On Regime Switching Models

Regime switching models have been widely studied for their ability to capture the dynamic behavior of time series data and are widely used in economic and financial data analysis. This paper reviews various regime switching models with various regime switching mechanisms, including threshold models, hidden Markov regime switching models, hidden semi-Markov regime switching models, and smooth transition models. The focus is on regime switching models for time series, studying their underlying frameworks, popular variants, and commonly used estimation methods. In addition, six different regime switching models are compared using two real-world datasets.

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Publication Details

Journal
Mathematics
Published
2025-03-29
DOI
https://doi.org/10.3390/math13071128
Citations
6
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
13.25

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article

On Regime Switching Models

Zhenni Tan, Yuehua Wu
6 citations
Mathematics
Financial Risk and Volatility Modeling
13.25
article

On Regime Switching Models

Zhenni Tan, Yuehua Wu
article en
6 citations

Abstract

Regime switching models have been widely studied for their ability to capture the dynamic behavior of time series data and are widely used in economic and financial data analysis. This paper reviews various regime switching models with various regime switching mechanisms, including threshold models, hidden Markov regime switching models, hidden semi-Markov regime switching models, and smooth transition models. The focus is on regime switching models for time series, studying their underlying frameworks, popular variants, and commonly used estimation methods. In addition, six different regime switching models are compared using two real-world datasets.

MathematicsVol. 13(7)
York University (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 1%
Financial Risk and Volatility Modeling
13.25
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