Explaining the Surprising Performance of Whisper Forecasts of Earnings

2008 ◽  
Author(s):  
Susan M. Machuga ◽  
Karen Teitel ◽  
Ray J. Pfeiffer
Keyword(s):  
Whisper Forecasts

Whisper forecasts of earnings per share: Is anyone still listening?

2011 ◽  
Vol 64 (5) ◽  
pp. 476-482 ◽  
Author(s):  
William D. Brown ◽  
Guy D. Fernando
Keyword(s):  
Earnings Per Share ◽  
Whisper Forecasts

Whisper forecasts of quarterly earnings per share

1999 ◽  
Vol 28 (1) ◽  
pp. 27-50 ◽  
Author(s):  
Mark Bagnoli ◽  
Messod D. Beneish ◽  
Susan G. Watts
Keyword(s):  
Quarterly Earnings ◽  
Earnings Per Share ◽  
Whisper Forecasts

Whisper Forecasts of Quarterly Earnings per Share

1998 ◽  
Author(s):  
Mark E. Bagnoli ◽  
Messod Daniel Beneish ◽  
Susan G. Watts
Keyword(s):  
Quarterly Earnings ◽  
Earnings Per Share ◽  
Whisper Forecasts

How Analysts and Whisperers Use Fundamental Accounting Signals to Make Quarterly EPS Forecasts

2015 ◽  
Vol 32 (3) ◽  
pp. 401-422 ◽  
Author(s):  
Susan Wahab ◽  
Karen Teitel ◽  
Bernard Morzuch
Keyword(s):  
Cash Flow ◽  
Explanatory Power ◽  
Forecast Model ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Panel Regression ◽  
Market Participants ◽  
Earnings Per Share ◽  
Incremental Information ◽  
Whisper Forecasts

We examine the relative efficiency of whisperers’ and analysts’ forecasts of one-quarter-ahead earnings per share (EPS) and identify commonalities and differences in their use of fundamentals to forecast earnings. Results suggest that (a) fundamentals that focus on sales and cost of sales are relevant in explaining one-quarter-ahead EPS changes; (b) whisperers focus on cash flow fundamentals and accrual-based earnings measures in their one-quarter-ahead forecasts, whereas analysts focus on only cash flow fundamentals; and (c) although neither analysts nor whisperers fully incorporate information contained in fundamentals and accrual-based earnings measures in their forecasts, whisperers’ earnings forecast model (forecast errors model) exhibits higher (lower) explanatory power than that of analysts. We also examine robustness of our results by reestimating the models using a two-way random-effects panel data estimator. Although our conclusions remain the same, more statistically significant fundamentals emerge in panel regression results. Evidence presented in this article is consistent with (a) whisperers being different from analysts and (b) whisper forecasts containing unique incremental information beyond that of analysts’ forecasts. Market participants may want to consider using both forecasts when making investment decisions.

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