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Counterparty risk for CDS: Default clustering effects

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  • Bo, Lijun
  • Capponi, Agostino

Abstract

We derive a closed-form expression for the bilateral credit valuation adjustment of a credit default swap in presence of simultaneous defaults. We develop our analysis under a default intensity model specified by a class of three-dimensional subordinators, allowing for default dependence through common risk factors. We performance a suitable decomposition of the bilateral price into debit and credit valuation adjustment components. Those components do not have a symmetric impact on the price because of the joint event occurrences. Our analysis indicates that simultaneous defaults have material impact on the size and directionality of the adjustments. Our findings suggest policymakers to consider default clustering when designing counterparty valuation procedures, especially during periods of financial distress.

Suggested Citation

  • Bo, Lijun & Capponi, Agostino, 2015. "Counterparty risk for CDS: Default clustering effects," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 29-42.
    • Handle: RePEc:eee:jbfina:v:52:y:2015:i:c:p:29-42
    DOI: 10.1016/j.jbankfin.2014.11.010
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    References listed on IDEAS

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    1. S. Crépey & M. Jeanblanc & B. Zargari, 2010. "Counterparty Risk on a CDS in a Markov Chain Copula Model with Joint Defaults," World Scientific Book Chapters, in: Masaaki Kijima & Chiaki Hara & Keiichi Tanaka & Yukio Muromachi (ed.), Recent Advances In Financial Engineering 2009, chapter 4, pages 91-126, World Scientific Publishing Co. Pte. Ltd..
    2. Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, vol. 62(1), pages 93-117, February.
    3. Lijun Bo & Agostino Capponi, 2014. "Bilateral credit valuation adjustment for large credit derivatives portfolios," Finance and Stochastics, Springer, vol. 18(2), pages 431-482, April.
    4. Kay Giesecke & Baeho Kim, 2011. "Systemic Risk: What Defaults Are Telling Us," Management Science, INFORMS, vol. 57(8), pages 1387-1405, August.
    5. Masaaki Fujii & Akihiko Takahashi, 2012. "Collateralized CDS and Default Dependence -Implications for the Central Clearing," CARF F-Series CARF-F-281, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Francis A. Longstaff & Arvind Rajan, 2008. "An Empirical Analysis of the Pricing of Collateralized Debt Obligations," Journal of Finance, American Finance Association, vol. 63(2), pages 529-563, April.
    7. 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.
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    Citations

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    Cited by:

    1. Harb, Etienne & Louhichi, Wael, 2017. "Pricing CDS spreads with Credit Valuation Adjustment using a mixture copula," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 963-975.
    2. Stéphane Crépey & Shiqi Song, 2016. "Counterparty risk and funding: immersion and beyond," Finance and Stochastics, Springer, vol. 20(4), pages 901-930, October.
    3. 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).
    4. St'ephane Cr'epey & Shiqi Song, 2017. "Invariance times," Papers 1702.01045, arXiv.org.
    5. Tingqiang Chen & Binqing Xiao & Haifei Liu, 2018. "Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions," Complexity, Hindawi, vol. 2018, pages 1-16, March.
    6. J. C. Arismendi-Zambrano & Vladimir Belitsky & Vinicius Amorim Sobreiro & Herbert Kimura, 2020. "The Implications of Tail Dependency Measures for Counterparty Credit Risk Pricing," Economics Department Working Paper Series n306-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    7. Stéphane Crépey & Shiqi Song, 2017. "Invariance Times ," Working Papers hal-01455414, HAL.
    8. Stéphane Crépey & Shiqi Song, 2018. "Counterparty risk and funding: immersion and beyond," Working Papers hal-01764403, HAL.
    9. Lin, Feng & Peng, Liang & Xie, Jiehua & Yang, Jingping, 2018. "Stochastic distortion and its transformed copula," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 148-166.
    10. Wang, Lei & Li, Shouwei & Chen, Tingqiang, 2019. "Investor behavior, information disclosure strategy and counterparty credit risk contagion," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 37-49.
    11. Castellano, Rosella & Corallo, Vincenzo & Morelli, Giacomo, 2022. "Structural estimation of counterparty credit risk under recovery risk," Journal of Banking & Finance, Elsevier, vol. 140(C).

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    More about this item

    Keywords

    Counterparty risk; Simultaneous defaults; Multivariate subordinators; Credit default swaps;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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