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An infinite hidden Markov model for short-term interest rates

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  • Maheu, John M.
  • Yang, Qiao

Abstract

The time-series dynamics of short-term interest rates are important as they are a key input into pricing models of the term structure of interest rates. In this paper we extend popular discrete time short-rate models to include Markov switching of infinite dimension. This is a Bayesian nonparametric model that allows for changes in the unknown conditional distribution over time. Applied to weekly U.S. data we find significant parameter change over time and strong evidence of non-Gaussian conditional distributions. Our new model with a hierarchical prior provides significant improvements in density forecasts as well as point forecasts. We find evidence of recurring regimes as well as structural breaks in the empirical application.

Suggested Citation

  • Maheu, John M. & Yang, Qiao, 2016. "An infinite hidden Markov model for short-term interest rates," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 202-220.
  • Handle: RePEc:eee:empfin:v:38:y:2016:i:pa:p:202-220 DOI: 10.1016/j.jempfin.2016.06.006
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    References listed on IDEAS

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    1. Chan, K C, et al, 1992. " An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-1227, July.
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    Cited by:

    1. repec:eee:intfor:v:33:y:2017:i:4:p:1025-1043 is not listed on IDEAS
    2. Liu, Jia & Maheu, John M, 2015. "Improving Markov switching models using realized variance," MPRA Paper 71120, University Library of Munich, Germany.

    More about this item

    Keywords

    Hierarchical Dirichlet process prior; Beam sampling; Markov switching; MCMC;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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