Towards a taxonomy of forecast error measures: A factor-comparative investigation of forecast error dimensions

Towards a taxonomy of forecast error measures: A factor-comparative investigation of forecast error dimensions

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Article ID: iaor19951546
Country: United Kingdom
Volume: 13
Issue: 4
Start Page Number: 409
End Page Number: 416
Publication Date: Aug 1994
Journal: International Journal of Forecasting
Authors: ,
Abstract:

This study explores the nature of information conveyed by 14 error measures drawn from the literature, using real-life forecasting data from 691 individual product items over six quarterly periods. Principal components analysis is used to derive factor solutions that are subsequently compared for two forecasting methods, a version of Holt’s exponential smoothing, and the random walk model (Naive 1). The results reveal four underlying forecast error dimensions that are stable across the two factor solutions. The potentially confounding influence of sales volume on the derived error dimensions is also explored via correlation analysis.

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