Diversified Firms and Analyst Earnings Forecasts: The Role of Management Guidance at the Segment Level

2019 ◽  
Vol 18 (3) ◽  
pp. 1-38 ◽  
Author(s):  
Paul André ◽  
Andrei Filip ◽  
Rucsandra Moldovan
Keyword(s):  
Earnings Forecasts ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Group Level ◽  
Financial Analyst ◽  
Management Guidance ◽  
Analyst Earnings ◽  
Diversified Firms ◽  
Matched Samples

ABSTRACT Using a unique, manually collected dataset, we are the first to analyze the role that management guidance at the segment level plays for the financial analyst earnings forecasts of diversified firms. About half of the diversified European firms in the sample provide segment-level guidance (SLG), with considerable variation in precision and disaggregation. We find that (1) analyst earnings forecast errors are smaller, and (2) the magnitude of disagreement between individual forecasts and the average forecast is lower for firms that provide SLG, beyond the effect of group-level guidance. The results hold in matched samples and within-firm analyses around SLG initiation. We further show that the results are stronger in situations characterized by higher information asymmetry, but not in situations characterized by operational complexity. Overall, the results imply that SLG mitigates, to some extent, the difficult task that financial analysts face when valuing diversified companies.

The Rewards for Meeting or Beating Managers' Own Earnings Guidance

2020 ◽  
Author(s):  
Kai Wai Hui ◽  
Alfred Z. Liu ◽  
Yao Zhang
Keyword(s):  
Stock Return ◽  
Earnings Forecasts ◽  
Earnings Guidance ◽  
Cross Sectional ◽  
Earnings Expectations ◽  
Future Performance ◽  
Management Guidance ◽  
Prior Literature ◽  
Management Earnings Guidance ◽  
Analyst Earnings

This study documents a stock return premium for meeting or beating management's own earnings guidance (MBMG) that is separate and distinct from the premium for meeting or beating analysts' earnings forecasts (MBAF) documented in prior literature. Cross-sectional analyses reveal that the MBMG premium relative to the MBAF premium increases when management guidance is more informative. We also find that MBMG is incrementally informative about a firm's future performance after considering MBAF. Our findings suggest that investors consider management earnings guidance to be a performance threshold in addition to analyst earnings forecasts when forming earnings expectations.

Discussion: “Dispersion in Analysts' Earnings Forecasts as a Measure of Uncertainty”

1998 ◽  
Vol 13 (3) ◽  
pp. 271-274 ◽  
Author(s):  
Lawrence D. Brown
Keyword(s):  
Stock Price ◽  
Annual Report ◽  
Earnings Forecasts ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Data Set ◽  
Forecast Dispersion ◽  
Forecast Revision ◽  
Analyst Earnings ◽  
The Impact

This paper tackles an interesting question; namely, whether dispersion in analysts' earnings forecasts reflects uncertainty about firms' future economic performance. It improves on the extant literature in three ways. First, it uses detailed analyst earnings forecast data to estimate analyst forecast dispersion and revision. The contrasting evidence of Morse, Stephan, and Stice (1991) and Brown and Han (1992), who respectively used consensus and detailed analyst data to examine the impact of earnings announcements on forecast dispersion, suggest that detailed data are preferable for determining the data set on which analysts' forecasts are conditioned. Second, it relates forecast dispersion to both analyst earnings forecast revision and stock price reaction to the subsequent earnings announcement. Previous studies related forecast dispersion to either analyst forecast revision (e.g., Stickel 1989) or to subsequent stock price movements (e.g., Daley et al. [1988]), but not to both revision and returns. Third, it includes the interim quarters along with the annual report. In contrast, previous research focused on the annual report, ignoring the interims (Daley et al. [1988]).

scholarly journals The Role of Anchoring Bias in the Equity Market: Evidence from Analysts’ Earnings Forecasts and Stock Returns

2012 ◽  
Vol 48 (1) ◽  
pp. 47-76 ◽  
Author(s):  
Ling Cen ◽  
Gilles Hilary ◽  
K. C. John Wei
Keyword(s):  
Stock Returns ◽  
Earnings Forecasts ◽  
Equity Market ◽  
Stock Splits ◽  
Forecast Errors ◽  
Forecast Revisions ◽  
Earnings Per Share ◽  
Earnings Surprises ◽  
Anchoring Bias

