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On the formulation of credit barrier model using radial basis functions

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  • Humphrey K K Tung

    (City University of Hong Kong, Kowloon, Hong Kong)

  • Michael C S Wong

    (City University of Hong Kong, Kowloon, Hong Kong)

Abstract

Albanese et al in 2003 and Avellaneda and Zhu in 2001 develop the framework of credit barrier model. They provide special solutions to the model in case of simple stochastic structure. The technical aspect of the model remains wide open for general stochastic structure that is crucial when the model is required to calibrate with aggregate amount of empirical data. This paper provides a technical solution to this problem with the use of radial basis functions (RBF). This paper discusses the numerical implementation of the credit barrier model using the RBF method. It also demonstrates that the RBF method is numerically tractable in this problem and allows in the model richer stochastic structure capable of capturing relevant market information.

Suggested Citation

  • Humphrey K K Tung & Michael C S Wong, 2014. "On the formulation of credit barrier model using radial basis functions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(9), pages 1437-1452, September.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:9:p:1437-1452
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    Cited by:

    1. Weiwei Liu & Zhile Yang & Kexin Bi, 2017. "Forecasting the Acquisition of University Spin-Outs: An RBF Neural Network Approach," Complexity, Hindawi, vol. 2017, pages 1-8, October.

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