IDEAS home Printed from https://ideas.repec.org/p/ofr/wpaper/15-16.html
   My bibliography  Save this paper

Bounding Wrong-Way Risk in Measuring Counterparty Risk

Author

Listed:
  • Paul Glasserman

    (Columbia University)

  • Linan Yang

    (Columbia University)

Abstract

Counterparty risk measurement integrates two sources of risk: market risk, which determines the size of a firm's exposure to a counterparty, and credit risk, which reflects the likelihood that the counterparty will default on its obligations. Wrong-way risk refers to the possibility that a counterparty's default risk increases with the market value of the exposure. We investigate the potential impact of wrong-way risk in calculating a credit valuation adjustment (CVA) to a derivatives portfolio: CVA has become a standard tool for pricing counterparty risk and setting associated capital requirements. We present a method, introduced in our earlier work, for bounding the impact of wrong-way risk on CVA. The method holds fixed marginal models for market and credit risk while varying the dependence between them. Given simulated paths of the two models, we solve a linear program to find the worst-case CVA resulting from wrongway risk. The worst case can be overly conservative, so we extend the procedure by penalizing deviations of the joint model from a baseline model. By varying the penalty for deviations, we can sweep out the full range of possible CVA values for different degrees of wrong-way risk. Our method addresses an important source of model risk in counterparty risk measurement.

Suggested Citation

  • Paul Glasserman & Linan Yang, 2015. "Bounding Wrong-Way Risk in Measuring Counterparty Risk," Working Papers 15-16, Office of Financial Research, US Department of the Treasury.
  • Handle: RePEc:ofr:wpaper:15-16
    as

    Download full text from publisher

    File URL: https://www.financialresearch.gov/working-papers/files/OFRwp-2015-16_Wrong-Way-Risk-in-Measuring-Counterparty-Risk.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Friedrich Pukelsheim, 2014. "Biproportional scaling of matrices and the iterative proportional fitting procedure," Annals of Operations Research, Springer, vol. 215(1), pages 269-283, April.
    2. Damiano Brigo & Agostino Capponi & Andrea Pallavicini, 2014. "Arbitrage-Free Bilateral Counterparty Risk Valuation Under Collateralization And Application To Credit Default Swaps," Mathematical Finance, Wiley Blackwell, vol. 24(1), pages 125-146, January.
    3. Samim Ghamami & Lisa R. Goldberg, 2014. "Stochastic Intensity Models of Wrong Way Risk: Wrong Way CVA Need Not Exceed Independent CVA," Finance and Economics Discussion Series 2014-54, Board of Governors of the Federal Reserve System (U.S.).
    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. Derek Singh & Shuzhong Zhang, 2019. "Distributionally Robust XVA via Wasserstein Distance Part 2: Wrong Way Funding Risk," Papers 1910.03993, arXiv.org.
    2. Derek Singh & Shuzhong Zhang, 2020. "Distributionally Robust XVA via Wasserstein Distance: Wrong Way Counterparty Credit and Funding Risk," Applied Economics and Finance, Redfame publishing, vol. 7(6), pages 70-100, December.
    3. Janis Müller & Peter N. Posch, 2018. "Wrong-way-risk in tails," Journal of Asset Management, Palgrave Macmillan, vol. 19(4), pages 205-215, July.
    4. Derek Singh & Shuzhong Zhang, 2019. "Distributionally Robust XVA via Wasserstein Distance: Wrong Way Counterparty Credit and Funding Risk," Papers 1910.01781, arXiv.org, revised May 2020.

