Citation

Kuek, Jia Sin and Chin, Wen Cheong and Tan, Siow Hooi (2017) Level shift two-components autoregressive conditional heteroscedasticity modelling for WTI crude oil market. AIP Conference Proceedings, 1830. 080006. ISSN 1551-7616

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Abstract

This study aims to investigate the crude oil volatility using a two components autoregressive conditional heteroscedasticity (ARCH) model with the inclusion of abrupt jump feature. The model is able to capture abrupt jumps, news impact, clustering volatility, long persistence volatility and heavy-tailed distributed error which are commonly observed in the crude oiltime series. For the empirical study, we have selected the WTI crude oil index from year 2000 to 2016. The results found that by including the multiple-abrupt jumps in ARCH model, there are significant improvements of estimation evaluations as compared with the standard ARCH models. The outcomes of this study can provide useful information for risk management and portfolio analysis in the crude oil markets.

Item Type:	Article
Uncontrolled Keywords:	Heteroscedasticity, Regression
Subjects:	H Social Sciences > HA Statistics > HA1-4737 Statistics (General) > HA29-32 Theory and method of social science statistics
Divisions:	Faculty of Management (FOM)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	27 Oct 2020 17:37
Last Modified:	27 Oct 2020 17:37
URII:	http://shdl.mmu.edu.my/id/eprint/7101

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