Forecasting CPO price using ARIMA, ARCH and GARCH models
The oil palm industry in Malaysia directly contributes to the economy through financial returns that enhance the national income. A forecast of crude palm oil (CPO) price is important, especially when the investors will encounter with the increasing risks and uncertainties in the future. Therefore,...
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| Format: | Thesis |
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2016
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| Online Access: | http://eprints.uthm.edu.my/8997/ http://eprints.uthm.edu.my/8997/1/Raed_Hameed_Mahdi_Al%2DTemeeme.compressed.pdf |
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| Summary: | The oil palm industry in Malaysia directly contributes to the economy through financial returns that enhance the national income. A forecast of crude palm oil (CPO) price is important, especially when the investors will encounter with the increasing risks and uncertainties in the future. Therefore, the applicability of the forecasting approaches in predicting the CPO price is becoming a matter of great concern. The aim of this study is to forecast the price of palm oil in Malaysia for a period of 31 years; 1983 - 2014. The objective of the research is to propose an appropriate model to forecast the CPO price. This study involves three types of model, which are Autoregressive Integrated Moving Average (ARIMA), Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Akaike Information Criteria (AIC) and Hannan-Quinn Criterion (H-Q) statistic were used to obtain the best model. It was found that ARIMA (2, 1, 5) performed better compared to ARCH and GARCH models. It is concluded that ARIMA (2, 1, 5) model can be used as an alternative model to forecast the CPO price. |
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