AbstractWe test the implications of anchoring bias associated with forecast earnings per share (FEPS) for forecast errors, earnings surprises, stock returns, and stock splits. We find that analysts make optimistic (pessimistic) forecasts when a firm’s FEPS is lower (higher) than the industry median. Further, firms with FEPS greater (lower) than the industry median experience abnormally high (low) future stock returns, particularly around subsequent earnings announcement dates. These firms are also more likely to engage in stock splits. Finally, split firms experience more positive forecast revisions, more negative forecast errors, and more negative earnings surprises after stock splits.

The Moderating Effect of Industry Concentration on the Relations Between External Attributes and the Properties of Analyst Earnings Forecast

2013 ◽  
Vol 16 (03) ◽  
pp. 1350019 ◽  
Author(s):  
Yu-Cheng Chen ◽  
Chiung-Yao Huang ◽  
Pei-I Chou
Keyword(s):  
Forecast Accuracy ◽  
Earnings Forecasts ◽  
Moderating Effect ◽  
Industry Concentration ◽  
Earnings Forecast ◽  
Moderating Effects ◽  
Forecast Dispersion ◽  
Earnings Surprise ◽  
Using Data ◽  
Analyst Earnings

Based on the work of earlier studies, the main objective of this study is to determine whether the properties of analyst earnings forecast are related to the interaction effects of external attributes and industry concentration that were not the focus of previous research. Specifically, this study examines the relations between external attributions and the properties of analyst earnings forecasts. Furthermore, we explore the moderating effect of industry concentration on the relations between external attributions and the properties of analyst earnings forecasts. Using data from Compustat and I/B/E/S, we provide evidence that analysts' earnings forecast accuracy is lower and the forecast dispersion is larger for firms with more earnings surprise. Firms with more analysts' forecasts covering are associated with higher forecast accuracy, but not necessarily higher forecast dispersion. The moderating effects of industry concentration on the relationships between earnings surprise, the number of estimates covering the company and forecast accuracy are particularly strong. In addition, the moderating effects of industry concentration on the relationship between earnings surprise, the number of estimates covering the company and the forecast dispersion are partially supported. Overall, the industrial concentration factor either magnifies or alleviates the effect of external attributions on analyst's forecast accuracy and forecast dispersion.

Implications of Cost Behavior for Analysts' Earnings Forecasts

2015 ◽  
Vol 28 (1) ◽  
pp. 57-80 ◽  
Author(s):  
Mustafa Ciftci ◽  
Raj Mashruwala ◽  
Dan Weiss
Keyword(s):  
Earnings Forecasts ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Clear Pattern ◽  
Earnings Prediction ◽  
Cost Behavior ◽  
Cost Variability ◽  
Available Information ◽  
Cost Stickiness ◽  
Jel Classifications

ABSTRACT Recent work in management accounting offers several novel insights into firms' cost behavior. This study explores whether financial analysts appropriately incorporate information on two types of cost behavior in predicting earnings—cost variability and cost stickiness. Since analysts' utilization of information is not directly observable, we model the process of earnings prediction to generate empirically testable hypotheses. The results indicate that analysts “converge to the average” in recognizing both cost variability and cost stickiness, resulting in substantial and systematic earnings forecast errors. Particularly, we find a clear pattern—inappropriate incorporation of available information on cost behavior in earnings forecasts leads to larger errors in unfavorable scenarios than in favorable ones. Overall, enhancing analysts' awareness of the expense side is likely to improve their earnings forecasts, mainly when sales turn to the worse. JEL Classifications: M41; M46; G12.

