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The effect of industry classification on analyst following and the properties of their earnings forecasts

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  • Dennis Y. Chung
  • Karel Hrazdil
  • Xin Li

Abstract

Using a comprehensive data set, we compare four broadly available industry classification schemes (Standard Industrial Classification (SIC), North American Industry Classification System (NAICS), Fama–French classification (FF) and Global Industry Classification Standard (GICS)) in their effectiveness to group analysts and their earnings forecast properties. We demonstrate the advantage of the GICS to be consistent across different forecasting properties and across different groups of firms. Our results suggest that GICS should be utilized in research designs, either in the primary analysis or as a necessary corroboration.

Suggested Citation

  • Dennis Y. Chung & Karel Hrazdil & Xin Li, 2017. "The effect of industry classification on analyst following and the properties of their earnings forecasts," Applied Economics Letters, Taylor & Francis Journals, vol. 24(6), pages 417-421, March.
    • Handle: RePEc:taf:apeclt:v:24:y:2017:i:6:p:417-421
    DOI: 10.1080/13504851.2016.1197362
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    Cited by:

    1. Hrazdil, Karel & Li, Xin & Suwanyangyuan, Nattavut, 2022. "CEO happiness and forecasting," Global Finance Journal, Elsevier, vol. 52(C).

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