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Regime-Switching Univariate Diffusion Models of the Short-Term Interest Rate


  • Choi Seungmoon

    () (University of Adelaide)


This article proposes a general regime-switching univariate diffusion model to describe the dynamics of the short-term interest rate. The maximum likelihood estimates are obtained using the weekly series of U.S. three-month treasury bill rates. The estimation results reveal that there are strong evidences for the existence of high and low volatility regimes, for the time varying transition probability of the regime variable, and for the high persistence of both regimes. In both regimes, the volatility, but not the drift, is estimated accurately and plays a key role in explaining the dynamics of the interest rates. High persistence's and different volatilities of two regimes can well explain volatility clustering observed in the data. Based on the inferred probability of the process being in each regime, most of the high volatility periods correspond to some historic events. The likelihood-based test shows that misspecification can result in misleading outcomes particularly regarding the volatility and transition probabilities of the regime index.

Suggested Citation

  • Choi Seungmoon, 2009. "Regime-Switching Univariate Diffusion Models of the Short-Term Interest Rate," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-41, March.
  • Handle: RePEc:bpj:sndecm:v:13:y:2009:i:1:n:4

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    References listed on IDEAS

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    Cited by:

    1. Seungmoon Choi, 2011. "Closed-Form Likelihood Expansions for Multivariate Time-Inhomogeneous Diffusions," School of Economics Working Papers 2011-26, University of Adelaide, School of Economics.
    2. Stéphane Goutte & Benteng Zou, 2012. "Continuous time regime switching model applied to foreign exchange rate," Working Papers hal-00643900, HAL.
    3. Joanna Janczura & Rafal Weron, 2012. "Inference for Markov-regime switching models of electricity spot prices," HSC Research Reports HSC/12/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    4. Joanna Janczura & Rafał Weron, 2013. "Goodness-of-fit testing for the marginal distribution of regime-switching models with an application to electricity spot prices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(3), pages 239-270, July.
    5. Stéphane GOUTTE & Benteng Zou, 2011. "Foreign exchange rates under Markov Regime switching model," CREA Discussion Paper Series 11-16, Center for Research in Economic Analysis, University of Luxembourg.
    6. Goutte, Stéphane, 2014. "Conditional Markov regime switching model applied to economic modelling," Economic Modelling, Elsevier, vol. 38(C), pages 258-269.
    7. Janczura, Joanna & Weron, Rafal, 2010. "Goodness-of-fit testing for regime-switching models," MPRA Paper 22871, University Library of Munich, Germany.
    8. Choi, Seungmoon, 2013. "Closed-form likelihood expansions for multivariate time-inhomogeneous diffusions," Journal of Econometrics, Elsevier, vol. 174(2), pages 45-65.
    9. Bu, Ruijun & Cheng, Jie & Hadri, Kaddour, 2016. "Reducible diffusions with time-varying transformations with application to short-term interest rates," Economic Modelling, Elsevier, vol. 52(PA), pages 266-277.
    10. Choi, Seungmoon, 2015. "Explicit form of approximate transition probability density functions of diffusion processes," Journal of Econometrics, Elsevier, vol. 187(1), pages 57-73.
    11. Lux, Thomas, 2013. "Exact solutions for the transient densities of continuous-time Markov switching models: With an application to the poisson multifractal model," Kiel Working Papers 1871, Kiel Institute for the World Economy (IfW).

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