Markov Switching Smooth Transition GARCH Model

2016/03/06 by Nafiseh Alemohammad, AleMohammad, N., Saeid Rezakhah +3
Economics, Econometrics and Finance · Environmental Science · #60J10 #62F15 #62M10 #FOS: Computer and information sciences #FOS: Mathematics #Financial Risk and Volatility Modeling #Hydrology and Drought Analysis #Market Dynamics and Volatility #Methodology (stat.ME) #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.1603.01795

openalex publication_date 2016/03/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A Markov switching asymmetric GARCH model which imposes more leverage effect of the negative shocks is considered. The asymptotic behavior of the second moment is investigated and an upper bound for it is calculated. A bayesian strategy through Gibbs and griddy Gibbs sampling is used to estimate the parameters. Finally we study the performance of the model by two real data sets. We show that this model has the best in-sample fit via DIC and provides a better forecast when the negative skewness is large enough.

Citations

• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Generalized autoregressive conditional heteroskedasticity
• Autoregressive conditional heteroskedasticity and changes in regime

Related

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• Markov Switch Smooth Transition HYGARCH Model: Stability and Estimation
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• Long-memory GARCH via a two-dimensional Markov chain
• Continuous-time Markov-switching GARCH Process with Robust and Efficient State Path and Volatility Estimation