    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. Alessandro Gnoatto & Athena Picarelli & Christoph Reisinger, 2020. "Deep xVA solver -- A neural network based counterparty credit risk management framework," Papers 2005.02633, arXiv.org, revised Dec 2022.
    2. Frédéric Vrins, 2017. "Wrong-Way Risk Cva Models With Analytical Epe Profiles Under Gaussian Exposure Dynamics," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(07), pages 1-35, November.
    3. Cheikh Mbaye & Frédéric Vrins, 2022. "Affine term structure models: A time‐change approach with perfect fit to market curves," Mathematical Finance, Wiley Blackwell, vol. 32(2), pages 678-724, April.
    4. Akari, Mohamed-Ali & Ben-Abdallah, Ramzi & Breton, Michèle & Dionne, Georges, 2021. "The impact of central clearing on the market for single-name credit default swaps," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    5. Lorenzo Silotto & Marco Scaringi & Marco Bianchetti, 2024. "XVA modelling: validation, performance and model risk management," Annals of Operations Research, Springer, vol. 336(1), pages 183-274, May.
    6. BRIGO, Damiano & VRINS, Frédéric, 2018. "Disentangling wrong-way risk: pricing credit valuation adjustment via change of measures," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1154-1164.
    7. Kerem Akartunalı & Philip A. Knight, 2017. "Network models and biproportional rounding for fair seat allocations in the UK elections," Annals of Operations Research, Springer, vol. 253(1), pages 1-19, June.
    8. Luke M. Bennett & Wei Hu, 2023. "Filtration enlargement‐based time series forecast in view of insider trading," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 112-140, February.
    9. St'ephane Cr'epey & Shiqi Song, 2017. "Invariance times," Papers 1702.01045, arXiv.org.
    10. Enrico Biffis & David Blake & Lorenzo Pitotti & Ariel Sun, 2016. "The Cost of Counterparty Risk and Collateralization in Longevity Swaps," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(2), pages 387-419, June.
    11. Damiano Brigo & Nicola Pede & Andrea Petrelli, 2015. "Multi Currency Credit Default Swaps Quanto effects and FX devaluation jumps," Papers 1512.07256, arXiv.org, revised Jan 2018.
    12. Francesca Biagini & Alessandro Gnoatto & Immacolata Oliva, 2019. "Pricing of counterparty risk and funding with CSA discounting, portfolio effects and initial margin," Working Papers 04/2019, University of Verona, Department of Economics.
    13. Xingchun Wang, 2016. "The Pricing of Catastrophe Equity Put Options with Default Risk," International Review of Finance, International Review of Finance Ltd., vol. 16(2), pages 181-201, June.
    14. Arismendi-Zambrano, Juan & Belitsky, Vladimir & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2022. "The implications of dependence, tail dependence, and bounds’ measures for counterparty credit risk pricing," Journal of Financial Stability, Elsevier, vol. 58(C).
    15. Wang, Guanying & Wang, Xingchun & Zhou, Ke, 2017. "Pricing vulnerable options with stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 485(C), pages 91-103.
    16. Zhaonan Qu & Alfred Galichon & Wenzhi Gao & Johan Ugander, 2023. "On Sinkhorn's Algorithm and Choice Modeling," Papers 2310.00260, arXiv.org, revised Apr 2025.
    17. Brigo, Damiano & Francischello, Marco & Pallavicini, Andrea, 2019. "Nonlinear valuation under credit, funding, and margins: Existence, uniqueness, invariance, and disentanglement," European Journal of Operational Research, Elsevier, vol. 274(2), pages 788-805.
    18. Ballotta, Laura & Fusai, Gianluca & Marazzina, Daniele, 2019. "Integrated structural approach to Credit Value Adjustment," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1143-1157.
    19. Chaofan Sun & Ken Seng Tan & Wei Wei, 2022. "Credit Valuation Adjustment with Replacement Closeout: Theory and Algorithms," Papers 2201.09105, arXiv.org, revised Jan 2022.
    20. Francesca Biagini & Alessandro Gnoatto & Katharina Oberpriller, 2025. "When defaults cannot be hedged: an actuarial approach to xVA calculations via local risk-minimization," Papers 2502.12774, arXiv.org, revised Feb 2025.

    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:ofr:wpaper:15-16. 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: Corey Garriott (email available below). General contact details of provider: https://edirc.repec.org/data/ofrgvus.html .

    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.