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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.

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.

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 investigate the impact of the introduction of New Zealand's statutory‐backed continuous disclosure regime enacted in December 2002 on the differential disclosure behaviour of New Zealand firms with good and bad earnings news.

This paper examines the level of information disclosure, analyst forecast error and forecast dispersion, abnormal returns and abnormal volumes for firms with good and bad news earnings announcements in a sample period surrounding reforms to New Zealand's continuous disclosure regime.

The authors find evidence that the pre‐announcement information flow was poorer prior to the reform for bad news firms compared to good news firms, in terms of greater analysts' forecast dispersion and a larger abnormal price reaction to the actual earnings announcement. Second, the reform reduced the asymmetry of information flow between good and bad news firms, with the differences in analysts' forecast dispersion and abnormal price reaction dissipating after the reform.

The findings suggest that the reforms to New Zealand's continuous disclosure regime have reduced managers' propensity to withhold bad news and improved the quality of information provided to investors by firms with bad earnings news.

This study improves our understanding of the impact of disclosure reform on the behaviour of managers in a market with relatively low liquidity and less litigation risk in comparison to larger and more developed markets.

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 examined the effect of different types of politically connected (PCON) Malaysian firms on analysts' forecast accuracy and dispersion.

The study identified different types of PCON firms according to Wong and Hooy's (2018) classification, which divided political connections into government-linked companies (GLCs), boards of directors, business owners and family members of government leaders. The sample covered the period 2007–2016, for which earnings forecast data were obtained from the Institutional Brokers' Estimate System (IBES) database and financial data were extracted from Thomson Reuters Fundamentals. We deleted any market consensus estimates made by less than three analysts and/or firms with less than three years of analyst forecast information to control for the impact of individual analysts' personal attributes.

The study found that PCON firms were associated with lower analyst forecast accuracy and higher forecast dispersion. The effect was more salient in GLCs than in other PCON firms, either through families, business ties or boards of directors. Further analyses showed that PCON firms—in particular GLCs—were associated with more aggressive reporting of earnings and poorer quality of accruals, hence providing inadequate information for analysts to produce accurate and less dispersed earnings forecasts. The results were robust even after addressing endogeneity issues.

This study found new evidence of the impact of different types of PCON firms in exacerbating information asymmetry, which was not addressed in prior studies.

This study has a significant practical implication for investors that they should be mindful of high information asymmetry in politically connected firms, particularly government-linked companies.

This is the first study to provide evidence of the impact of different types of PCON firms on analysts' earnings forecasts.

The purpose of this paper is to report on research concerning financial analysts’ activity surrounding profit warnings issued by listed companies in the four largest European stock exchanges (France, Germany, the Netherlands and the UK). The authors address three aspects of analysts’ forecasts: ex-post accuracy of forecasts, earnings forecast revisions, and consensus forecast dispersion. The goal of the analysis is to study the differences between financial analysts’ behavior within different regulatory settings, namely common law vs civil law countries.

The sample is composed of 1,330 profit warnings issued by listed European firms during the period 2000-2010. The authors apply event study methodology and OLS regressions to highlight the impact of the legal information environment on analysts’ reactions.

The empirical analysis reveals that analyst activity depends on each country’s legal context factors, such as the legal information environment of the firm and the index of investor protection. Accordingly, the authors show that both a richer legal information environment and stronger country-level investor protection substantially improve analyst accuracy around profit warnings.

The sample is only composed on firms from four European countries owing to a lack of firms from other European countries that disclosed PW during the period 2000-2010. It would be pertinent to conduct future research dealing with an international sample from different continents.

The paper contributes to a deeper understanding of analysts’ reactions to profit warnings. The findings can influence firms’ reporting practices and lead to future regulation policies.

This work is the first to examine the relationship between profit warning releases and the behavior of financial analysts in a pan-European context where there are different institutional levels of investor protection.

The purpose of this paper is to investigate the relationship between voluntary disclosure of intangibles and financial analysts’ earnings forecasts properties.

Disclosures about intangible assets were hand-collected through content analysis of annual reports of a sample of US non-financial firms, while analysts’ earnings forecasts properties were collected from Bloomberg Professional database. The authors relied on correlation and multivariate regression analyses to test the research hypotheses.

The results show that increased intangible disclosures affect analysts’ earnings forecasts accuracy, dispersion, and favourable consensus recommendations. However, this effect varies according to the nature of intangible assets.

The results may be of interest to different market participants such as corporate managers, financial analysts, and standards setting bodies that recently published guidelines on voluntary disclosure of intangibles.

This study develops a new comprehensive index to measure the content of narrative disclosures about a large number of intangibles, such as human, structural, and relational assets. The findings contribute to the current debate on the value-relevance of narrative disclosures on intangibles to investors and financial analysts.