Serial Correlation in Management Earnings Forecast Errors*

2009 ◽  
Author(s):  
Guojin Gong ◽  
Laura Yue Li ◽  
Jundong (Jeff) Wang
Keyword(s):  
Serial Correlation ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Management Earnings Forecast

Serial Correlation in Management Earnings Forecast Errors

2011 ◽  
Vol 49 (3) ◽  
pp. 677-720 ◽  
Author(s):  
GUOJIN GONG ◽  
LAURA Y. LI ◽  
JEFF J. WANG
Keyword(s):  
Serial Correlation ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Management Earnings Forecast

Stickiness in Costs and Voluntary Disclosures: Evidence from Management Earnings Forecasts

2017 ◽  
Vol 30 (3) ◽  
pp. 211-234 ◽  
Author(s):  
Mustafa Ciftci ◽  
Feras M. Salama
Keyword(s):  
Earnings Forecasts ◽  
Positive Association ◽  
Job Security ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Management Earnings Forecasts ◽  
Voluntary Disclosures ◽  
Management Earnings Forecast ◽  
The Relationship ◽  
Cost Stickiness

ABSTRACT We investigate the relationship between cost stickiness and management earnings forecasts. Prior research suggests that earnings are more volatile for sticky cost firms resulting in greater earnings forecast errors. The greater forecast errors might increase investors' demand for information and induce managers to issue earnings forecasts. Alternatively, managers might refrain from issuing earnings forecasts for sticky cost firms because greater forecast errors might damage managers' credibility and adversely affect their job security. We find that cost stickiness is positively associated with management earnings forecast issuance, suggesting that the benefits outweigh the costs. Prior research also suggests that cost stickiness has negative implications for earnings. We find a positive association between cost stickiness and management earnings forecast errors, suggesting that managers do not fully incorporate the negative implications of cost stickiness into their forecasts. Finally, we find that analysts' forecast errors for sticky cost firms are greater than managers'. JEL Classifications: M41; M46; G12.

The Association Between Management Earnings Forecast Errors and Accruals

2008 ◽  
Author(s):  
Guojin Gong ◽  
Laura Yue Li ◽  
Hong Xie
Keyword(s):  
Earnings Forecast ◽  
Forecast Errors ◽  
Management Earnings Forecast

The Association between Management Earnings Forecast Errors and Accruals

2009 ◽  
Vol 84 (2) ◽  
pp. 497-530 ◽  
Author(s):  
Guojin Gong ◽  
Laura Yue Li ◽  
Hong Xie
Keyword(s):  
Earnings Forecasts ◽  
Positive Association ◽  
Business Environment ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Management Forecasts ◽  
Management Earnings Forecasts ◽  
Operating Environment ◽  
Management Earnings Forecast ◽  
Accrual Mispricing

ABSTRACT: We investigate the association between errors in management forecasts of subsequent year earnings and current year accruals. In an uncertain operating environment, managers' assessments of their firms' business prospects are imperfect. Since managers' imperfect business assessments influence both accruals generation and earnings projection, we hypothesize that management earnings forecasts exhibit greater optimism (pessimism) when accruals are relatively high (low). Consistent with this hypothesis, we find a positive association between management earnings forecast errors and accruals. This positive association is stronger for firms operating in a more uncertain business environment and for firms in industries exhibiting greater covariation between accruals and growth-related activities. Moreover, this positive association is significant when accruals likely reflect managers' true beliefs about firms' business prospects, but is nonexistent when accruals are likely manipulated to boost managers' trading gains. Supplementary analysis reveals that the presence of management earnings forecasts does not significantly reduce accrual mispricing.

Refining financial analysts’ forecasts by predicting earnings forecast errors

2017 ◽  
Vol 25 (2) ◽  
pp. 256-272 ◽  
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.

The Association between Unsystematic Security Returns and the Magnitude of Earnings Forecast Errors

1979 ◽  
Vol 17 (2) ◽  
pp. 316 ◽  
Author(s):  
William H. Beaver ◽  
Roger Clarke ◽  
William F. Wright
Keyword(s):  
Earnings Forecast ◽  
Forecast Errors ◽  
Security Returns

scholarly journals The Joint Effect of Accounting Knowledge and Self-serving Attribution on the Voluntary Disclosure of Management Earnings Forecast

2019 ◽  
Vol 12 (1) ◽  
pp. 91-127
Author(s):  
Kanjana Phonsumlissakul ◽  
Juthathip Audsabumrungrat ◽  
Supol Durongwatana
Keyword(s):  
Voluntary Disclosure ◽  
Joint Effect ◽  
Earnings Forecast ◽  
Management Earnings Forecast

Effects of Institutional Investors as Independent Outside Block-holders on Analysts’ Earnings Forecast Errors

2018 ◽  
Vol 16 (3) ◽  
pp. 27-53
Author(s):  
Sang Cheol Lee ◽  
Yunkeun Lee ◽  
Yong Sun Shin
Keyword(s):  
Institutional Investors ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Block Holders
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