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Extracting information from spot interest rates and credit ratings using double higher-order hidden markov models

Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/136065

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Title: Extracting information from spot interest rates and credit ratings using double higher-order hidden markov models
Related: Computational economics, Vol. 26, No. 3-4, (2005), p.251-284
DOI: 10.1007/s10614-005-9010-6
Publisher: Springer
Date: 2005
FoR/RFCD Code(s): 149900 Other Economics 140300 Econometrics
Author/Creator: Siu, Tak-Kuen
Author/Creator: Ching, Wai-Ki
Author/Creator: Fung, Eric S
Author/Creator: Ng, Michael K
Description: 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.
Description: 34 page(s)
Subject Keyword: 149900 Other Economics
Subject Keyword: 140300 Econometrics
Subject Keyword: double higher-order hidden markov model
Subject Keyword: credit ratings
Subject Keyword: long range dependence
Subject Keyword: optimal hidden economic states
Subject Keyword: spot interest rates
Resource Type: journal article
Organisation: Macquarie University. Dept. of Applied Finance and Actuarial Studies

Identifier: http://hdl.handle.net/1959.14/136065
Identifier: ISSN:0927-7099
Identifier: mq-rm-2009000356
Language: eng
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