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Extracting Information from Spot Interest Rates and Credit Ratings using Double Higher-Order Hidden Markov Models

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  • Tak-Kuen Siu

  • Wai-Ki Ching

  • Eric Fung

  • Michael Ng

Abstract

Estimating and forecasting the unobservable states of an economy are important and practically relevant topics in economics. Central bankers and regulators can use information about the market expectations on the hidden states of the economy as a reference for decision and policy makings, for instance, deciding monetary policies. Spot interest rates and credit ratings of bonds contain important information about the hidden sequence of the states of the economy. In this paper, we develop double higher-order hidden Markov chain models (DHHMMs) for extracting information about the hidden sequence of the states of an economy from the spot interest rates and credit ratings of bonds. We consider a discrete-state model described by DHHMMs and focus on the qualitative aspect of the unobservable states of the economy. The observable spot interest rates and credit ratings of bonds depend on the hidden states of the economy which are modelled by DHHMMs. The DHHMMs can incorporate the persistent phenomena of the time series of spot interest rates and the credit ratings. We employ the maximum likelihood method and the EM algorithm, namely Viterbi's algorithm, to uncover the optimal hidden sequence of the states of the economy which can be interpreted the “best” estimate of the sequence of the underlying economic states generating the spot interest rates and credit ratings of the bonds. Then, we develop an efficient maximum likelihood estimation method to estimate the unknown parameters in our model. Numerical experiment will be conducted to illustrate the implementation of the model. Copyright Springer Science+Business Media, Inc. 2005
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Suggested Citation

  • Tak-Kuen Siu & Wai-Ki Ching & Eric Fung & Michael Ng, 2007. "Extracting Information from Spot Interest Rates and Credit Ratings using Double Higher-Order Hidden Markov Models," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 425-425, May.
    • Handle: RePEc:kap:compec:v:29:y:2007:i:3:p:425-425
    DOI: 10.1007/s10614-006-9057-z
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    2. Zhu, Dong-Mei & Lu, Jiejun & Ching, Wai-Ki & Siu, Tak-Kuen, 2017. "Discrete-time optimal asset allocation under Higher-Order Hidden Markov Model," Economic Modelling, Elsevier, vol. 66(C), pages 223-232.
    3. Xi, Xiaojing & Mamon, Rogemar, 2011. "Parameter estimation of an asset price model driven by a weak hidden Markov chain," Economic Modelling, Elsevier, vol. 28(1-2), pages 36-46, January.
    4. Xi, Xiaojing & Mamon, Rogemar, 2011. "Parameter estimation of an asset price model driven by a weak hidden Markov chain," Economic Modelling, Elsevier, vol. 28(1), pages 36-46.
    5. 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.

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