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Static models of central counterparty risk

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  • Samim Ghamami

    (Federal Reserve Board, Washington D.C. 20551, USA;
    Center for Risk Management Research, University of California, Berkeley, CA 94720, USA)

Abstract

Following the 2009 G-20 clearing mandate, international standard setting bodies (SSBs) have outlined a set of principles for central counterparty (CCP) risk management. They have also devised formulaic CCP risk capital requirements on clearing members for their central counterparty exposures. There is still no consensus among CCP regulators and bank regulators on how central counterparty risk should be measured coherently in practice. A conceptually sound and logically consistent definition of the CCP risk capital in the absence of a unifying CCP risk measurement framework is challenging. Incoherent CCP risk capital requirements may create an obscure environment disincentivizing the central clearing of over the counter (OTC) derivatives transactions. Based on novel applications of well-known mathematical models in finance, this paper introduces a risk measurement framework that coherently specifies all layers of the default waterfall resources of typical derivatives CCPs. The proposed framework gives the first risk sensitive definition of the CCP risk capital based on which less risk sensitive non-model-based methods can be evaluated.

Suggested Citation

  • Samim Ghamami, 2015. "Static models of central counterparty risk," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(02), pages 1-36.
    • Handle: RePEc:wsi:ijfexx:v:02:y:2015:i:02:n:s2424786315500115
    DOI: 10.1142/S2424786315500115
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    References listed on IDEAS

    as
    1. Samim Ghamami & Bo Zhang, 2014. "Efficient Monte Carlo Counterparty Credit Risk Pricing and Measurement," Finance and Economics Discussion Series 2014-114, Board of Governors of the Federal Reserve System (U.S.).
    2. Duffie, Darrell & Li, Ada & Lubke, Theo, 2010. "Policy Perspectives on OTC Derivatives Market Infrastructure," Research Papers 2046, Stanford University, Graduate School of Business.
    3. Theo Lubke & Ada Li & Darrell Duffie, 2010. "Policy perspectives on OTC derivatives market infrastructure," Staff Reports 424, Federal Reserve Bank of New York.
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    Citations

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    Cited by:

    1. Berndsen, Ron, 2020. "Five Fundamental Questions on Central Counterparties," Other publications TiSEM 1f3bd844-92ab-4104-8f57-9, Tilburg University, School of Economics and Management.
    2. Albanese Claudio & Armenti Yannick & Crépey Stéphane, 2020. "XVA metrics for CCP optimization," Statistics & Risk Modeling, De Gruyter, vol. 37(1-2), pages 25-53, January.
    3. Ghamami, Samim & Glasserman, Paul, 2017. "Does OTC derivatives reform incentivize central clearing?," Journal of Financial Intermediation, Elsevier, vol. 32(C), pages 76-87.
    4. Ron Berndsen, 2021. "Fundamental questions on central counterparties: A review of the literature," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2009-2022, December.
    5. Mark Paddrik & Simpson Zhang, 2019. "Central Counterparty Default Waterfalls and Systemic Loss," 2019 Meeting Papers 213, Society for Economic Dynamics.
    6. Tomasz R. Bielecki & Igor Cialenco & Shibi Feng, 2018. "A Dynamic Model of Central Counterparty Risk," Papers 1803.02012, arXiv.org.
    7. Stéphane Crépey, 2022. "Positive XVAs," Post-Print hal-03910135, HAL.
    8. Samim Ghamami & Paul Glasserman, 2016. "Does OTC Derivatives Reform Incentivize Central Clearing?," Working Papers 16-07, Office of Financial Research, US Department of the Treasury.
    9. Tomasz R. Bielecki & Igor Cialenco & Shibi Feng, 2018. "A Dynamic Model Of Central Counterparty Risk," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-34, December.

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