Cheng, J (2016) Spectral density of Markov switching models: Derivation, simulation studies and application. Model Assisted Statistics and Applications. ISSN 1574-1699

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Abstract

This paper is concerned with frequency domain analysis of Markov mean-switching autoregressive (MMSAR) models, linear Markov switching autoregressive (LMSAR) model and transitional Markov switching autoregressive (TMSAR) model. We derive the general expressions of autocovariance functions and spectra for these three models. Simulation studies of theoretical spectral density functions of these three models are presented. The results show that Markov chain seems to be the most important determinants of the frequency distribution of the volatility. A time series is analysed and both smoothed periodogram and theoretical spectra (of LMSAR and TMSAR models) show similar pattern and give clear ideas of business cycle.

Item Type: Article
Additional Information: This publication is available online at https://content.iospress.com/articles/model-assisted-statistics-and-applications/mas373
Uncontrolled Keywords: Markov switching autoregressive models; autocovariance structure; spectral density function; frequency domain analysis
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Natural Sciences > School of Computing and Maths
Depositing User: Symplectic
Date Deposited: 09 Jan 2019 16:00
Last Modified: 09 Jan 2019 16:00
URI: http://eprints.keele.ac.uk/id/eprint/5652

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