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Modeling Credit Risk with Hidden Markov Default Intensity

Author

Listed:
  • Feng-Hui Yu

    (The University of Hong Kong)

  • Jiejun Lu

    (Harvard John A. Paulson School of Engineering and Applied Sciences)

  • Jia-Wen Gu

    (Southern University of Science and Technology)

  • Wai-Ki Ching

    (The University of Hong Kong
    Hughes Hall
    Beijing University of Chemical Technology)

Abstract

This paper investigates the modeling of credit default under an interactive reduced-form intensity-based model based on the Hidden Markov setting proposed in Yu et al. (Quant Finance 7(5):781–794, 2017). The intensities of defaults are determined by the hidden economic states which are governed by a Markov chain, as well as the past defaults. We estimate the parameters in the default intensity by using Expectation–Maximization algorithm with real market data under three different practical default models. Applications to pricing of credit default swap (CDS) is also discussed. Numerical experiments are conducted to compare the results under our models with real recession periods in US. The results demonstrate that our model is able to capture the hidden features and simulate credit default risks which are critical in risk management and the extracted hidden economic states are consistent with the real market data. In addition, we take pricing CDS as an example to illustrate the sensitivity analysis.

Suggested Citation

  • Feng-Hui Yu & Jiejun Lu & Jia-Wen Gu & Wai-Ki Ching, 2019. "Modeling Credit Risk with Hidden Markov Default Intensity," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 1213-1229, October.
    • Handle: RePEc:kap:compec:v:54:y:2019:i:3:d:10.1007_s10614-018-9869-7
    DOI: 10.1007/s10614-018-9869-7
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    1. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    2. Jia-Wen Gu & Bo Jiang & Wai-Ki Ching & Harry Zheng, 2016. "On Modeling Economic Default Time: A Reduced-Form Model Approach," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 157-177, February.
    3. Fan Yu, 2007. "Correlated Defaults In Intensity‐Based Models," Mathematical Finance, Wiley Blackwell, vol. 17(2), pages 155-173, April.
    4. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
    5. Feng-Hui Yu & Wai-Ki Ching & Jia-Wen Gu & Tak-Kuen Siu, 2017. "Interacting default intensity with a hidden Markov process," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 781-794, May.
    6. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2014. "Valuing risky debt: A new model combining structural information with the reduced-form approach," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 261-271.
    7. Harry Zheng & Lishang Jiang, 2009. "Basket CDS pricing with interacting intensities," Finance and Stochastics, Springer, vol. 13(3), pages 445-469, September.
    8. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    9. Rüdiger Frey & Wolfgang Runggaldier, 2010. "Pricing credit derivatives under incomplete information: a nonlinear-filtering approach," Finance and Stochastics, Springer, vol. 14(4), pages 495-526, December.
    10. Kay Giesecke & Lisa R. Goldberg & Xiaowei Ding, 2011. "A Top-Down Approach to Multiname Credit," Operations Research, INFORMS, vol. 59(2), pages 283-300, April.
    11. Shaked, Moshe & George Shanthikumar, J., 1987. "The multivariate hazard construction," Stochastic Processes and their Applications, Elsevier, vol. 24(2), pages 241-258, May.
    12. Francis A. Longstaff & Arvind Rajan, 2008. "An Empirical Analysis of the Pricing of Collateralized Debt Obligations," Journal of Finance, American Finance Association, vol. 63(2), pages 529-563, April.
    13. Giacomo Giampieri & Mark Davis & Martin Crowder, 2005. "Analysis of default data using hidden Markov models," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 27-34.
    14. Robert A. Jarrow & Fan Yu, 2008. "Counterparty Risk and the Pricing of Defaultable Securities," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 20, pages 481-515, World Scientific Publishing Co. Pte. Ltd..
    15. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    16. Luca Vincenzo Ballestra & Graziella Pacelli & Davide Radi, 2017. "Computing the survival probability in the Madan–Unal credit risk model: application to the CDS market," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 299-313, February.
    17. Jia-Wen Gu & Wai-Ki Ching & Tak-Kuen Siu & Harry Zheng, 2013. "On pricing basket credit default swaps," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1845-1854, December.
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