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Efficient algorithms for basket default swap pricing with multivariate Archimedean copulas

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  • Choe, Geon Ho
  • Jang, Hyun Jin

Abstract

We introduce a new importance sampling method for pricing basket default swaps employing exchangeable Archimedean copulas and nested Gumbel copulas. We establish more realistic dependence structures than existing copula models for credit risks in the underlying portfolio, and propose an appropriate density for importance sampling by analyzing multivariate Archimedean copulas. To justify efficiency and accuracy of the proposed algorithms, we present numerical examples and compare them with the crude Monte Carlo simulation, and finally show that our proposed estimators produce considerably smaller variances.

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  • 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.
    • Handle: RePEc:eee:insuma:v:48:y:2011:i:2:p:205-213
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    References listed on IDEAS

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    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. Niall Whelan, 2004. "Sampling from Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, vol. 4(3), pages 339-352.
    3. Zhiyong Chen & Paul Glasserman, 2008. "Fast Pricing of Basket Default Swaps," Operations Research, INFORMS, vol. 56(2), pages 286-303, April.
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    Cited by:

    1. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    2. Henry Penikas, 2014. "Investment portfolio risk modelling based on hierarchical copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 18-38.
    3. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management," Energy Economics, Elsevier, vol. 42(C), pages 332-342.
    4. Lei, Lei & Peng, Yijie & Fu, Michael C. & Hu, Jian-Qiang, 2023. "Copula sensitivity analysis for portfolio credit derivatives," European Journal of Operational Research, Elsevier, vol. 308(1), pages 455-466.
    5. Choe, Geon Ho & Choi, So Eun & Jang, Hyun Jin, 2020. "Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    6. Aloui, Riadh & Gupta, Rangan & Miller, Stephen M., 2016. "Uncertainty and crude oil returns," Energy Economics, Elsevier, vol. 55(C), pages 92-100.
    7. Koirala, Krishna H. & Mishra, Ashok K. & D'Antoni, Jeremy M. & Mehlhorn, Joey E., 2015. "Energy prices and agricultural commodity prices: Testing correlation using copulas method," Energy, Elsevier, vol. 81(C), pages 430-436.
    8. Geon Ho Choe & Hyun Jin Jang & Soon Won Kwon, 2015. "A factor contagion model for portfolio credit derivatives," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1571-1582, September.
    9. 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.
    10. Kim, Jeong-Hoon & Ma, Yong-Ki & Park, Chan Yeol, 2016. "Joint survival probability via truncated invariant copula," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 68-76.

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