期刊名称：CORE Discussion Papers / Center for Operations Research and Econometrics (UCL), Louvain
出版年度：2007
卷号：1
出版社：Center for Operations Research and Econometrics (UCL), Louvain
摘要：We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional
mean and variance switch in time from one GARCH process to another. The switching is
governed by a hidden Markov chain. We provide sufficient conditions for geometric
ergodicity and existence of moments of the process. Because of path dependence, maximum
likelihood estimation is not feasible. By enlarging the parameter space to include the state
variables, Bayesian estimation using a Gibbs sampling algorithm is feasible. We illustrate
the model on SP500 daily returns.
