Is Analyst Earnings Forecast Ability Only Firm-Specific?

2007 ◽  
Author(s):  
Lawrence D. Brown ◽  
Emad Mohammad
Keyword(s):  
Earnings Forecast ◽  
Analyst Earnings

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]).

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.

Analyst earnings forecast trends in Pacific Rim countries

2004 ◽  
Vol 30 (7) ◽  
pp. 19-35 ◽  
Author(s):  
Stephen J. Ciccone ◽  
Ahmad Etebari
Keyword(s):  
Pacific Rim ◽  
Earnings Forecast ◽  
Analyst Earnings

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.

The Timeliness of Bad Earnings News and Litigation Risk

2012 ◽  
Vol 87 (6) ◽  
pp. 1967-1991 ◽  
Author(s):  
Dain C. Donelson ◽  
John M. McInnis ◽  
Richard D. Mergenthaler ◽  
Yong Yu
Keyword(s):  
Lower Incidence ◽  
Data Availability ◽  
Earnings Forecast ◽  
Litigation Risk ◽  
Prior Work ◽  
Press Releases ◽  
Analyst Earnings ◽  
Jel Classifications

ABSTRACT This study investigates whether the timely revelation of bad earnings news is associated with a lower incidence of litigation. The timeliness of earnings news is captured by a new measure based on the evolution of the consensus analyst earnings forecast. Holding total bad earnings news and other determinants of litigation constant, we find that earlier revelation of bad earnings news lowers the likelihood of litigation. This result holds for both settled and dismissed lawsuits. Further, we reconcile our findings with prior work that measures timeliness using managerial warnings via press releases. These tests suggest our findings are attributable to the ability of our timeliness measure to capture bad earning news revealed through disclosure channels beyond press releases. Data Availability: Data are available from public sources identified in the paper. JEL Classifications: K22; K41; M41.

Does an anti-corruption campaign increase analyst earnings forecast optimism?

2021 ◽  
pp. 101931
Author(s):  
Nian Li ◽  
Nianhang Xu ◽  
Rui Dong ◽  
Kam C. Chan ◽  
Xiaowei Lin
Keyword(s):  
Earnings Forecast ◽  
Analyst Earnings
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