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- Title
TREND DETECTION THROUGH SEGMENTATION USING DISCRETE HIDDEN MARKOV MODEL.
- Authors
ÖZGÜR, Özler
- Abstract
There are two models that benefit from the concept of hidden variables and are used frequently in practice. These are hidden Markov model and Markov switching model. Although there are quite a number of regime switching studies which applied the Markov switching model in the field of econometrics, studies that use the hidden Markov model for examining the regimes in econometric time series are sparse. In this study, we apply discrete hidden Markov model to four high-frequency time series and show that although transformed discrete data have to be used in the model structure, the model identifies two or more regimes quite well. It is concluded that the discrete hidden Markov model is defining regimes effectively, thereby, can also identify and segment trends.
- Subjects
HIDDEN Markov models; MARKOV processes; TIME series analysis
- Publication
Hacettepe University Journal of Economics & Administrative Sciences / Hacettepe Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi, 2020, Vol 38, Issue 2, p267
- ISSN
1301-8752
- Publication type
Article
- DOI
10.17065/huniibf.530209