Siti Roslindar, Yaziz and Maizah Hura, Ahmad and Pung, Yean Ping and Nor Hamizah, Miswan (2015) Forecasting Malaysian Gold Using a Hybrid of ARIMA and GJR-GARCH Models. Applied Mathematical Sciences, 9 (30). pp. 1491-1501. ISSN 1314-7552 (print); 1312-885X (online). (Published)
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Abstract
An effective way to improve forecast accuracy is to use a hybrid model. This paper proposes a hybrid model of linear autoregressive moving average (ARIMA) and non-linear GJR-GARCH model also known as TARCH in modeling and
forecasting Malaysian gold. The goodness of fit of the model is measured using Akaike information criteria (AIC) while the forecasting performance is assessed using mean absolute percentage error (MAPE), bias proportion, variance
proportion and covariance proportion.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | ARIMA-GJR, TARCH, hybrid model, heteroscedasticity, volatility clustering |
| Subjects: | Q Science > Q Science (General) |
| Faculty/Division: | Faculty of Industrial Sciences And Technology |
| Depositing User: | Mrs. Neng Sury Sulaiman |
| Date Deposited: | 10 Apr 2015 01:43 |
| Last Modified: | 28 Jun 2018 04:01 |
| URI: | https://umpir.ump.edu.my/id/eprint/8976 |
| Statistic Details: | View Download Statistic |
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