Maizah Hura, Ahmad and Pung, Yean Ping and Siti Roslindar, Yaziz and Nor Hamizah, Miswan (2014) A Hybrid Model for Improving Malaysian Gold Forecast Accuracy. International Journal of Mathematical Analysis, 8 (28). pp. 1377-1387. ISSN 1312-8876 (print); 1314-7579 (online). (Published)
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Abstract
A hybrid model has been considered an effective way to improve forecast accuracy. This paper proposes the hybrid model of the linear autoregressive moving average (ARIMA) and the non-linear generalized autoregressive conditional heteroscedasticity (GARCH) in modeling and forecasting. Malaysian gold price is used to present the development of the hybrid model. The goodness of fit of the model is measured using Akaike information criteria (AIC) while the forecasting performance is assessed using bias, variance proportion, covariance proportion and mean absolute percentage error (MAPE).
Item Type: | Article |
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Uncontrolled Keywords: | ARIMA-GARCH, 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: | 11 Dec 2014 04:30 |
Last Modified: | 27 Jun 2018 08:45 |
URI: | http://umpir.ump.edu.my/id/eprint/7489 |
Download Statistic: | View Download Statistics |
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