Evaluating the information content of earnings forecasts

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    2 Citations (Scopus)
    393 Downloads (Pure)

    Abstract

    This study develops a framework to compare the ability of alternative earnings forecast approaches to capture the market expectation of future earnings. Given prior evidence of analysts’ systematic optimistic bias, we decompose earnings surprises into analysts’ earnings surprises and adjustments based on alternative forecasting models. An equal market response to these two components indicates that the associated earnings forecast is a sufficient estimate of the market expectation of future earnings. To apply our framework, we examine four recent regression-based earnings forecasting models, alongside a simple earnings-based random walk model and analysts’ forecasts. Using the earnings forecasts of the model that satisfies our sufficiency condition, we identify a set of stocks for which the market is unduly pessimistic about future earnings. The investment strategy of buying and holding these stocks generates statistically significant abnormal returns. We offer an explanation as to why this and similar strategies might be successful.

    Original languageEnglish
    Pages (from-to)674-699
    Number of pages26
    JournalAccounting and Business Research
    Volume48
    Issue number6
    Early online date4 Jan 2018
    DOIs
    Publication statusPublished - 1 Oct 2018

    Keywords

    • Earnings forecasts
    • earnings response coefficient
    • market expectation of future earnings
    • analysts’ forecasts
    • portfolio selection

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