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PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps

Author

Listed:
  • Liu Xiangdong

    (Department of Statistics, Jinan University, Guangzhou510632, China)

  • Li Xianglong

    (Department of Statistics, Jinan University, Guangzhou510632, China)

  • Zheng Shaozhi

    (Department of Statistics, Jinan University, Guangzhou510632, China)

  • Qian Hangyong

    (Department of Statistics, Jinan University, Guangzhou510632, China)

Abstract

A parameter estimation method, called PMCMC in this paper, is proposed to estimate a continuous-time model of the term structure of interests under Markov regime switching and jumps. There is a closed form solution to term structure of interest rates under Markov regime. However, the model is extended to be a CKLS model with non-closed form solutions which is a typical nonlinear and non-Gaussian state-space model(SSM) in the case of adding jumps. Although the difficulty of parameter estimation greatly prevents from researching models, we prove that the nonlinear and non-Gaussian state-space model has better performances in studying volatility. The method proposed in this paper will be implemented in simulation and empirical study for SHIBOR. Empirical results illustrate that the PMCMC algorithm has powerful advantages in tackling the models.

Suggested Citation

  • Liu Xiangdong & Li Xianglong & Zheng Shaozhi & Qian Hangyong, 2020. "PMCMC for Term Structure of Interest Rates under Markov Regime Switching and Jumps," Journal of Systems Science and Information, De Gruyter, vol. 8(2), pages 159-169, April.
    • Handle: RePEc:bpj:jossai:v:8:y:2020:i:2:p:159-169:n:5
    DOI: 10.21078/JSSI-2020-159-11
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    References listed on IDEAS

    as
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