IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v56y2008i2p286-303.html
   My bibliography  Save this article

Fast Pricing of Basket Default Swaps

Author

Listed:
  • Zhiyong Chen

    (Financial Analytics and Structured Transactions Group, Bear Stearns and Company Inc., New York, New York 10179)

  • Paul Glasserman

    (Graduate School of Business, Columbia University, New York, New York 10027)

Abstract

A basket default swap is a derivative security tied to an underlying basket of corporate bonds or other assets subject to credit risk. The value of the contract depends on the joint distribution of the default times of the underlying assets. Valuing a basket default swap often entails Monte Carlo simulation of these default times. For baskets of high-quality credits and for swaps that require multiple defaults to trigger payment, pricing the swap is a rare-event simulation problem. The Joshi-Kainth algorithm is an innovative importance-sampling technique for this problem that forces a predetermined number of defaults to occur on each path. This paper analyzes, extends, and improves the Joshi-Kainth algorithm. We show that, in its original form, the algorithm can actually increase variance; we present an alternative that is guaranteed to reduce variance, even when defaults are not rare. Along the way, we provide a rigorous underpinning in a setting sufficiently general to include both the original method and the version proposed here.

Suggested Citation

  • Zhiyong Chen & Paul Glasserman, 2008. "Fast Pricing of Basket Default Swaps," Operations Research, INFORMS, vol. 56(2), pages 286-303, April.
    • Handle: RePEc:inm:oropre:v:56:y:2008:i:2:p:286-303
    DOI: 10.1287/opre.1070.0456
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.1070.0456
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.1070.0456?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mark Joshi & Dherminder Kainth, 2004. "Rapid and accurate development of prices and Greeks for nth to default credit swaps in the Li model," Quantitative Finance, Taylor & Francis Journals, vol. 4(3), pages 266-275.
    2. Paul Glasserman & Jingyi Li, 2005. "Importance Sampling for Portfolio Credit Risk," Management Science, INFORMS, vol. 51(11), pages 1643-1656, November.
    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. Huei-Wen Teng & Cheng-Der Fuh & Chun-Chieh Chen, 2016. "On an automatic and optimal importance sampling approach with applications in finance," Quantitative Finance, Taylor & Francis Journals, vol. 16(8), pages 1259-1271, August.
    2. Zhiyong Chen & Paul Glasserman, 2008. "Sensitivity estimates for portfolio credit derivatives using Monte Carlo," Finance and Stochastics, Springer, vol. 12(4), pages 507-540, October.
    3. Guangwu Liu, 2015. "Simulating Risk Contributions of Credit Portfolios," Operations Research, INFORMS, vol. 63(1), pages 104-121, February.
    4. Yang Deng & Helen X. H. Bao & Pu Gong, 2018. "Increased Tail Dependence in Global Public Real Estate Markets," International Real Estate Review, Global Social Science Institute, vol. 21(2), pages 145-168.
    5. Kay Giesecke & Baeho Kim, 2011. "Risk Analysis of Collateralized Debt Obligations," Operations Research, INFORMS, vol. 59(1), pages 32-49, February.
    6. Choe, Geon Ho & Jang, Hyun Jin, 2011. "Efficient algorithms for basket default swap pricing with multivariate Archimedean copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 205-213, March.
    7. Biagini, Francesca & Mazzon, Andrea & Oberpriller, Katharina, 2023. "Reduced-form framework for multiple ordered default times under model uncertainty," Stochastic Processes and their Applications, Elsevier, vol. 156(C), pages 1-43.

    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. Grundke, Peter, 2009. "Importance sampling for integrated market and credit portfolio models," European Journal of Operational Research, Elsevier, vol. 194(1), pages 206-226, April.
    2. Guangwu Liu, 2015. "Simulating Risk Contributions of Credit Portfolios," Operations Research, INFORMS, vol. 63(1), pages 104-121, February.
    3. Han, Chulwoo & Park, Frank C., 2022. "A geometric framework for covariance dynamics," Journal of Banking & Finance, Elsevier, vol. 134(C).
    4. Gerardo Manzo & Antonio Picca, 2020. "The Impact of Sovereign Shocks," Management Science, INFORMS, vol. 66(7), pages 3113-3132, July.
    5. Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
    6. İsmail Başoğlu & Wolfgang Hörmann & Halis Sak, 2018. "Efficient simulations for a Bernoulli mixture model of portfolio credit risk," Annals of Operations Research, Springer, vol. 260(1), pages 113-128, January.
    7. Fathi, Abid & Nader, Naifar, 2007. "Price Calibration of basket default swap: Evidence from Japanese market," MPRA Paper 6013, University Library of Munich, Germany.
    8. Busch, Ramona & Koziol, Philipp & Mitrovic, Marc, 2015. "Many a little makes a mickle: Macro portfolio stress test for small and medium-sized German banks," Discussion Papers 23/2015, Deutsche Bundesbank.
    9. Choe, Geon Ho & Jang, Hyun Jin, 2011. "Efficient algorithms for basket default swap pricing with multivariate Archimedean copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 205-213, March.
    10. Huang, Xin & Zhou, Hao & Zhu, Haibin, 2012. "Assessing the systemic risk of a heterogeneous portfolio of banks during the recent financial crisis," Journal of Financial Stability, Elsevier, vol. 8(3), pages 193-205.
    11. Anand Deo & Sandeep Juneja, 2021. "Credit Risk: Simple Closed-Form Approximate Maximum Likelihood Estimator," Operations Research, INFORMS, vol. 69(2), pages 361-379, March.
    12. Ikeda, Yuki, 2021. "Efficient Computation of Portfolio Credit Risk with Chain Default," MPRA Paper 106652, University Library of Munich, Germany.
    13. Puzanova, Natalia & Düllmann, Klaus, 2013. "Systemic risk contributions: A credit portfolio approach," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1243-1257.
    14. Andrei Rusu, 2020. "Multivariate VaR: A Romanian Market study," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 12(1), pages 79-95, June.
    15. Ping Li & Ze†Zheng Li, 2015. "Change Analysis for the Dependence Structure and Dynamic Pricing of Basket Default Swaps," European Financial Management, European Financial Management Association, vol. 21(4), pages 646-671, September.
    16. Black, Lamont & Correa, Ricardo & Huang, Xin & Zhou, Hao, 2016. "The systemic risk of European banks during the financial and sovereign debt crises," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 107-125.
    17. Spiliopoulos, Konstantinos & Sowers, Richard B., 2011. "Recovery rates in investment-grade pools of credit assets: A large deviations analysis," Stochastic Processes and their Applications, Elsevier, vol. 121(12), pages 2861-2898.
    18. Mohamed A. Ayadi & Hatem Ben-Ameur & Nabil Channouf & Quang Khoi Tran, 2019. "NORTA for portfolio credit risk," Annals of Operations Research, Springer, vol. 281(1), pages 99-119, October.
    19. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    20. Henry Lam & Clementine Mottet, 2017. "Tail Analysis Without Parametric Models: A Worst-Case Perspective," Operations Research, INFORMS, vol. 65(6), pages 1696-1711, December.

    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:inm:oropre:v:56:y:2008:i:2:p:286-303. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.