Abstract
The Box-Jenkins approach to time series modelling consists of extracting predictable movements (or patterns) from the observed data through a series of iterations. The univariate Box-Jenkins method is purely a forecasting tool; no explanation is offered in that there are no regressor-type variables. The Box-Jenkins approach follows a three phase procedure:
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Model identification : a particular category of Box-Jenkins (B-J) model is identified by using various statistics computed from an analysis of the historical data.
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Model estimation and verification : once identified, the “best model” is estimated such that the fitted values come as close as possible to capturing the pattern exhibited by the actual data.
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Forecasting : the final model is used to forecast the time series and to develop confidence intervals that measure the uncertainty associated with the forecast.
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Aljandali, A., Tatahi, M. (2018). Economic Forecasting using ARIMA Modelling. In: Economic and Financial Modelling with EViews. Statistics and Econometrics for Finance. Springer, Cham. https://doi.org/10.1007/978-3-319-92985-9_7
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DOI: https://doi.org/10.1007/978-3-319-92985-9_7
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