.
    2. Duffie, Darrell, 2014. "Resolution of Failing Central Counterparties," Research Papers 3256, Stanford University, Graduate School of Business.
    3. Mark Paddrik & Sriram Rajan & H. Peyton Young, 2020. "Contagion in Derivatives Markets," Management Science, INFORMS, vol. 66(8), pages 3603-3616, August.
    4. Paddrick, Mark & Young, H. Peyton, 2021. "How safe are central counterparties in credit default swap markets?," LSE Research Online Documents on Economics 101170, London School of Economics and Political Science, LSE Library.
    5. Bruno Biais & Florian Heider & Marie Hoerova, 2016. "Risk-Sharing or Risk-Taking? Counterparty Risk, Incentives, and Margins," Journal of Finance, American Finance Association, vol. 71(4), pages 1669-1698, August.
    6. Huang, Wenqian & Zhu, Haoxiang, 2024. "CCP auction design," Journal of Economic Theory, Elsevier, vol. 217(C).
    7. Rama Cont, 2017. "Central clearing and risk transformation," Working Paper 2017/3, Norges Bank.
    8. Albert J. Menkveld & Guillaume Vuillemey, 2021. "The Economics of Central Clearing," Annual Review of Financial Economics, Annual Reviews, vol. 13(1), pages 153-178, November.
    9. Wenqian Huang & Elöd Takáts, 2024. "Model Risk at Central Counterparties: Is Skin in the Game a Game Changer?," International Journal of Central Banking, International Journal of Central Banking, vol. 20(3), pages 161-184, July.
    10. Ghamami, Samim & Glasserman, Paul & Young, Hobart, 2022. "Collateralized networks," LSE Research Online Documents on Economics 107496, London School of Economics and Political Science, LSE Library.
    11. Rodrigo Cifuentes & Hyun Song Shin & Gianluigi Ferrucci, 2005. "Liquidity Risk and Contagion," Journal of the European Economic Association, MIT Press, vol. 3(2-3), pages 556-566, 04/05.
    12. Paul Glasserman & Ciamac C. Moallemi & Kai Yuan, 2015. "Hidden Illiquidity with Multiple Central Counterparties," Working Papers 15-07, Office of Financial Research, US Department of the Treasury.
    13. Vincent Bignon & Guillaume Vuillemey, 2020. "The Failure of a Clearinghouse: Empirical Evidence [Counterparty risk externality: centralized versus over-the-counter markets]," Review of Finance, European Finance Association, vol. 24(1), pages 99-128.
    14. Wenqian Huang, 2019. "Central counterparty capitalization and misaligned incentives," BIS Working Papers 767, Bank for International Settlements.
    15. Gandy, Axel & Veraart, Luitgard A. M., 2017. "A Bayesian methodology for systemic risk assessment in financial networks," LSE Research Online Documents on Economics 66312, London School of Economics and Political Science, LSE Library.
    16. Larry Eisenberg & Thomas H. Noe, 2001. "Systemic Risk in Financial Systems," Management Science, INFORMS, vol. 47(2), pages 236-249, February.
    17. Paddrick, Mark & Rajan, Sriram & Young, H. Peyton, 2020. "Contagion in derivatives markets," LSE Research Online Documents on Economics 100868, London School of Economics and Political Science, LSE Library.
    18. L. C. G. Rogers & L. A. M. Veraart, 2013. "Failure and Rescue in an Interbank Network," Management Science, INFORMS, vol. 59(4), pages 882-898, April.
    19. Axel Gandy & Luitgard A. M. Veraart, 2017. "A Bayesian Methodology for Systemic Risk Assessment in Financial Networks," Management Science, INFORMS, vol. 63(12), pages 4428-4446, December.
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    More about this item

    Keywords

    central counterparties; systemic risk; contagion; stress testing; Cover 2.;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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