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Capturing the Regime-Switching and Memory Properties of Interest Rates

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  • Xiaojing Xi
  • Rogemar Mamon

Abstract

We propose a mean-reverting interest rate model whose mean-reverting level, speed of mean-reversion and volatility are all modulated by a weak Markov chain (WMC). This model features a simple way to capture the regime-switching evolution of the parameters as well as the memory property of the data. Concentrating on the second-order WMC framework, we derive the filters of the WMC and other auxiliary processes through a change of reference probability measure. Optimal estimates of model parameters are provided by employing the EM algorithm. The $$h$$ h -step ahead forecasts under our proposed set-up are examined and compared with those under the usual Markovian regime-switching framework. We obtain better goodness-of-fit performance based on our numerical results generated from the implementation of WMC-based filters to a 10-year dataset of weekly short-term-maturity Canadian yield rates. Some statistical inference issues of the proposed modelling approach are also discussed. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Xiaojing Xi & Rogemar Mamon, 2014. "Capturing the Regime-Switching and Memory Properties of Interest Rates," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 307-337, October.
    • Handle: RePEc:kap:compec:v:44:y:2014:i:3:p:307-337
    DOI: 10.1007/s10614-013-9396-5
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    Cited by:

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    More about this item

    Keywords

    Weak hidden Markov model; Parameter estimation; Regime-switching; Memory property; C51; G12;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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