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Financial 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.

Whether 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.

A 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.

This 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.

The purpose of this paper is to examine the impact of management’s choice of forecast precision on the subsequent dispersion and accuracy of analysts’ earnings forecasts.

Using a sample of 3,584 yearly management earnings per share (EPS) forecasts and 10,287 quarterly management EPS forecasts made during the period of 2002-2007 and collected from the First Call database, the authors controlled for factors previously found to impact analysts’ forecast accuracy and dispersion and investigate the link between management forecast precision and attributes of the analysts’ forecasts.

Results provide empirical evidence that managements’ disclosure precision has a statistically significant impact on both the dispersion and the accuracy of subsequent analysts’ forecasts. It was found that the dispersion in analysts’ forecasts is negatively related to the management forecast precision. In other words, a precise management forecast is associated with a smaller dispersion in the subsequent analysts’ forecasts. Evidence consistent with accuracy in subsequent analysts’ forecasts being positively associated with the precision in the management forecast was also found. When the present analysis focuses on range forecasts provided by management, it was found that lower precision (a larger range) is associated with a larger dispersion among analysts and larger forecast errors.

Evidence suggests a consistency in inferences across both annual and quarterly earnings forecasts by management. Accordingly, recent calls to eliminate earnings guidance through short-term quarterly management forecasts may have failed to consider the linkage between the attributes (precision) of those forecasts and the dispersion and accuracy in subsequent analysts’ forecasts.

This study contributes to the literature on both management earnings forecasts and analysts’ earnings forecasts. The results assist in policy deliberations related to calls to eliminate short-term management earnings guidance.

This paper aims to investigate the association between analyst forecast dispersion and investors’ perceived uncertainty toward earnings.

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.

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.

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.

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.

The purpose of this study is to use implied volatilities from exchange traded options to examine the interaction between analysts’ forecast revisions and the market’s perception of uncertainty about firm value.

The authors examine how characteristics of individual forecast revisions, e.g. news and changes in dispersion of forecasts, affect changes in implied volatilities, whether analysts use the observable changes in implied volatilities to inform their forecast revisions and whether changes in dispersion of forecasts are correlated with changes in implied volatilities.

The authors find that good (bad) news forecast revisions reduce (increase) investors’ perception of uncertainty about firm value, analysts do not appear to use changes in implied volatilities to shade their forecast revisions to good/bad news and dispersion of forecasts are a reasonable proxy for uncertainty about firm value as indicated by their correlation with implied volatilities.

Recent research on analysts’ forecast revisions and management forecasts has focused on risk perception rather than value. This paper extends this work with a risk metric based on market transactions in both a short and long window analysis, as well as univariate and multivariate analysis.

This study examines the impact of annual report disclosures on analysis' forecasts for a sample of firms listed on the Stock Exchange of Singapore (SES). We examine the relation between the level of corporate disclosure and accuracy of analysts' earnings forecasts, dispersion in analysts' earnings forecasts, and the size of analyst following. The results reveal that the level of annual report disclosures is positively related to the accuracy of earnings forecasts by analysts, provided there is no big earnings surprise, and is also positively related to analyst following. We also find that the level of corporate disclosure is negatively related to dispersion in analysts' earnings forecasts provided there is no big earnings surprise. Tints, this study shows that more corporate disclosures by Singapore firms lead to more accuracy and less dispersion in the earnings forecasts among analysts. Furthermore, greater corporate disclosure can also lead to greater analyst interest in the firm.

This study aims to explore the relationship between product market competition (competition hereafter) and the quality of analysts’ forecasts.

This study uses industry-level (i.e. Herfindahl–Hirschman index), as well as firm-level (i.e. Lerner index) measures of competition and uses forecast accuracy and forecasts dispersion as proxies for analysts’ forecast quality. Further, this study considers a sample of Chinese-listed manufacturing companies for the period spanning 2005 to 2016 and uses various estimation techniques to empirically test the hypothesized relationship.

The results show that firms in highly competitive industries are characterized by greater accuracy and smaller dispersion in forecasts. Further, this positive association is more pronounced in SOEs as compared to NSOEs, and in industries characterized by intense competition. The sensitivity analysis further endorses the main results.

Presenting theoretical and empirical evidence, this study suggests that regulatory bodies should take steps to promote the competitive environment in China. This can help financial analysts in developing more accurate and reliable forecasts and ultimately can bring informational efficiency to the market. Finally, investors would be able to perform their business valuation process in a better way and make economic-useful decisions regarding their capital resource allocation.

