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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