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An Empirical Examination of the Divergence between Managers’ and Analysts’ Earnings Forecasts
Author(s) -
Das Somnath,
Kim Kyonghee,
Patro Sukesh
Publication year - 2017
Publication title -
contemporary accounting research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.769
H-Index - 99
eISSN - 1911-3846
pISSN - 0823-9150
DOI - 10.1111/1911-3846.12351
Subject(s) - earnings , consensus forecast , quarter (canadian coin) , divergence (linguistics) , econometrics , economics , actuarial science , business , financial economics , finance , geography , linguistics , philosophy , archaeology
We study circumstances when analysts’ forecasts diverge from managers’ forecasts after management guidance, and the consequences of this divergence for investors and analysts. Our results show that investors’ return response to earnings surprises based on analyst forecasts is significantly weaker when analyst and management forecasts diverge, and that this attenuating effect is stronger when the management forecast is more credible. When the divergent management forecast is more accurate than the analyst consensus forecast, the subsequent‐quarter analyst consensus forecast is significantly more accurate than that of the current quarter, and exhibits less serial correlation. Overall, our findings suggest that, when analyst and management forecasts diverge, investors find the two sources to contain complementary information, and analysts learn to improve their subsequent forecasts.