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An Econometric Model of the Term Structure of Interest Rates Under Regime-Switching Risk

In: Hidden Markov Models in Finance

Author

Listed:
  • Shu Wu

    (University of Kansas)

  • Yong Zeng

    (University of Missouri at Kansas City)

Abstract

This paper develops and estimates a continuous-time model of the term structure of interests under regime shifts. The model uses an analytically simple representation of Markov regime shifts that elucidates the effects of regime shifts on the yield curve and gives a clear interpretation of regime-switching risk premiums. The model falls within the broad class of essentially affine models with a closed form solution of the yield curve, yet it is flexible enough to accommodate priced regime-switching risk, time-varying transition probabilities, regime-dependent mean reversion coefficients as well as stochastic volatilities within each regime. A two-factor version of the model is implemented using Efficient Method of Moments. Empirical results show that the model can account for many salient features of the yield curve in the U.S.

Suggested Citation

  • Shu Wu & Yong Zeng, 2014. "An Econometric Model of the Term Structure of Interest Rates Under Regime-Switching Risk," International Series in Operations Research & Management Science, in: Rogemar S. Mamon & Robert J. Elliott (ed.), Hidden Markov Models in Finance, edition 127, chapter 0, pages 55-83, Springer.
    • Handle: RePEc:spr:isochp:978-1-4899-7442-6_3
    DOI: 10.1007/978-1-4899-7442-6_3
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    Cited by:

    1. Liu, Wei-han, 2018. "Hidden Markov model analysis of extreme behaviors of foreign exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1007-1019.
    2. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. Robert J. Elliott & Tak Kuen Siu, 2016. "Pricing regime-switching risk in an HJM interest rate environment," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1791-1800, December.
    4. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models," Papers 2011.03741, arXiv.org, revised Dec 2020.

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