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Composite Earnings Forecasting Efficiency

Author

Listed:
  • John B. Guerard

    (O'Connor & Associates, 141 West Jackson Boulevard, Chicago, Illinois 60604)

  • Carl R. Beidleman

    (Department of Finance, Lehigh University, Bethlehem, Pennsylvania 18015)

Abstract

Composite earnings-per-share models were estimated for 35 chemical, food, and utility firms during the 1979--1980 period. It is generally held that financial analysts produce earnings forecasts superior to time series model forecasts; however, the results of this study indicate that the average mean square forecasting error of analyst forecasts may be reduced by combining analyst and univariate time-series model forecasts. Despite the high degree of correlation existing among analyst and time-series forecasts, the ordinary least-squares model estimation of the composite-earnings model is a better forecasting model than the composite-earnings models estimated with ridge regression techniques.

Suggested Citation

  • John B. Guerard & Carl R. Beidleman, 1987. "Composite Earnings Forecasting Efficiency," Interfaces, INFORMS, vol. 17(5), pages 103-113, October.
    • Handle: RePEc:inm:orinte:v:17:y:1987:i:5:p:103-113
    DOI: 10.1287/inte.17.5.103
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    Cited by:

    1. Elkin Castaño V. & Luis Fernando Melo Velandia, 1998. "Métodos De Combinación De Pronósticos:Una Aplicación A La Inflación Colombiana," Borradores de Economia 3212, Banco de la Republica.
    2. Vera Shanshan Lin, 2019. "Judgmental adjustments in tourism forecasting practice: How good are they?," Tourism Economics, , vol. 25(3), pages 402-424, May.
    3. Webby, Richard & O'Connor, Marcus, 1996. "Judgemental and statistical time series forecasting: a review of the literature," International Journal of Forecasting, Elsevier, vol. 12(1), pages 91-118, March.

    More about this item

    Keywords

    finance: portfolio;

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