IDEAS home Printed from https://ideas.repec.org/a/wsi/ijtafx/v21y2018i08ns0219024918500504.html
   My bibliography  Save this article

A Dynamic Model Of Central Counterparty Risk

Author

Listed:
  • TOMASZ R. BIELECKI

    (Department of Applied Mathematics, Illinois Institute of Technology, 10 West 32nd Street, Building REC, Room 208, Chicago, IL 60616, USA)

  • IGOR CIALENCO

    (Department of Applied Mathematics, Illinois Institute of Technology, 10 West 32nd Street, Building REC, Room 208, Chicago, IL 60616, USA)

  • SHIBI FENG

    (Department of Applied Mathematics, Illinois Institute of Technology, 10 West 32nd Street, Building REC, Room 208, Chicago, IL 60616, USA)

Abstract

We introduce a dynamic model of the default waterfall of derivatives central counterparties and propose a risk sensitive method for sizing the initial margin, and the default fund and its allocation among clearing members. Using a Markovian structure model of joint credit migrations, our evaluation of the default fund takes into account the joint credit quality of clearing members as they evolve over time. Another important aspect of the proposed methodology is the use of the time consistent dynamic risk measures for computation of the initial margin and the default fund. We carry out a comprehensive numerical study, where, in particular, we analyze the advantages of the proposed methodology and its comparison with the currently prevailing methods used in industry.

