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Robust approach to earnings forecast: A comparison

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  • Xiaojian Yu
  • Xiaoqian Zhang
  • Donald Lien

Abstract

This paper applies three robust approaches, namely, the MM estimation, the Theil–Sen estimation, and the quantile regression, to generate earnings forecasts in Chinese financial market and evaluates the forecast accuracy of these three methods based on three forecasting criteria. We examine six forecasting models where the predicted variables include earnings per share, net income, and three profitability measures. We show that the three robust methods significantly outperform the OLS method. Moreover, the MM estimation and the quantile regression have better forecast accuracy than the Theil–Sen approach.

Suggested Citation

  • Xiaojian Yu & Xiaoqian Zhang & Donald Lien, 2024. "Robust approach to earnings forecast: A comparison," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1530-1558, August.
    • Handle: RePEc:wly:jforec:v:43:y:2024:i:5:p:1530-1558
    DOI: 10.1002/for.3085
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    References listed on IDEAS

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