Using ARIMA-GARCH Model to Analyze Fluctuation Law of International Oil Price
Author(s) -
Ying Xiang
Publication year - 2022
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2022/3936414
Subject(s) - autoregressive integrated moving average , autoregressive conditional heteroskedasticity , autoregressive model , econometrics , economics , moving average , moving average model , oil price , heteroscedasticity , time series , volatility (finance) , mathematics , statistics , monetary economics
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.
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