Suggested Citation

  • 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.
  • Handle: RePEc:wsi:ijtafx:v:21:y:2018:i:08:n:s0219024918500504
    DOI: 10.1142/S0219024918500504
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219024918500504
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219024918500504?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Binbin Deng, 2017. "Counterparty risk, central counterparty clearing and aggregate risk," Annals of Finance, Springer, vol. 13(4), pages 355-400, November.
    2. Arnold, M., 2017. "The impact of central clearing on banks’ lending discipline," Journal of Financial Markets, Elsevier, vol. 36(C), pages 91-114.
    3. Yannick Armenti & Stéphane Crépey & Samuel Drapeau & Antonis Papapantoleon, 2018. "Multivariate Shortfall Risk Allocation and Systemic Risk," Working Papers hal-01764398, HAL.
    4. Tomasz R. Bielecki & Igor Cialenco & Marcin Pitera, 2014. "A unified approach to time consistency of dynamic risk measures and dynamic performance measures in discrete time," Papers 1409.7028, arXiv.org, revised Sep 2017.
    5. Paul Embrechts & Haiyan Liu & Tiantian Mao & Ruodu Wang, 2017. "Quantile-Based Risk Sharing with Heterogeneous Beliefs," Swiss Finance Institute Research Paper Series 17-65, Swiss Finance Institute, revised Jan 2018.
    6. Michael Kalkbrener, 2005. "An Axiomatic Approach To Capital Allocation," Mathematical Finance, Wiley Blackwell, vol. 15(3), pages 425-437, July.
    7. Tasche, Dirk, 2002. "Expected shortfall and beyond," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1519-1533, July.
    8. Marcell Béli & Kata Váradi, 2017. "A possible methodology for determining the initial margin," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 16(2), pages 119-147.
    9. Kai Detlefsen & Giacomo Scandolo, 2005. "Conditional and Dynamic Convex Risk Measures," SFB 649 Discussion Papers SFB649DP2005-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Ghamami, Samim & Glasserman, Paul, 2017. "Does OTC derivatives reform incentivize central clearing?," Journal of Financial Intermediation, Elsevier, vol. 32(C), pages 76-87.
    11. A. Cherny, 2006. "Weighted V@R and its Properties," Finance and Stochastics, Springer, vol. 10(3), pages 367-393, September.
    12. H Peyton Young & Mark Paddrik, 2017. "How Safe are Central Counterparties in Derivatives Markets?," Economics Series Working Papers 826, University of Oxford, Department of Economics.
    13. Tomasz R. Bielecki & Igor Cialenco & Marcin Pitera, 2016. "A survey of time consistency of dynamic risk measures and dynamic performance measures in discrete time: LM-measure perspective," Papers 1603.09030, arXiv.org, revised Jan 2017.
    14. Fischer, T., 2003. "Risk capital allocation by coherent risk measures based on one-sided moments," Insurance: Mathematics and Economics, Elsevier, vol. 32(1), pages 135-146, February.
    15. Vicente, L.A.B.G. & Cerezetti, F.V. & De Faria, S.R. & Iwashita, T. & Pereira, O.R., 2015. "Managing risk in multi-asset class, multimarket central counterparties: The CORE approach," Journal of Banking & Finance, Elsevier, vol. 51(C), pages 119-130.
    16. 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.
    17. Kai Detlefsen & Giacomo Scandolo, 2005. "Conditional and dynamic convex risk measures," Finance and Stochastics, Springer, vol. 9(4), pages 539-561, October.
    18. Bielecki, Tomasz R. & Jakubowski, Jacek & Niewęgłowski, Mariusz, 2017. "Conditional Markov chains: Properties, construction and structured dependence," Stochastic Processes and their Applications, Elsevier, vol. 127(4), pages 1125-1170.
    19. Alexander S. Cherny, 2009. "Capital Allocation And Risk Contribution With Discrete‐Time Coherent Risk," Mathematical Finance, Wiley Blackwell, vol. 19(1), pages 13-40, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tomasz R. Bielecki & Igor Cialenco & Marcin Pitera & Thorsten Schmidt, 2019. "Fair Estimation of Capital Risk Allocation," Papers 1902.10044, arXiv.org, revised Nov 2019.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tomasz R. Bielecki & Igor Cialenco & Shibi Feng, 2018. "A Dynamic Model of Central Counterparty Risk," Papers 1803.02012, arXiv.org.
    2. Alexander S. Cherny, 2009. "Capital Allocation And Risk Contribution With Discrete‐Time Coherent Risk," Mathematical Finance, Wiley Blackwell, vol. 19(1), pages 13-40, January.
    3. Elisa Mastrogiacomo & Emanuela Rosazza Gianin, 2019. "Time-consistency of risk measures: how strong is such a property?," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 287-317, June.
    4. Saul Jacka & Seb Armstrong & Abdel Berkaoui, 2017. "Multi-currency reserving for coherent risk measures," Papers 1712.01319, arXiv.org, revised Dec 2017.
    5. Guangyan Jia & Mengjin Zhao, 2022. "On the Correspondence and the Risk Contribution for Conditional Coherent and Deviation Risk Measures," Papers 2208.13336, arXiv.org, revised Feb 2023.
    6. Berndsen, Ron, 2020. "Five Fundamental Questions on Central Counterparties," Other publications TiSEM 1f3bd844-92ab-4104-8f57-9, Tilburg University, School of Economics and Management.
    7. Alessandro Doldi & Marco Frittelli, 2021. "Real-Valued Systemic Risk Measures," Mathematics, MDPI, vol. 9(9), pages 1-24, April.
    8. Tomasz R. Bielecki & Igor Cialenco & Marcin Pitera, 2018. "A Unified Approach to Time Consistency of Dynamic Risk Measures and Dynamic Performance Measures in Discrete Time," Mathematics of Operations Research, INFORMS, vol. 43(1), pages 204-221, February.
    9. Eduard Kromer & Ludger Overbeck, 2017. "DIFFERENTIABILITY OF BSVIEs AND DYNAMIC CAPITAL ALLOCATIONS," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(07), pages 1-26, November.
    10. Wang, Wei & Xu, Huifu & Ma, Tiejun, 2023. "Optimal scenario-dependent multivariate shortfall risk measure and its application in risk capital allocation," European Journal of Operational Research, Elsevier, vol. 306(1), pages 322-347.
    11. Cosimo Munari & Stefan Weber & Lutz Wilhelmy, 2023. "Capital requirements and claims recovery: A new perspective on solvency regulation," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(2), pages 329-380, June.
    12. Mitja Stadje, 2018. "Representation Results for Law Invariant Recursive Dynamic Deviation Measures and Risk Sharing," Papers 1811.09615, arXiv.org, revised Dec 2018.
    13. Tadese, Mekonnen & Drapeau, Samuel, 2020. "Relative bound and asymptotic comparison of expectile with respect to expected shortfall," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 387-399.
    14. Zachary Feinstein & Birgit Rudloff, 2018. "Time consistency for scalar multivariate risk measures," Papers 1810.04978, arXiv.org, revised Nov 2021.
    15. Jun Zhao & Emmanuel Lépinette & Peibiao Zhao, 2019. "Pricing under dynamic risk measures," Post-Print hal-02135232, HAL.
    16. Buch, A. & Dorfleitner, G., 2008. "Coherent risk measures, coherent capital allocations and the gradient allocation principle," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 235-242, February.
    17. Alessandro Doldi & Marco Frittelli, 2020. "Conditional Systemic Risk Measures," Papers 2010.11515, arXiv.org, revised May 2021.
    18. Tomasz R. Bielecki & Igor Cialenco & Marcin Pitera, 2016. "A survey of time consistency of dynamic risk measures and dynamic performance measures in discrete time: LM-measure perspective," Papers 1603.09030, arXiv.org, revised Jan 2017.
    19. Tomasz R. Bielecki & Igor Cialenco & Marcin Pitera, 2014. "A unified approach to time consistency of dynamic risk measures and dynamic performance measures in discrete time," Papers 1409.7028, arXiv.org, revised Sep 2017.
    20. E. Kromer & L. Overbeck & K. Zilch, 2019. "Dynamic systemic risk measures for bounded discrete time processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 90(1), pages 77-108, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:ijtafx:v:21:y:2018:i:08:n:s0219024918500504. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijtaf/ijtaf.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.