Siti Roslindar, Yaziz and Roslinazairimah, Zakaria and Maizah Hura, Ahmad (2017) Determination of sample size for higher volatile data using new framework of hybrid Box-Jenkins - GARCH: a case study on gold price. In: 1st International Conference On Applied & Industrial Mathematics And Statistics 2017 (ICOAIMS 2017) , 8-10 Aug 2017 , Kuantan, Pahang. pp. 1-7.. (Unpublished)
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36. Determination of Sample Size for Higher Volatile Data using New Framework of Hybrid Box-Jenkins - GARCH A Case Study on Gold Price.pdf - Published Version Restricted to Repository staff only Download (744kB) | Request a copy |
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36.1 Determination of Sample Size for Higher Volatile Data using New Framework of Hybrid Box-Jenkins - GARCH - A Case Study on Gold Price.pdf - Published Version Download (125kB) | Preview |
Abstract
The hybrid model of Box-Jenkins - GARCH has been shown to be a promising tool for forecasting higher volatile time series. In this study, the framework of determining the optimal sample size using the hybrid Box-Jenkins - GARCH is proposed for practical application in analysing and forecasting higher volatile data. The proposed framework is employed to daily world gold price series from year 1971 to 2013. The data is divided into 12 different sample sizes (from 30 to 10200). Each sample is tested using different combination of the hybrid Box-Jenkins - GARCH model. Our study shows that the optimal sample size to forecast gold price using the framework of the hybrid model is 1250 data of 5-year sample. Hence, the empirical results of model selection criteria and 1-step-ahead forecasting evaluations suggest that the latest 12.25% (5-year data) of 10200 data is sufficient enough to be employed in the hybrid Box-Jenkins - GARCH with similar forecasting performance as by using 41-year data.
| Item Type: | Conference or Workshop Item (Lecture) |
|---|---|
| Uncontrolled Keywords: | Box-Jenkins model; Box-Jenkins – GARCH; Gold price forecasting; Sample size |
| Subjects: | Q Science > Q Science (General) T Technology > T Technology (General) |
| Faculty/Division: | Faculty of Industrial Sciences And Technology |
| Depositing User: | Pn. Hazlinda Abd Rahman |
| Date Deposited: | 24 May 2018 03:02 |
| Last Modified: | 24 May 2018 03:02 |
| URI: | http://umpir.ump.edu.my/id/eprint/20583 |
| Download Statistic: | View Download Statistics |
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