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Joint survival probability via truncated invariant copula

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  • Kim, Jeong-Hoon
  • Ma, Yong-Ki
  • Park, Chan Yeol

Abstract

Given an intensity-based credit risk model, this paper studies dependence structure between default intensities. To model this structure, we use a multivariate shot noise intensity process, where jumps occur simultaneously and their sizes are correlated. Through very lengthy algebra, we obtain explicitly the joint survival probability of the integrated intensities by using the truncated invariant Farlie–Gumbel–Morgenstern copula with exponential marginal distributions. We also apply our theoretical result to pricing basket default swap spreads. This result can provide a useful guide for credit risk management.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:chsofr:v:85:y:2016:i:c:p:68-76
    DOI: 10.1016/j.chaos.2016.01.012
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    References listed on IDEAS

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    1. Herbertsson, Alexander & Jang, Jiwook & Schmidt, Thorsten, 2011. "Pricing basket default swaps in a tractable shot noise model," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1196-1207, August.
    2. Dassios, Angelos & Jang, Jiwook, 2003. "Pricing of catastrophe reinsurance and derivatives using the Cox process with shot noise intensity," LSE Research Online Documents on Economics 2849, London School of Economics and Political Science, LSE Library.
    3. 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.
    4. Yong-Ki Ma & Jeong-Hoon Kim, 2010. "Pricing the credit default swap rate for jump diffusion default intensity processes," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 809-817.
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    Cited by:

    1. See-Woo Kim & Yong-Ki Ma & Ciprian Necula, 2023. "Modeling Tail Dependence Using Stochastic Volatility Model," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 129-147, June.

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