Distance and prediction error variance constraints for ARMA model portfolios

Timothy Chenoweth, Karen Dowling, Robert Hubata, Robert St Louis

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Poskitt and Tremayne 74 (1987) present a posterior odds ratio (R) portfolio selection strategy for ARMA models. This paper makes the range of prediction error variances that are implicit in R more explicit. Model closeness is quantified using a distance function in a Hilbert space. The relationship between distance and the posterior odds ratio is demonstrated. This provides a distance interpretation of the posterior odds ratio. The distance function also makes it possible to develop a prediction error variance (p.e.v.) criterion for identifying models to include in an ARMA model portfolio. A simulation experiment shows that the p.e.v. criterion provides forecasters with both a measure for assessing the likelihood that the models in an ARMA model portfolio yield practically equivalent forecasts, and a measure for assessing the usefulness of alternative criteria for identifying the order of an ARMA model.

Original languageEnglish (US)
Pages (from-to)41-52
Number of pages12
JournalInternational Journal of Forecasting
Issue number1
StatePublished - Jan 1 2004


  • Distance
  • Information criteria
  • Misspecification error
  • Order determination
  • Posterior odds ratio
  • Prediction error variance

ASJC Scopus subject areas

  • Business and International Management


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