An Empirical Examination of the Divergence Between Managers' and Analysts' Earnings Forecasts PDF Download
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Author: Somnath Das Publisher: ISBN: Category : Languages : en Pages : 55
Book Description
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.
Author: Somnath Das Publisher: ISBN: Category : Languages : en Pages : 55
Book Description
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.
Author: Michael Tang Publisher: ISBN: Category : Investment analysis Languages : en Pages : 104
Book Description
"I develop and explore a new dimension of earnings guidance - guidance consistency. Contrary to the conventional view that managers make an independent guidance decision each period, I find empirical support for the dynamic disclosure theory, which argues that managers consider earnings guidance as a multi-period decision and try to maintain consistency in guidance. Once I account for past guidance in a logistic model, several known guidance determinants are no longer significant in explaining management guidance decisions. In contrast, past guidance remains significant both statistically and economically across various specifications, suggesting that management guidance decisions are largely predetermined. Moreover, the guidance consistency measure is more robust than the conventional frequency-based 'habitual' variable in explaining future guidance. The results still hold in a Heckman selection model and after propensity score matching, mitigating the concern that guidance consistency is merely driven by firms operating in stable environments. Moreover, firms with a history of consistent (inconsistent) guidance are less (more) responsive to various guidance determinants, and omit guidance primarily due to lack of private information (past unsuccessful expectation management). Compared with inconsistent guiders, consistent guiders are more likely to: (a) guide earlier in the quarter; (b) bundle guidance with earnings announcements; (c) issue guidance even when analyst forecasts are already aligned with managers' own estimates; and (d) also maintain consistency in their guidance timing or specificity. After controlling for analyst forecasts before guidance, their forecasts after guidance are more likely to be aligned with guidance issued by consistent guiders than by inconsistent guiders. My evidence suggests that both managers and analysts view guidance as a multi-period decision, supporting the dynamic disclosure theory"--Page iv.
Author: Yuan Shi (Ph.D.) Publisher: ISBN: Category : Business forecasting Languages : en Pages : 98
Book Description
My dissertation examines whether managers issuing earnings guidance learn from the forecast errors in prior earnings guidance issued by them. Using data on quarterly earnings forecasts issued by managers during the period from 2001 to 2016, I find results that are consistent with managers learning from their previous forecast errors to improve their forecast accuracy. However, the intensity of the managers' reactions to previous forecast errors is asymmetric. Consistent with prior literature that emphasizes the importance of meeting or beating forecasts for managers, certain managers that miss their own forecasts tend to be conservative enough in their future forecasts to avoid missing their own forecasts again. However, as expected, when the managers have met or beaten their previous forecasts, they have a smaller forecast error, but they still beat their previous forecasts. Additional analysis suggests that these effects persist even after controlling for potential earnings management to achieve these earnings targets. I also examine the impact of managerial attributes and board governance characteristics on the learning process. My analysis suggests that while CEO overconfidence and CFO overconfidence appear to impede learning, Managerial ability, CEO duality and outside CEO(s) as director(s) strengthen the learning effect. My findings shed light on an important aspect of management guidance and may have implications for users of this information such as financial analysts and investors.
Author: Joshua Ronen Publisher: Springer Science & Business Media ISBN: 0387257713 Category : Business & Economics Languages : en Pages : 587
Book Description
This book is a study of earnings management, aimed at scholars and professionals in accounting, finance, economics, and law. The authors address research questions including: Why are earnings so important that firms feel compelled to manipulate them? What set of circumstances will induce earnings management? How will the interaction among management, boards of directors, investors, employees, suppliers, customers and regulators affect earnings management? How to design empirical research addressing earnings management? What are the limitations and strengths of current empirical models?
Author: Somnath Das
Author: Somnath Das
Author: Michael Tang
Author: Gary Allen Porter
Author: Sanjeev Bhojraj
Author: Yuan Shi (Ph.D.)
Author: Gordian A. Ndubizo
Author: Christopher D. Hodgdon
Author: Dwight David McIntyre
Author: Joshua Ronen
Author: Patricia Colleen O'Brian