analyst forecast dispersion
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2020 ◽  
Vol 13 (5) ◽  
pp. 98
Author(s):  
Shuang Liu ◽  
Juan Yao ◽  
Stephen Satchell

Prior studies found that analyst forecast dispersion predicts future market returns. Some prior studies attribute this predictability to the short-sale constraints in the market according to the overpricing theory. Using the U.S. data from 1981 to 2014, we find that the return predictive power of aggregate dispersion only exists prior to 2005. The investor sentiment index, as a proxy of short-sale constraints used by many studies, can only explain the dispersion effect prior to 2005. The investor sentiment index and other proxies such as institutional ownership and put options cannot explain the significant weakening of the dispersion effect after the global financial crisis. We argue that the dispersion-return relation is partly driven by the correlation between dispersion and conditional equity premium. Our evidence suggests that the short-sale constrained stocks do not experience a higher dispersion effect, which is contrary to what the overpricing theory predicts.


2020 ◽  
Vol 19 (3) ◽  
pp. 289-312
Author(s):  
Jundong (Jeff) Wang

Purpose This paper aims to investigate the association between analyst forecast dispersion and investors’ perceived uncertainty toward earnings. Design/methodology/approach A new measure for investors’ expectations of earnings announcement uncertainty is constructed, using changes in implied volatility of option contracts prior to earnings announcements. Unlike other proxies of uncertainty, this measure isolates the incremental uncertainty regarding the upcoming earnings announcement and is a forward-looking measure. Findings Using this new proxy, this paper finds a significant negative correlation between analyst forecast dispersion and investors’ uncertainty regarding the upcoming earnings announcements. Further tests show that this negative correlation is driven by analysts’ private information acquisition rather than analysts; uncertainty toward upcoming earnings announcements. Additional cross-sectional tests show that this negative relationship is more pronounced in the subsample with lower earnings quality. Social implications This paper helps to further the understanding of the information content of analyst forecast dispersion, particularly the ways in which they gather and produce private information and their incentives for so doing. Originality/value This paper introduces a new market-based and forward-looking proxy of earnings announcement uncertainty that should be useful in future research. This paper also provides original empirical evidence that analysts gather and produce an additional private information to the market when facing noisy signals and that their information reduces investors’ uncertainty toward upcoming earnings announcements.


2018 ◽  
Vol 10 (2) ◽  
pp. 130-145
Author(s):  
Raymond Cox ◽  
Ajit Dayanandan ◽  
Han Donker ◽  
John R. Nofsinger

PurposeFinancial analysts have been found to be overconfident. The purpose of this paper is to study the ramifications of that overconfidence on the dispersion of earnings estimates as a predictor of the US business cycle.Design/methodology/approachWhether aggregate analyst forecast dispersion contains information about turning points in business cycles, especially downturns, is examined by utilizing the analyst earnings forecast dispersion metric. The primary analysis derives from logit regression and Markov switching models. The analysis controls for sentiment (consumer confidence), output (industrial production), and financial indicators (stock returns and turnover). Analyst data come from Institutional Brokers Estimate System, while the economic data are available at the Federal Reserve Bank of St Louis Economic Data site.FindingsA rise in the dispersion of analyst forecasts is a significant predictor of turning points in the US business cycle. Financial analyst uncertainty of earnings estimate contains crucial information about the risks of US business cycle turning points. The results are consistent with some analysts becoming overconfident during the expansion period and misjudging the precision of their information, thus over or under weighting various sources of information. This causes the disagreement among analysts measured as dispersion.Originality/valueThis is the first study to show that analyst forecast dispersion contributions valuable information to predictions of economic downturns. In addition, that dispersion can be attributed to analyst overconfidence.


2016 ◽  
Vol 34 (1) ◽  
pp. 54-73 ◽  
Author(s):  
Ashiq Ali ◽  
Mark Liu ◽  
Danielle Xu ◽  
Tong Yao

This article examines whether a corporate disclosure practice is one of the reasons for the forecast dispersion anomaly—the negative relation between analyst forecast dispersion and future stock returns. Prior studies have shown that firms tend to delay the disclosure of bad news and that withholding of news leads to greater dispersion in analysts’ forecasts. Accordingly, we predict that firms with higher dispersion in analysts’ earnings forecasts are more likely to experience poor earnings in the subsequent quarter, and find evidence consistent with this prediction. After controlling for the relation between forecast dispersion and future earnings, we find that forecast dispersion is no longer significantly negatively related to future stock returns. These results suggest that temporary withholding of bad news by firms increases forecast dispersion among analysts and leads to low subsequent stock returns.


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