THE PREDICTIVE PERFORMANCE OF THREE AUTOREGRESSIVE MOVING‐AVERAGE MODELS:A MONTE CARLO INVESTIGATION Journal Article uri icon

Overview

abstract

  • Abstract. The relative accuracy of point and interval forecasts from three related autoregressive moving‐average (ARMA) models—multivariate, univariate, and transfer function—is evaluated in this study. It is found that the multivariate models produce the most accurate one‐ and three‐step‐ahead point forecasts of nonindependent series. However, the most accurate point forecasts of independent series are generated by the univariate models. Compared with the multivariate models, the transfer function predictions are relatively unreliable, but with the appropriate restrictions they are superior to the univariate forecasts in certain cases. Interval forecasts from the correctly specified models are reliable indicators of forecast dispersion.

publication date

  • July 1, 1989

has restriction

  • closed

Date in CU Experts

  • July 14, 2014 12:18 PM

Full Author List

  • Batts JT; McNown RF

author count

  • 2

Other Profiles

International Standard Serial Number (ISSN)

  • 0143-9782

Electronic International Standard Serial Number (EISSN)

  • 1467-9892

Additional Document Info

start page

  • 301

end page

  • 314

volume

  • 10

issue

  • 4