Markov regime-switching autoregressive model with tempered stable distribution: simulation evidence
-
Lingbing Feng
and
Yanlin Shi
Abstract
Markov regime-switching (MRS) autoregressive model is a widely used approach to model the economic and financial data with potential structural breaks. The innovation series of such MRS-type models are usually assumed to follow a Normal distribution, which cannot accommodate fat-tailed properties commonly present in empirical data. Many theoretical studies suggest that this issue can lead to inconsistent estimates. In this paper, we consider the tempered stable distribution, which has the attractive stability under aggregation property missed in other popular alternatives like Student’s t-distribution and General Error Distribution (GED). Through systematically designed simulation studies with the MRS autoregressive models, our results demonstrate that the model with tempered stable distribution uniformly outperforms those with Student’s t-distribution and GED. Our empirical study on the implied volatility of the S&P 500 options (VIX) also leads to the same conclusions. Therefore, we argue that the tempered stable distribution could be widely used for modelling economic and financial data in general contexts with an MRS-type specification.
Acknowledgments
We are grateful to Macquarie University and Jiangxi University of Finance and Economics for their support. The authors would also like to thank Dave Allen, Felix Chan, Kin-Yip Ho, Michael McAleer, Paresh Narayan, Morten Nielson, Albert Tsui, Zhaoyong Zhang, and participants at the 1st Conference on Recent Developments in Financial Econometrics and Applications, the 8th China R Conference (Nanchang), ANU Research School Brown Bag Seminar, Central University of Finance and Economics Seminar, China Meeting of Econometric Society, Chinese Economists Society China Annual Conference, Econometric Society Australasian Meeting, Ewha Woman’s University Department of Economics Seminar, International Congress of the Modeling and Simulation Society of Australia and New Zealand and Shandong University Seminar. We particularly thank the Editor-in-Chief Bruce Mizrach and one anonymous referee for providing valuable comments on earlier drafts. The usual disclaimer applies.
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Articles in the same Issue
- Research Articles
- Bond risk premia and the return forecasting factor
- On the performance of information criteria for model identification of count time series
- Trimmed Whittle estimation of the SVAR vs. filtering low-frequency fluctuations: applications to technology shocks
- Markov regime-switching autoregressive model with tempered stable distribution: simulation evidence
- Testing for cointegration with threshold adjustment in the presence of structural breaks
- A model for ordinal responses with heterogeneous status quo outcomes
Articles in the same Issue
- Research Articles
- Bond risk premia and the return forecasting factor
- On the performance of information criteria for model identification of count time series
- Trimmed Whittle estimation of the SVAR vs. filtering low-frequency fluctuations: applications to technology shocks
- Markov regime-switching autoregressive model with tempered stable distribution: simulation evidence
- Testing for cointegration with threshold adjustment in the presence of structural breaks
- A model for ordinal responses with heterogeneous status quo outcomes
