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Pricing CDS spreads with Credit Valuation Adjustment using a mixture copula

Listed author(s):
  • Harb, Etienne
  • Louhichi, Wael
Registered author(s):

    Credit derivatives pricing models before Basel III ignored losses in market value stemming from higher probability of counterparty default. We propose a general credit derivatives pricing model to evaluate a Credit Default Swap (CDS) with counterparty risk, including the Credit Valuation Adjustment (CVA) in order to optimize the economic capital allocation. We work from the model proposed by Luciano (2003, Working Paper, International Center of Economic Research) and the general pricing representation established by Sorensen and Bollier (Financial Analysts Journal 1994;50(3):23–33) to provide a model close to the market practice, easy to implement and fitting with Basel III framework. We approach the dependence between counterparty risk and that of the reference entity with a technical tool: the copula, in particular, the mixture one that combines common “extreme” copulas. We study the CDS's vulnerability in extreme dependence cases. By varying Spearman's rho, the mixture copula covers a broad spectrum of dependence and ensures closed form prices. We end up with an application on real market data.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0275531916300319
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    Article provided by Elsevier in its journal Research in International Business and Finance.

    Volume (Year): 39 (2017)
    Issue (Month): PB ()
    Pages: 963-975

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    Handle: RePEc:eee:riibaf:v:39:y:2017:i:pb:p:963-975
    DOI: 10.1016/j.ribaf.2016.02.003
    Contact details of provider: Web page: http://www.elsevier.com/locate/ribaf

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    1. Arora, Navneet & Gandhi, Priyank & Longstaff, Francis A., 2012. "Counterparty credit risk and the credit default swap market," Journal of Financial Economics, Elsevier, vol. 103(2), pages 280-293.
    2. Giesecke, Kay, 2004. "Correlated default with incomplete information," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1521-1545, July.
    3. Dong, Yinghui & Wang, Guojing, 2014. "Bilateral counterparty risk valuation for credit default swap in a contagion model using Markov chain," Economic Modelling, Elsevier, vol. 40(C), pages 91-100.
    4. U. Cherubini & E. Luciano, 2002. "Bivariate option pricing with copulas," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(2), pages 69-85.
    5. Kim, Jinbeom & Leung, Tim, 2016. "Pricing derivatives with counterparty risk and collateralization: A fixed point approach," European Journal of Operational Research, Elsevier, vol. 249(2), pages 525-539.
    6. Cherubini, Umberto & Mulinacci, Sabrina & Romagnoli, Silvia, 2011. "A copula-based model of speculative price dynamics in discrete time," Journal of Multivariate Analysis, Elsevier, vol. 102(6), pages 1047-1063, July.
    7. Umberto Cherubini & Elisa Luciano, 2003. "Pricing and Hedging Credit Derivatives with Copulas," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 32(2), pages 219-242, 07.
    8. 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, 01.
    9. Dong, Yinghui & Yuen, Kam C. & Wu, Chongfeng, 2014. "Unilateral counterparty risk valuation of CDS using a regime-switching intensity model," Statistics & Probability Letters, Elsevier, vol. 85(C), pages 25-35.
    10. Bo, Lijun & Capponi, Agostino, 2015. "Counterparty risk for CDS: Default clustering effects," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 29-42.
    11. Christophette Blanchet-Scalliet & Fr\'ed\'eric Patras, 2008. "Counterparty risk valuation for CDS," Papers 0807.0309, arXiv.org.
    12. Michael S. Gibson, 2005. "Measuring counterparty credit exposure to a margined counterparty," Finance and Economics Discussion Series 2005-50, Board of Governors of the Federal Reserve System (U.S.).
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