IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1201.0111.html
   My bibliography  Save this paper

A CDS Option Miscellany

Author

Listed:
  • Richard J Martin

Abstract

CDS options allow investors to express a view on spread volatility and obtain a wider range of payoffs than are possible with vanilla CDS. We give a detailed exposition of different types of single-name CDS option, including options with upfront protection payment, recovery options and recovery swaps, and also presents a new formula for the index option. The emphasis is on using the Black-76 formula where possible and ensuring consistency within asset classes. In the framework shown here the `armageddon event' does not require special attention.

Suggested Citation

  • Richard J Martin, 2011. "A CDS Option Miscellany," Papers 1201.0111, arXiv.org, revised May 2019.
    • Handle: RePEc:arx:papers:1201.0111
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1201.0111
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hatem Ben-Ameur & Damiano Brigo & Eymen Errais, 2009. "A dynamic programming approach for pricing CDS and CDS options," Quantitative Finance, Taylor & Francis Journals, vol. 9(6), pages 717-726.
    2. Bruche, Max & González-Aguado, Carlos, 2010. "Recovery rates, default probabilities, and the credit cycle," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
    3. Damiano Brigo & Naoufel El-Bachir, 2007. "An exact formula for default swaptions' pricing in the SSRJD stochastic intensity model," ICMA Centre Discussion Papers in Finance icma-dp2007-14, Henley Business School, University of Reading.
    4. Dirk Tasche, 2004. "The single risk factor approach to capital charges in case of correlated loss given default rates," Papers cond-mat/0402390, arXiv.org, revised Feb 2004.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    2. Gourieroux, Christian & Lu, Yang, 2019. "Least impulse response estimator for stress test exercises," Journal of Banking & Finance, Elsevier, vol. 103(C), pages 62-77.
    3. Andrea Cipollini & Giuseppe Missaglia, 2008. "Measuring bank capital requirements through Dynamic Factor analysis," Center for Economic Research (RECent) 010, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    4. Ildiko Orban & Oday Tamimi, 2020. "Accounting Model for Impairment under IFRS 9 and its Impact on Loss Allowance," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1259-1277.
    5. Thamayanthi Chellathurai, 2017. "Probability Density Of Recovery Rate Given Default Of A Firm’S Debt And Its Constituent Tranches," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
    6. Rösch, Daniel & Scheule, Harald, 2009. "The Empirical Relation between Credit Quality, Recovery and Correlation," Hannover Economic Papers (HEP) dp-418, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Tomas Konecny & Jakub Seidler & Aelta Belyaeva & Konstantin Belyaev, 2017. "The Time Dimension of the Links Between Loss Given Default and the Macroeconomy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(6), pages 462-491, October.
    8. Hasan, Iftekhar & Politsidis, Panagiotis N. & Sharma, Zenu, 2021. "Global syndicated lending during the COVID-19 pandemic," Journal of Banking & Finance, Elsevier, vol. 133(C).
    9. Mora, Nada, 2015. "Creditor recovery: The macroeconomic dependence of industry equilibrium," Journal of Financial Stability, Elsevier, vol. 18(C), pages 172-186.
    10. Wu, Yang-Che & Chung, San-Lin, 2010. "Catastrophe risk management with counterparty risk using alternative instruments," Insurance: Mathematics and Economics, Elsevier, vol. 47(2), pages 234-245, October.
    11. Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.
    12. Rafael Repullo & Javier Suarez, 2013. "The Procyclical Effects of Bank Capital Regulation," The Review of Financial Studies, Society for Financial Studies, vol. 26(2), pages 452-490.
    13. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," Economic Modelling, Elsevier, vol. 125(C).
    14. Doumpos, Michalis & Andriosopoulos, Kostas & Galariotis, Emilios & Makridou, Georgia & Zopounidis, Constantin, 2017. "Corporate failure prediction in the European energy sector: A multicriteria approach and the effect of country characteristics," European Journal of Operational Research, Elsevier, vol. 262(1), pages 347-360.
    15. Giuseppe Orlando & Roberta Pelosi, 2020. "Non-Performing Loans for Italian Companies: When Time Matters. An Empirical Research on Estimating Probability to Default and Loss Given Default," IJFS, MDPI, vol. 8(4), pages 1-22, November.
    16. Charitou, Andreas & Dionysiou, Dionysia & Lambertides, Neophytos & Trigeorgis, Lenos, 2013. "Alternative bankruptcy prediction models using option-pricing theory," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2329-2341.
    17. Repullo, Rafael & Suarez, Javier, 2008. "The Procyclical Effects of Basel II," CEPR Discussion Papers 6862, C.E.P.R. Discussion Papers.
    18. Devjak Srečko, 2018. "Modeling of Cash Flows from Nonperforming Loans in a Commercial Bank," Naše gospodarstvo/Our economy, Sciendo, vol. 64(4), pages 3-9, December.
    19. Janette Larney & Gerrit Lodewicus Grobler & James Samuel Allison, 2022. "Introducing Two Parsimonious Standard Power Mixture Models for Bimodal Proportional Data with Application to Loss Given Default," Mathematics, MDPI, vol. 10(23), pages 1-19, November.
    20. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, July.

    More about this item

    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:arx:papers:1201.0111. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.