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Economic Forecasting using ARIMA Modelling

  • Abdulkader Aljandali
  • Motasam Tatahi
Chapter
Part of the Statistics and Econometrics for Finance book series (SEFF)

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:
  • 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.

  • 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.

  • Forecasting: the final model is used to forecast the time series and to develop confidence intervals that measure the uncertainty associated with the forecast.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Abdulkader Aljandali
    • 1
  • Motasam Tatahi
    • 2
  1. 1.Department of Accounting, Finance and EconomicsCoventry University LondonLondonUK
  2. 2.Department of Economics, Finance and AccountingRegent’s University London-European Business School LondonLondonUK

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