期刊名称：Discussion Paper / Département des Sciences Économiques de l'Université Catholique de Louvain
印刷版ISSN：1379-244X
出版年度：2006
卷号：1
出版社：Université catholique de Louvain
摘要：We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance switches in time from one GARCH process to another. The switching is governed by a time-varying probability, specified as a function of past information. We provide sufficient conditions for stationarity and existence of moments. Because of path dependence, maximum likehood estimation is infeasible. By enlarging the parameter space to include the state variables, Bayesian estimation using a Gibbs sampling algorithm is feasible. We apply this model using the NASDAQ daily returns series.
