Changes in Analysts' Information around Earnings Announcements

Orie E. Barron; Donal Byard; Oliver Kim

doi:10.2308/accr.2002.77.4.821

Changes in Analysts' Information around Earnings Announcements

The Accounting Review ◽

10.2308/accr.2002.77.4.821 ◽

2002 ◽

Vol 77 (4) ◽

pp. 821-846 ◽

Cited By ~ 147

Author(s):

Orie E. Barron ◽

Donal Byard ◽

Oliver Kim

Keyword(s):

Earnings Announcements ◽

Financial Analysts ◽

Earnings Forecasts ◽

Forecast Errors ◽

Accounting Disclosures

In this study we examine changes in the precision and the commonality of information contained in individual analysts' earnings forecasts, focusing on changes around earnings announcements. Using the empirical proxies suggested by the Barron et al. (1998) model that are based on the across-analyst correlation in forecast errors, we conclude that the commonality of information among active analysts decreases around earnings announcements. We also conclude that the idiosyncratic information contained in these individual analysts' forecasts increases immediately after earnings announcements, and that this increase is more significant as more analysts revise their forecasts. These results are consistent with theories positing that an important role of accounting disclosures is to trigger the generation of idiosyncratic information by elite information processors such as financial analysts (Kim and Verrecchia 1994, 1997).

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Concurrent Earnings Announcements and Analysts' Information Production

The Accounting Review ◽

10.2308/accr-52489 ◽

2019 ◽

Vol 95 (1) ◽

pp. 165-189 ◽

Cited By ~ 7

Author(s):

Matthew Driskill ◽

Marcus P. Kirk ◽

Jennifer Wu Tucker

Keyword(s):

Earnings Announcements ◽

Financial Analysts ◽

Earnings Forecasts ◽

Data Availability ◽

Limited Attention ◽

Conference Calls ◽

Stock Recommendations ◽

Rich Information ◽

Sample Firm ◽

Jel Classifications

ABSTRACT We examine whether financial analysts are subject to limited attention. We find that when analysts have another firm in their coverage portfolio announcing earnings on the same day as the sample firm (a “concurrent announcement”), they are less likely to issue timely earnings forecasts for the sample firm's subsequent quarter than analysts without a concurrent announcement. Among the analysts who issue timely earnings forecasts, the thoroughness of their work decreases as their number of concurrent announcements increases. In addition, analysts are more sluggish in providing stock recommendations and less likely to ask questions in earnings conference calls as their number of concurrent announcements increases. Moreover, when analysts face concurrent announcements, they tend to allocate their limited attention to firms that already have rich information environments, leaving behind firms in need of attention. Overall, our evidence suggests that even financial analysts, who serve as information specialists, are subject to limited attention. JEL Classifications: G10; G11; G17; G14. Data Availability: Data are publicly available from the sources identified in the paper.

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

Journal of Financial and Quantitative Analysis ◽

10.1017/s0022109012000609 ◽

2012 ◽

Vol 48 (1) ◽

pp. 47-76 ◽

Cited By ~ 69

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.

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

Journal of International Accounting Research ◽

10.2308/jiar-52502 ◽

2019 ◽

Vol 18 (3) ◽

pp. 1-38 ◽

Cited By ~ 1

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.

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Refining financial analysts’ forecasts by predicting earnings forecast errors

International Journal of Accounting and Information Management ◽

10.1108/ijaim-06-2016-0065 ◽

2017 ◽

Vol 25 (2) ◽

pp. 256-272 ◽

Cited By ~ 1

Author(s):

Tatiana Fedyk

Keyword(s):

Serial Correlation ◽

Design Methodology ◽

Financial Analysts ◽

Earnings Forecasts ◽

Autoregressive Process ◽

Earnings Forecast ◽

Forecast Errors ◽

Content Type ◽

Quarterly Earnings ◽

Prior Literature

Purpose The purpose of this paper is to examine the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm’s industry and the analyst’s experience and brokerage house affiliation. Prior research on financial analysts’ quarterly earnings forecasts has documented serial correlation in forecast errors. Design/methodology/approach Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, the consensus forecast errors are modeled as an autoregressive process. The model of forecast errors that best fits the data is AR(1), and the obtained autoregressive coefficients are used to predict consensus forecast errors. Findings Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors and proposes a series of refinements to the consensus. Originality/value These refinements were not presented in prior literature and can be useful to financial analysts and investors.

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Comprehensive Income: which potential effects on firms' performance evaluation and users' decision process?

FINANCIAL REPORTING ◽

10.3280/fr2015-002003 ◽

2016 ◽

pp. 55-94

Author(s):

Pier Luigi Marchini ◽

Carlotta D'Este

Keyword(s):

Performance Evaluation ◽

Decision Process ◽

Financial Analysts ◽

Listed Companies ◽

Financial Statement ◽

Comprehensive Income ◽

Other Comprehensive Income ◽

Gains And Losses ◽

The Impact

The reporting of comprehensive income is becoming increasingly important. After the introduction of Other Comprehensive Income (OCI) reporting, as required by the 2007 IAS 1-revised, the IASB is currently seeking inputs from investors on the usefulness of unrealized gains and losses and on the role of comprehensive income. This circumstance is of particular relevance in code law countries, as local pre-IFRS accounting models influence financial statement preparers and users. This study aims at investigating the role played by unrealized gains and losses reporting on users' decision process, by examining the impact of OCI on the Italian listed companies RoE ratio and by surveying a sample of financial analysts, also content analysing their formal reports. The results show that the reporting of comprehensive income does not affect the financial statement users' decision process, although it statistically affects Italian listed entities' performance.

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