An analysis of the accuracy of long-term earnings predictions

Kenneth S. Lorek, G. Lee Willinger

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper provides information on the long-term predictive ability of annual earnings numbers. We obtained a sample of 486 calendar, year-end firms that had complete quarterly earnings-per-share (eps) before extraordinary items available from 1978 to 1998. Firm-specific, quarterly, autoregressive-integrated-moving-average (ARIMA) time-series models were used to generate one through five year-ahead annual eps predictions across the 1994-1998 holdout period. Analysis of mean absolute percentage errors indicates: (1) firm-specific ARIMA models outperform so-called, common-structure, "primier" ARIMA models, (2) forecast errors from the firm-specific ARIMA time-series models ranged from 0.358 to 0.547 for one through five year-ahead annual eps predictions, (3) long-term earnings forecast accuracy is linked to firm size and earnings persistence, and (4) further research is needed to develop more powerful, long-term earnings prediction models suitable for use in conjunction with the abnormal earnings valuation model.

Original languageEnglish (US)
Title of host publicationAdvances in Accounting
PublisherJAI Press
Pages161-175
Number of pages15
Volume19
ISBN (Print)0762308710, 9780762308712
DOIs
StatePublished - Jan 1 2002
Externally publishedYes

ASJC Scopus subject areas

  • Accounting
  • Finance

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  • Cite this

    Lorek, K. S., & Lee Willinger, G. (2002). An analysis of the accuracy of long-term earnings predictions. In Advances in Accounting (Vol. 19, pp. 161-175). JAI Press. https://doi.org/10.1016/S0882-6110(02)19009-2