Determination of sample size for higher volatile data using new framework of hybrid Box-Jenkins - GARCH: a case study on gold price
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 highe...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/20583/ http://umpir.ump.edu.my/id/eprint/20583/1/36.%20Determination%20of%20Sample%20Size%20for%20Higher%20Volatile%20Data%20using%20New%20Framework%20of%20Hybrid%20Box-Jenkins%20-%20GARCH%20A%20Case%20Study%20on%20Gold%20Price.pdf http://umpir.ump.edu.my/id/eprint/20583/3/36.1%20Determination%20of%20Sample%20Size%20for%20Higher%20Volatile%20Data%20using%20New%20Framework%20of%20Hybrid%20Box-Jenkins%20-%20GARCH%20-%20A%20Case%20Study%20on%20Gold%20Price.pdf |
| Summary: | 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. |
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