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Importance Sampling for Credit Portfolio Risk with Risk Factors Having t-Copula

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  • Rongda Chen

    (China Academy of Financial Research, Zhejiang University of Finance and Economics, Hangzhou 310018, China2School of Finance, Zhejiang University of Finance and Economics, Hangzhou 310018, China3Coordinated Innovation Center of Wealth Management and Quantitative Investment of Zhejiang University of Finance and Economics, Hangzhou 310018, China4Center for Research of Regulation and Policy of Zhejiang Province, Hangzhou 310018, China)

  • Ze Wang

    (School of Finance, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

  • Lean Yu

    (School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China)

Abstract

This paper proposes an efficient simulation method for calculating credit portfolio risk when risk factors have a heavy-tailed distributions. In modeling heavy tails, its features of return on underlying asset are captured by multivariate t-Copula. Moreover, we develop a three-step importance sampling (IS) procedure in the t-copula credit portfolio risk measure model for further variance reduction. Simultaneously, we apply the Levenberg–Marquardt algorithm associated with nonlinear optimization technique to solve the problem that estimates the mean-shift vector of the systematic risk factors after the probability measure change. Numerical results show that those methods developed in the t-copula model can produce large variance reduction relative to the plain Monte Carlo method, to estimate more accurately tail probability of credit portfolio loss distribution.

Suggested Citation

  • Rongda Chen & Ze Wang & Lean Yu, 2017. "Importance Sampling for Credit Portfolio Risk with Risk Factors Having t-Copula," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1101-1124, July.
    • Handle: RePEc:wsi:ijitdm:v:16:y:2017:i:04:n:s0219622017500201
    DOI: 10.1142/S0219622017500201
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    References listed on IDEAS

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    2. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Ren, Fei & He, Yun-Xing, 2018. "Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 301-310.

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