Markov Switching Garch Models: Higher Order Moments, Kurtosis Measures, and Volatility Evaluation in Recessions and Pandemic
From MaRDI portal
Publication:6620992
DOI10.1080/07350015.2021.1974459zbMATH Open1547.62656MaRDI QIDQ6620992
Publication date: 17 October 2024
Published in: Journal of Business and Economic Statistics (Search for Journal in Brave)
Cites Work
- Analysis of time series subject to changes in regime
- On the Markov chain central limit theorem
- Deriving the autocovariances of powers of Markov-switching GARCH models, with applications to statistical inference
- Strict stationarity of generalized autoregressive processes
- Mixing: Properties and examples
- Autoregressive conditional heteroskedasticity and changes in regime
- Generalized autoregressive conditional heteroscedasticity
- The \(L^2\)-structures of standard and switching-regime GARCH models
- DETERMINING THE NUMBER OF REGIMES IN MARKOV SWITCHING VAR AND VMA MODELS
- Theory and inference for a Markov switching GARCH model
- Conditional Heteroskedasticity in Asset Returns: A New Approach
- On a Mixture GARCH Time-Series Model
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
- On a Mixture Autoregressive Conditional Heteroscedastic Model
- Markov-switching BILINEAR − GARCH models: Structure and estimation
- Exponential-Type GARCH Models With Linear-in-Variance Risk Premium
- Confidence Intervals for Conditional Tail Risk Measures in ARMA–GARCH Models
Related Items (2)
Spectral representation of Markov-switching bilinear processes ⋮ On the Markov-switching autoregressive stochastic volatility processes
This page was built for publication: Markov Switching Garch Models: Higher Order Moments, Kurtosis Measures, and Volatility Evaluation in Recessions and Pandemic
