IDEAS home Printed from https://ideas.repec.org/p/tiu/tiutis/39f37d9b-7b60-4d46-9608-dc8fc24410ae.html
   My bibliography  Save this paper

Why Is a CCP failure very unlikely?

Author

Listed:
  • McLaughlin, Dennis
  • Berndsen, Ron

    (Tilburg University, School of Economics and Management)

Abstract

No abstract is available for this item.

Suggested Citation

  • McLaughlin, Dennis & Berndsen, Ron, 2021. "Why Is a CCP failure very unlikely?," Other publications TiSEM 39f37d9b-7b60-4d46-9608-d, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:39f37d9b-7b60-4d46-9608-dc8fc24410ae
    as

    Download full text from publisher

    File URL: https://pure.uvt.nl/ws/portalfiles/portal/46839740/2021_002.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Berndsen, Ron, 2020. "Five Fundamental Questions on Central Counterparties," Discussion Paper 2020-028, Tilburg University, Center for Economic Research.
    2. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
    3. 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.
    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. Bardoscia, Marco & Ferrara, Gerardo & Vause, Nicholas & Yoganayagam, Michael, 2021. "Simulating liquidity stress in the derivatives market," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    2. Bardoscia, Marco & Caccioli, Fabio & Gao, Haotian, 2022. "Efficiency of central clearing under liquidity stress," Bank of England working papers 1002, Bank of England.
    3. Melinda Friesz & Kira Muratov-Szabó & Andrea Prepuk & Kata Váradi, 2021. "Risk Mutualization in Central Clearing: An Answer to the Cross-Guarantee Phenomenon from the Financial Stability Viewpoint," Risks, MDPI, vol. 9(8), pages 1-19, August.

    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. 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.
    2. Bardoscia, Marco & Caccioli, Fabio & Gao, Haotian, 2022. "Efficiency of central clearing under liquidity stress," Bank of England working papers 1002, Bank of England.
    3. Stefan Mittnik & Sandra Paterlini & Tina Yener, 2011. "Operational–risk Dependencies and the Determination of Risk Capital," Center for Economic Research (RECent) 070, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    4. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    5. Hamed Amini & Maxim Bichuch & Zachary Feinstein, 2021. "Decentralized Payment Clearing using Blockchain and Optimal Bidding," Papers 2109.00446, arXiv.org, revised Jan 2022.
    6. Robert Jarrow & Jeff Oxman & Yildiray Yildirim, 2010. "The cost of operational risk loss insurance," Review of Derivatives Research, Springer, vol. 13(3), pages 273-295, October.
    7. Antinolfi, Gaetano & Carapella, Francesca & Carli, Francesco, 2022. "Transparency and collateral: central versus bilateral clearing," Theoretical Economics, Econometric Society, vol. 17(1), January.
    8. J. Christopher Westland, 2015. "Economics of eBay’s buyer protection plan," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-20, December.
    9. S�verine Plunus & Georges Hübner & Jean-Philippe Peters, 2012. "Measuring operational risk in financial institutions," Applied Financial Economics, Taylor & Francis Journals, vol. 22(18), pages 1553-1569, September.
    10. Ikefuji, Masako & Laeven, Roger J.A. & Magnus, Jan R. & Muris, Chris, 2020. "Expected utility and catastrophic risk in a stochastic economy–climate model," Journal of Econometrics, Elsevier, vol. 214(1), pages 110-129.
    11. Lu, Zhaoyang, 2011. "Modeling the yearly Value-at-Risk for operational risk in Chinese commercial banks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(4), pages 604-616.
    12. Melinda Friesz & Kira Muratov-Szabó & Andrea Prepuk & Kata Váradi, 2021. "Risk Mutualization in Central Clearing: An Answer to the Cross-Guarantee Phenomenon from the Financial Stability Viewpoint," Risks, MDPI, vol. 9(8), pages 1-19, August.
    13. Giuseppe Galloppo & Alessandro Rogora, 2011. "What Has Worked In Operational Risk?," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 5(3), pages 1-17.
    14. Pflug Georg Ch. & Schaller Peter, 2009. "A note on pivotal Value-at-Risk estimates," Statistics & Risk Modeling, De Gruyter, vol. 27(3), pages 201-209, December.
    15. Stefan Aulbach & Verena Bayer & Michael Falk, 2012. "A multivariate piecing-together approach with an application to operational loss data," Papers 1205.1617, arXiv.org.
    16. Mainik Georg & Rüschendorf Ludger, 2012. "Ordering of multivariate risk models with respect to extreme portfolio losses," Statistics & Risk Modeling, De Gruyter, vol. 29(1), pages 73-106, March.
    17. Gambacorta, Leonardo, 2008. "How do banks set interest rates?," European Economic Review, Elsevier, vol. 52(5), pages 792-819, July.
    18. Injun Hwang & Baeho Kim, 2020. "Heterogeneity and netting efficiency under central clearing: A stochastic network analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(2), pages 192-208, February.
    19. Xiaolin Luo & Pavel V. Shevchenko & John B. Donnelly, 2009. "Addressing the Impact of Data Truncation and Parameter Uncertainty on Operational Risk Estimates," Papers 0904.2910, arXiv.org.
    20. Dermot Turing & Mr. Manmohan Singh, 2018. "The Morning After--The Impact on Collateral Supply After a Major Default," IMF Working Papers 2018/228, International Monetary Fund.

    More about this item

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General

    Statistics

    Access and download statistics

    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:tiu:tiutis:39f37d9b-7b60-4d46-9608-dc8fc24410ae. 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: Richard Broekman (email available below). General contact details of provider: https://www.tilburguniversity.edu/about/schools/economics-and-management/ .

    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.