Smooth Transition Garch Models: a Baysian Perspective
Michel Lubrano ()
No 2001032, Discussion Papers (REL - Recherches Economiques de Louvain) from Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES)
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.
JEL-codes: C11 C22 C51 G14 (search for similar items in EconPapers)
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Working Paper: Smooth Transition GARCH Models: a Bayesian perspective (1999)
Working Paper: Smooth transition GARCH models: a Bayesian perspective (1998)
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Persistent link: https://EconPapers.repec.org/RePEc:ctl:louvre:2001032
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