Maizah Hura Ahmad, Yean Ping Pung, Siti Roslindar Yazir, N. Miswan
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引用次数: 9
摘要
混合模型被认为是提高预报精度的有效方法。本文提出了线性自回归移动平均(ARIMA)和非线性广义自回归条件异方差(GARCH)的混合模型进行建模和预测。采用马来西亚黄金价格发展的混合模型来呈现。采用赤池信息准则(Akaike information criteria, AIC)衡量模型的拟合优度，采用偏置、方差比例、协方差比例和平均绝对百分比误差(MAPE)评估模型的预测效果。
A Hybrid Model for Improving Malaysian Gold Forecast Accuracy
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).
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