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Note---Revising Forecasts of Accounting Earnings: A Comparison with the Box-Jenkins Method

Author

Listed:
  • Charles H. Brandon

    (Rollins College)

  • Jeffrey E. Jarrett

    (University of Rhode Island)

  • Saleha B. Khumawala

    (University of Houston)

Abstract

The purpose of this study was to contribute to the literature concerning forecasting the time series of accounting earnings. To accomplish this objective an experiment was conducted to compare the performance of Theil's Optimal Linear Correction technique for revising quarterly Box-Jenkins and other naive model forecasts of accounting earnings against the unrevised forecasts. Several results of this study are of particular interest. First, the study indicated that the Watts-Griffin parsimonious model outperformed other firm specific Box-Jenkins models. Second, the Optimal Linear Correction produced revised forecasts that were uniformly more accurate than the original unadjusted forecasts. Finally, the naive extrapolative time series models outperformed Box-Jenkins forecasts of accounting earnings.

Suggested Citation

  • Charles H. Brandon & Jeffrey E. Jarrett & Saleha B. Khumawala, 1983. "Note---Revising Forecasts of Accounting Earnings: A Comparison with the Box-Jenkins Method," Management Science, INFORMS, vol. 29(2), pages 256-263, February.
    • Handle: RePEc:inm:ormnsc:v:29:y:1983:i:2:p:256-263
    DOI: 10.1287/mnsc.29.2.256
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    Cited by:

    1. Bianchi, Lisa & Jarrett, Jeffrey & Choudary Hanumara, R., 1998. "Improving forecasting for telemarketing centers by ARIMA modeling with intervention," International Journal of Forecasting, Elsevier, vol. 14(4), pages 497-504, December.
    2. Yim, Andrew & Schröder, David, 2012. "Industry Effects on Firm and Segment Profitability Forecasting: Do Aggregation and Diversity Matter?," MPRA Paper 39190, University Library of Munich, Germany.

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