Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/63775
Title: Modelling seasonal conditional heteroscedasticity
Authors: Wong, H 
Lau, S
Keywords: Non-linear time series model
Generalized conditional heteroscedasticity
Seasonality
Issue Date: 2004
Publisher: Pushpa Publishing House
Source: Advances and applications in statistics, 2004, v. 4, no. 3, p. 327-355 How to cite?
Journal: Advances and applications in statistics 
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.
URI: http://hdl.handle.net/10397/63775
ISSN: 0972-3617
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