Smooth transition GARCH models: a Bayesian perspective
Michel Lubrano ()
No 1998066, CORE Discussion Papers from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two different 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 mixedeffect. A Bayesian strategy, based on the comparison between posterior and predictive Bayesian residuals, is built for detecting the presence and the shape of nonlinearities. The method is applied to the Brussels and Tokyo stock indexes. The need for an alternative parameterisation of the GARCH model is emphasised as a solution to numerical problems.
Keywords: Bayesian; asymmetric GARCH; speciﬁcation tests; nonlinear modelling; stock indexes (search for similar items in EconPapers)
JEL-codes: C11 C22 C51 G14 (search for similar items in EconPapers)
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Working Paper: Smooth Transition Garch Models: a Baysian Perspective (2001)
Working Paper: Smooth Transition GARCH Models: a Bayesian perspective (1999)
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:1998066
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