An Explanation for Why Prior Stock Returns and Analysts' Earnings Forecast Revisions Predict Earnings Management and Forecast errors

Abstract

We propose that the combination of prior stock returns and analyst forecast revisions of current earnings can predict subsequent firm earnings manipulations and analyst forecast “errors” in a setting in which investors, analysts, and managers are rational and do not behave opportunistically. We find empirical support for the prediction that firms that earn large positive abnormal returns and for which contemporaneous analyst earnings forecast revisions are positive are more likely to manage earnings up or down to beat analyst forecasts, whereas firms that earn large negative abnormal returns and for which analyst forecast revision are negative are more likely to engage in extreme income-decreasing earnings management. When combined with the argument that analysts forecast an earnings number that excludes transitory and managed components, such forms of earnings manipulations will contribute to the presence of two well-documented asymmetries in cross-sectional distributions of analysts’ forecast errors; a higher incidence and magnitude of extreme bad news surprises than extreme good news surprises, and a higher incidence of small, good news surprises than small, bad news surprises. We discuss the implications of the empirical support we find for our hypotheses for interpreting prior findings, developing hypotheses, and designing empirical tests in the analyst forecast rationality, earnings management, and earnings response coefficient literatures. An Explanation for Why Prior Stock Returns and Analysts’ Earnings Forecast Revisions Predict Earnings Management and Forecast errors

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