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Using ARIMA-GARCH Model to Analyze Fluctuation Law of International Oil Price

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  • Ying Xiang
  • Wen-Tsao Pan

Abstract

It is meaningful and of certain theoretical value for the development of economy through analyzing fluctuation rules of international oil prices and forecasting the future trend of international oil prices. By composing the autoregressive integrated moving average (ARIMA) model and the combination model of autoregressive integrated moving average model-generalized autoregressive conditional heteroskedasticity (ARIMA-GARCH) for analyzing and forecasting international oil prices, study shows that the combination model of ARIMA (1,1,0)-GARCH (1,1) is more suitable for short-term forecasting of international oil prices with higher accuracy that the MAPE of forecasting has reduced from 1.549% to 0.045% and the RMSE of forecasting has reduced from 1.032 to 0.071.

Suggested Citation

  • Ying Xiang & Wen-Tsao Pan, 2022. "Using ARIMA-GARCH Model to Analyze Fluctuation Law of International Oil Price," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-7, March.
    • Handle: RePEc:hin:jnlmpe:3936414
    DOI: 10.1155/2022/3936414
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    Cited by:

    1. Jilin Zhang & Lishi Ye & Yongzeng Lai, 2023. "Stock Price Prediction Using CNN-BiLSTM-Attention Model," Mathematics, MDPI, vol. 11(9), pages 1-18, April.

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