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The Dynamics of Earnings Forecast Management

The Dynamics of Earnings Forecast Management
Author: Dan Bernhardt
Publisher:
Total Pages: 32
Release: 2003
Genre:
ISBN:

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This paper investigates whether firms manage analyst forecasts to generate positive earnings surprises and the consequences of such forecast management. We first document that firms quot;talk downquot; forecasts. Forecasts of quarterly earnings issued later in the forecasting horizon grow increasingly pessimistic on average. More importantly, the exact timing of changes in earnings forecasts turn out to be a key determinant of whether a firm indeed succeeds at generating positive earnings surprises. In particular, (i) changes in consensus early in the forecast horizon have no effect on the probability that earnings will exceed the consensus, (ii) late forecasts that raise the consensus sharply reduce the probability of a positive earnings surprise, and (iii) late forecasts that lower the consensus sharply raise the probability of a positive earnings surprise. These last two findings are the opposite of what would be predicted if deviations of late forecasts from the consensus were due to new information arrival. We then find evidence that investors are systematically quot;misledquot; by late arriving forecasts. In particular, downward revisions in the consensus lead to large positive cumulative abnormal returns following the earnings announcement. Finally, while the finding that investors reward firms that successfully manage forecasts down might seem to provide a rationale for downward forecast management, this is not so. Specifically, controlling for the extant earnings-consensus forecast differential, the negative impact of downward forecast revisions on stock price dominates the stock price appreciation following the earnings announcement. This begs the question: Firms manage analyst forecasts (down), but why?


Real Earnings Management and the Properties of Analysts' Forecasts

Real Earnings Management and the Properties of Analysts' Forecasts
Author: Lisa Eiler
Publisher:
Total Pages: 43
Release: 2016
Genre:
ISBN:

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We examine how analysts' earnings forecast properties vary when accounting information is more difficult to process. Specifically, we investigate whether analysts' forecast properties are associated with traditional real earnings management (REM) measures. We hypothesize and find that analysts' forecast errors and dispersion are greater for REM firms. Next, we investigate cross-sectional differences among REM firms based on the presence of management guidance. We find some evidence that management guidance reduces the association between REM and analysts' forecast error, and strong evidence that management guidance reduces the association between REM and dispersion. Finally, we investigate cross-sectional differences among REM firms based on their earnings management incentives. We find that firms with low earnings management incentives drive the association between REM and analysts' forecast error and dispersion. This result suggests earnings are most difficult to forecast for REM firms lacking obvious financial reporting objectives. Our results are consistent across numerous proxies for REM. To the best of our knowledge, our paper is the first to provide robust evidence of a relation between REM and the properties of analysts' forecasts.


Management Earnings Forecasts

Management Earnings Forecasts
Author: Hwa Deuk Yi
Publisher:
Total Pages: 236
Release: 1994
Genre: Corporate profits
ISBN:

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Earnings Management

Earnings Management
Author: Joshua Ronen
Publisher: Springer Science & Business Media
Total Pages: 587
Release: 2008-08-06
Genre: Business & Economics
ISBN: 0387257713

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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?


An Empirical Test of Learning in Management Earnings Forecasts

An Empirical Test of Learning in Management Earnings Forecasts
Author: Yuan Shi (Ph.D.)
Publisher:
Total Pages: 98
Release: 2019
Genre: Business forecasting
ISBN:

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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.


Management Earnings Forecast Issuance and Earnings Surprises

Management Earnings Forecast Issuance and Earnings Surprises
Author: T. Sabri Oncu
Publisher:
Total Pages: 44
Release: 2019
Genre:
ISBN:

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This paper studies the impact of firms' public management guidance on their ability to meet or beat analysts' consensus forecasts. The model set forth here accounts for endogeneity of firms' management earnings forecast issuance to examine whether their public management guidance raises their probability of generating favorable earnings surprises. In addition, the model allows for state dependence to investigate whether the firms' past outcomes have any impact on the probabilities of their meeting or beating analysts' consensus forecasts and management forecast issuance. Based on a panel dataset of 1,807 firms and 28,031 firm-quarters between 1994 and 2002, I find the following: Firstly, firms that meet or beat their own management forecast are more likely to meet or beat the analysts' consensus forecast. Secondly, firms with a long history of meeting or beating the analysts' consensus forecasts are more likely to repeat their previous performance. Thirdly, firms with a long history of meeting or beating their own forecasts are more likely to issue management forecasts that they can meet or beat. And lastly, firms with a long history of meeting or beating analysts' consensus forecasts are more likely to issue management forecasts that they can meet or beat. The evidence presented in this paper suggests that not only firms' public management guidance but also their past outcomes play an important role in their ability to generate favorable earnings surprises.