Time series modelling — an integrated approach

Research output: Contribution to journalArticlepeer-review

Abstract

Some inadequacies of both the traditional (exponential smoothing) and Box-Jenkins approaches to time series forecasting of economic data are investigated. An approach is suggested which integrates these two methodologies. It is based on smoothing the data using straight line segments instead of differencing to obtain stationarity, and forecasting using an autoregressive-moving-average model for the residuals from the most recent linear segment. The efficiency of this approach is calculated theoretically using a series comprising integrated white noise.
Original languageEnglish
Pages (from-to)413-425
Number of pages13
JournalJournal of Applied Probability
Volume19
Issue numberA
DOIs
Publication statusPublished - 1982

Keywords

  • Time series
  • Box-Jenkins
  • Forecasting
  • Exponential smoothing
  • Differencing

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