Ahmad, Maizah Hura and Pung, Yean Ping and Yaziz, Siti Roslindar and Miswan, Nor Hamizah (2015) Forecasting Malaysian gold using a hybrid of ARIMA and GJR-GARCH models. Applied Mathematical Sciences, 9 (29-32). pp. 1491-1501. ISSN 1312-885X
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Official URL: http://dx.doi.org/10.12988/ams.2015.5124
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: | hybrid model, TARCH, volatility clustering |
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Science |
| ID Code: | 55337 |
| Deposited By: | Fazli Masari |
| Deposited On: | 24 Aug 2016 03:42 |
| Last Modified: | 15 Feb 2017 07:07 |
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