The contribution of the current research is threefold: first, it adds to the limited literature available on this specific topic; second, this study examines the issue in China and further single out the influence of state-ownership and intensity of competition on the relation between competition and forecast properties; and third, this study provides theoretical arguments for the positive association between competition and forecasts quality while setting directions for future research on the topic and suggests the potential channels such as the reporting quality channel and the information disclosure channel that need to be explored further, to better understand the mechanism where competition influences the quality of analysts’ forecasts.

European countries are likely to increasingly adopt integrated reporting (IR) voluntarily, after the 2014/95/EU Directive is revised and other initiatives are implemented. Therefore, the present study provides insights on the relevance of IR in voluntary contexts by exploring analysts' reactions to the release of integrated reports in diverse institutional settings.

Drawing on voluntary disclosure theory, a quantitative empirical research method is used to explore the moderating role of country-level institutional characteristics on the associations between voluntary IR release and analyst forecast accuracy and dispersion.

IR informativeness is not uniform in the voluntary context and institutional settings play a moderating role. IR release is associated with increased consensus among analyst forecasts. However, in countries with weak institutional enforcement, a reverse association is detected, indicating that analysts rely largely on IR where the institutional setting strongly protects investors. Although a strong institutional setting boosts the IR release usefulness in terms of accuracy, it creates noise in analyst consensus.

Academics can appreciate the usefulness of voluntary IR across the institutional enforcement contexts.

Managers can use these findings to understand opportunities offered by IR voluntary release. The study recommends that policymakers, standard setters and regulators strengthen the institutional enforcement of sustainability disclosure.

This study is a unique contribution to recent calls for research on the effects of nonfinancial disclosure regulation and on IR “impacts”. It shows on the international scale that IR usefulness for analysts is moderated by institutional patterns, not country-level institutional characteristics.

Anecdotal evidence suggests that emerging economy enterprises face higher uncertainty in business operations compared to their counterparts in more developed economies. However, there is little empirical evidence on this issue. The objective of this study is to fill this void in the literature and examine whether there is an association between the level of development of home country economy of a multinational corporation and uncertainty about future earnings measured by dispersion in analysts' earnings forecasts. After controlling for various firm‐ and country‐level factors, I find that the forecast dispersion tends to be larger for emerging economy enterprises (i.e., non‐U.S. firms cross‐listed in the U.S. whose home country economy is better characterized as emerging) than for developed economy enterprises (i.e., non‐U.S. firms cross‐listed in the U.S. whose home country economy is better characterized as developed), despite the fact that the emerging economy enterprises tend to be more heavily followed by analysts. Overall, the evidence supports the view that business uncertainty tends to be higher in emerging economies and highlights inherent difficulties associated with predicting future firm performance of the emerging economy enterprises.

This paper aims to investigate the informativeness of rhetorical impression management patterns of CEO letters and examines whether these rhetorical features affect financial analysts’ forecasting behaviour.

The authors use textual analysis on a sample of 526 CEO letters of US firms and apply factor analysis on individual linguistic style measures to identify co-occurrence patterns of style features.

The authors identify three holistic style patterns (assertive acclaiming, cautious plausibility-based framing and logic-based rationalizing) and find that assertive rhetorical feature in CEO letters is negatively related with the dispersion of financial analysts’ earnings forecasts and positively associated with earnings forecast accuracy. CEOs’ use of a rationalizing rhetorical pattern tends to decrease the dispersion of financial analysts’ earnings, whereas a cautious plausibility-based rhetorical position is only marginally instrumental in getting more accurate earnings predictions.

Whilst impression management communication is often theorized as manipulative and void of real information content, the findings suggest that impression management serves both self-presentation and information-sharing purposes.

This paper elaborates on the co-occurrence of style characteristics in management communication and is a first attempt to validate the external ramifications of holistic style profiles of corporate narratives by focusing on an economic target audience.

This study aims to examine the effects of product market competition (PMC) on analysts’ earnings forecast attributes, particularly forecast accuracy and dispersion. The authors also investigate whether investor protection moderates the relationship between PMC and forecast attributes.

The sample covers 49,578 firm-year observations from 38 countries. This study uses an ordinary least squares regression, a Heckman two-stage regression and an instrumental two-stage least squares regression.

This study finds that PMC is associated with higher forecast accuracy and lower dispersion. The results also show that investor protection enhances the effect of PMC on forecast accuracy and dispersion. These findings imply that countries with strong investor protection have a better information environment, as exhibited by the stronger relationship between PMC and analysts’ forecast properties.

The findings highlight the importance of strong governance mechanisms in both the country and industry environments. Policymakers, including government agencies and financial regulators, can leverage these insights to formulate regulations that promote competition, ensure investor protection and facilitate informed investment decisions.

This study advances our understanding of how PMC affects analysts’ earnings forecast attributes. In addition, it pioneers evidence of the moderating role of investor protection in the relationship between PMC and forecast attributes.