Forecasting Malaysian Gold Using a Hybrid of ARIMA and GJR-GARCH Models

• Main Authors: Siti Roslindar, Yaziz, Maizah Hura, Ahmad, Pung, Yean Ping, Nor Hamizah, Miswan
• Format: Article
• Language: English
• Published: Hikari Ltd. 2015
• Subjects: Q Science (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/8976/1/Forecasting%20Malaysian%20Gold%20Using%20a%20Hybrid%20of%20ARIMA%20and%20GJR-GARCH%20Models.pdf; http://umpir.ump.edu.my/id/eprint/8976/; http://dx.doi.org/10.12988/ams.2015.5124

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 usin...