Markov switching component GARCH model: Stability and forecasting

DOI10.1080/03610926.2013.841934zbMath1345.60073arXiv1303.5525OpenAlexW2962687598MaRDI QIDQ2816418

Saeid Rezakhah, N. Alemohammad, S. H. Alizadeh

Publication date: 22 August 2016

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1303.5525

zbMATH Keywords

stabilityMarkov processesforecastingBayesian inferenceGibbs sampling algorithmGARCH models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Numerical methods (including Monte Carlo methods) (91G60) Bayesian inference (62F15) Probabilistic models, generic numerical methods in probability and statistics (65C20) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Related Items (4)

Performance of MS-GARCH Models: Bayesian MCMC-Based Estimation ⋮ Markov switch smooth transition HYGARCH model: Stability and estimation ⋮ Spectral representation and autocovariance structure of Markov switching DSGE models ⋮ Markov switching asymmetric GARCH model: stability and forecasting

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