A COMPARATIVE ANALYSIS OF THE PREDICTIVE ABILITY OF ADAPTIVE FORECASTING, RE‐ESTIMATION, AND RE‐IDENTIFICATION USING BOX‐JENKINS TIME‐SERIES ANALYSIS ON QUARTERLY EARNINGS DATA

James C. McKeown, Kenneth S Lorek

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

This paper assesses the predictive ability of the Box‐Jenkins methodology when utilized in an on‐going setting. Three procedures are utilized to update the original forecasts generated from the Box‐Jenkins models: adaptive forecasting, re‐estimation, and re‐identification. The results indicate that constant monitoring of the structure and parameters of the time‐series models are necessary through time. It appears that adaptive forecasting techniques are insufficient to update BJ time‐series models when used in conjunction with quarterly earnings data. Re‐estimation is recommended as each new observation becomes available. Re‐identification procedures are recommended on a less frequent basis.

Original languageEnglish (US)
Pages (from-to)658-672
Number of pages15
JournalDecision Sciences
Volume9
Issue number4
DOIs
StatePublished - 1978
Externally publishedYes

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Monitoring
Time series analysis
Time series models
Predictive ability
Comparative analysis
Methodology

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation

Cite this

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title = "A COMPARATIVE ANALYSIS OF THE PREDICTIVE ABILITY OF ADAPTIVE FORECASTING, RE‐ESTIMATION, AND RE‐IDENTIFICATION USING BOX‐JENKINS TIME‐SERIES ANALYSIS ON QUARTERLY EARNINGS DATA",
abstract = "This paper assesses the predictive ability of the Box‐Jenkins methodology when utilized in an on‐going setting. Three procedures are utilized to update the original forecasts generated from the Box‐Jenkins models: adaptive forecasting, re‐estimation, and re‐identification. The results indicate that constant monitoring of the structure and parameters of the time‐series models are necessary through time. It appears that adaptive forecasting techniques are insufficient to update BJ time‐series models when used in conjunction with quarterly earnings data. Re‐estimation is recommended as each new observation becomes available. Re‐identification procedures are recommended on a less frequent basis.",
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