文章基本信息

标题：Comparative Evaluation of Forecast Accuracies for ARIMA, Exponential Smoothing and VAR
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作者：Hatice Erkekoglu ; Aweng Peter Majok Garang ; Adire Simon Deng 等
期刊名称：International Journal of Economics and Financial Issues
电子版ISSN：2146-4138
出版年度：2020
卷号：10
期号：6
页码：206-216
DOI：10.32479/ijefi.9020
出版社：EconJournals
摘要：While various linear and nonlinear forecasting models exist, multivariate methods like VAR, Exponential smoothing, and Box-Jenkins’ ARIMA methodology constitute the widely used methods in time series. This paper employs series of Turkish private consumption, exports and GDP data ranging between 1998: Q1 and 2017: Q4 to analyze the forecast performance of the three models using measures of accuracy such as RMSE, MAE, MAPE, Theil’s & . Seasonal decomposition and ADF unit root tests were performed to obtain new deseasonalized series and stationarity, respectively. Results offer preference for the use of ARIMA in forecasting, having performed better than VAR and exponential smoothing in all scenarios. Additionally, VAR model provided better forecast accuracy than exponential smoothing on all measures of accuracy except on Thiel’s whose VAR values were not computed. Cautionary use of ARIMA for forecasting is recommended.
关键词：Forecast Evaluation; ARIMA; Exponential Smoothing; VAR