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  • 标题:Smooth Transition Garch Models : a Baysian Perspective
  • 本地全文:下载
  • 作者:Michel LUBRANO
  • 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:2001
  • 卷号:1
  • 出版社:Université catholique de Louvain
  • 摘要:This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two différent regimes with a smooth transition function. In one formulation, the conditional variance reacts differently to negative and positive shocks while in a second formulation, small and big shocks have separate effects. The introduction of a threshold allows for a mixed effect. A Bayesian strategy, based on the comparison between posterior and predictive Bayesian residuals, is built for detecting the presence and the shape of non-linearities. The method is applied to the Brussels and Tokyo stock indexes. The attractiveness of an alternative parameterisation of the GARCH model is emphasised as a potential solution to some numerical problems.
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