Performance of MS-GARCH Models: Bayesian MCMC-Based Estimation
From MaRDI portal
Publication:5049444
DOI10.1007/978-3-030-54108-8_14OpenAlexW3132482434MaRDI QIDQ5049444
Lawrence Diteboho Xaba, Lebotsa Daniel Metsileng, Ntebogang Dinah Moroke
Publication date: 11 November 2022
Published in: Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-030-54108-8_14
maximum likelihood estimationDiebold-Mariano testBayesian Markov chain Monte Carlo (MCMC)error metricesnonlinear GARCH model
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Financial risk management with Bayesian estimation of GARCH models. Theory and applica\-tions.
- Multivariate mixed normal conditional heteroskedasticity
- Autoregressive conditional heteroskedasticity and changes in regime
- Maximum likelihood estimation of the Markov-switching GARCH model
- Generalized autoregressive conditional heteroscedasticity
- Dynamic risk exposures in hedge funds
- Finite mixture and Markov switching models.
- Non parametric portmanteau tests for detecting non linearities in high dimensions
- Markov switching component GARCH model: Stability and forecasting
- Theory and inference for a Markov switching GARCH model
- Forecasting Stock Market Volatility with Regime-Switching GARCH Models
- Bayesian estimation of a Markov-switching threshold asymmetric GARCH model with Student-t innovations
- Markov-Switching GARCH Modelling of Value-at-Risk
- A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
This page was built for publication: Performance of MS-GARCH Models: Bayesian MCMC-Based Estimation