THE PREDICTIVE PERFORMANCE OF THREE AUTOREGRESSIVE MOVING‐AVERAGE MODELS:A MONTE CARLO INVESTIGATION

John T. Batts and Robert McNown

Journal of Time Series Analysis, 1989, vol. 10, issue 4, 301-314

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.

Date: 1989
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https://doi.org/10.1111/j.1467-9892.1989.tb00030.x

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