Advances and Applications in Statistics
Volume 4, Issue 3, Pages 327 - 355
(December 2004)
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MODELLING SEASONAL CONDITIONAL HETEROSCEDASTICITY
Salina S. T. Lau (Hong Kong) and H. Wong (Hong Kong)
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Abstract: A
seasonal conditional heteroscedastic model is
proposed. The identification, estimation, and
diagnostic checking procedures for the model
are given. Simulation studies about the
performance of the suggested methods are
reported. Using the money supply (M1) of the
United States as an example, the model is
compared with some popular models such as Generalized
Autoregressive Conditional Heteroscedasticity
(GARCH), and seasonal GARCH. It is found that
the proposed model is more successful in
capturing the volatility than the other models
and produces better forecasts. |
Keywords and phrases: non-linear time series model, generalized conditional heteroscedasticity, seasonality. |
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