Audit Quality and Properties of Analyst Earnings Forecasts

2008 ◽  
Vol 83 (2) ◽  
pp. 327-349 ◽  
Author(s):  
Bruce K. Behn ◽  
Jong-Hag Choi ◽  
Tony Kang
Keyword(s):  
Financial Reporting ◽  
Audit Quality ◽  
Forecast Accuracy ◽  
Reporting Quality ◽  
Earnings Forecasts ◽  
Earnings Forecast ◽  
Forecast Dispersion ◽  
Industry Specialization ◽  
Big 5 ◽  
Analyst Earnings

Under the assumption that audit quality relates positively to unobservable financial reporting quality, we investigate whether audit quality is associated with the predictability of accounting earnings by focusing on analyst earnings forecast properties. The evidence shows that analysts' earnings forecast accuracy is higher and the forecast dispersion is smaller for firms audited by a Big 5 auditor. We further find that auditor industry specialization is associated with higher forecast accuracy and less forecast dispersion in the non-Big 5 auditor sample but not in the Big 5 auditor sample. Overall, our results suggest that high-quality audit provided by Big 5 auditors and industry specialist non-Big 5 auditors is associated with better forecasting performance by analysts.

Absolute Forecast Errors of Earnings in Malaysian IPO Prospectuses: The Impact of Ethnic Diversity

2014 ◽  
Vol 68 (3) ◽  
Author(s):  
Mohammed Abdullah Ammer ◽  
Nurwati A. Ahmad-Zaluki
Keyword(s):  
Ethnic Diversity ◽  
Boards Of Directors ◽  
Forecast Error ◽  
Forecast Accuracy ◽  
Earnings Forecasts ◽  
Ordinary Least Squares ◽  
Audit Committees ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
The Impact

The main focus of this paper is the earnings forecast, a vital information included in IPO prospectus. Specifically, our paper examined the impact of ethnic diversity groups on the boards of directors and audit committees in terms of earnings forecast accuracy. We are motivated by the lack of prior studies related to investigating IPO earnings forecast. Cross-sectional Ordinary Least Squares (OLS) modeling was conducted on 190 Malaysian IPOs from 2002 to 2012. For the evaluation of earnings forecast accuracy, we mathematically used the metric of Absolute Forecast Error (AFER). Moreover, for the test of robustness, we used the metric of Squared Forecast Error (SQFER) as error measurement, as it mostly deals with large errors. The empirical results indicate that the ethnic diversity groups on boards and audit committees have an impact on the accuracy of earnings forecasts. However, the evidence is significant for Chinese and Malay serving on boards but insignificant in terms of Chinese and Malay serving on audit committee. The findings indicate that multi-ethnic groups in Malaysian IPO companies could hinder the capability of IPO companies to achieve accurate earnings forecasts in their prospectuses.

scholarly journals Alternative Disclosure Methods For Accounting Changes And Analysts Earnings Forecasts

2011 ◽  
Vol 12 (3) ◽  
pp. 48 ◽  
Author(s):  
Thomas A. Buchman ◽  
C. Patrick Fort
Keyword(s):  
Forecast Accuracy ◽  
Cumulative Effect ◽  
Earnings Forecasts ◽  
The Other ◽  
Alternative Methods ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Generally Accepted Accounting Principles ◽  
Accounting Principles ◽  
Accounting Changes

<span>Generally accepted accounting principles (GAAP) require that firms changing accounting principles must report the change in one of three ways: the cumulative effect method, the retroactive restatement method, or a no-adjustment (prospective) method. The method a company should use is determined by the type of change being made. This raises the following question: can it be demonstrated that one of these methods is better, in some sense, than the other methods? A major problem in evaluating alternative methods of accounting of the same economic event and in deciding which one method should be adopted as GAAP is that it is impossible to objectively determine which of the alternatives is best. However, it is possible to rank alternatives on one dimension of interest-which method minimizes the income forecasts in years after the change. We obtained a sample of forms making accounting changes and formed three portfolios of firms based on the method they used to account for the change in accounting principle. We then compared financial analysts earnings forecast errors for the firms in the three portfolios. After controlling for relevant variables, we found that, in the year firms made accounting changes the firms making the changes requiring retroactive restatement had significantly larger forecast errors than the firms making changes requiring the other forms of disclosure, but in years subsequent to the year of change there were no significant differences in forecast errors. This leads us to the conclusion that, from an earnings forecast accuracy perspective, there is no advantage to calculating and presenting the cumulative effect of an accounting change or in preparing restated or pro-forma financial statements.</span>

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