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This study aims to examine the mediating role played by corporate governance (CG) in the relationship between corporate social responsibility (CSR) and analyst forecast quality.

The authors raise three specific questions: Does CG play a mediating role in the relationship between CSR and analyst forecast quality? If so, is such mediation effect of CG reduced for firms with weak governance? Do firms with superior CSR performance experience higher analyst forecast quality through the mediation effect of CG?

The present results suggest that CG serves as a partial mediator that facilitates CSR’s positive influence on analyst forecast quality. However, further analyses show that in firms with a low governance score, CG does not have a mediation effect. Conversely, the authors find that firms with superior CSR performance have higher forecast quality through the mediation effect of CG. The authors also find that the mediation effect of CG is more pronounced for the environmental component than for the social component of CSR.

To the best of the authors’ knowledge, this study is the first to investigate the role of CG as a mediator between CSR and analyst forecast quality and to reveal that the strength of this effect varies depending on firms’ CG level and CSR commitment.

It has been widely documented that investors and analysts underreact to information in past earnings changes, a fundamental performance indicator. The purpose of this paper is to examine whether managers’ voluntary disclosure efficiently incorporates information in past earnings changes, whether analysts recognize and fully anticipate the potential inefficiency in management forecasts and whether managers’ potential forecasting inefficiency entirely results from intentional disclosure strategies or at least partly reflects managers’ unintentional information processing biases.

Archival data were used to empirically test the relation between management earnings forecast errors and past earnings changes.

Results show that managers underreact to past earnings changes when projecting future earnings and analysts recognize, but fail to fully anticipate, the predictable bias associated with past earnings changes in management forecasts. Moreover, analysts appear to underreact more to past earnings changes when management forecasts exhibit greater underestimation of earnings change persistence. Further analyses suggest that the underestimation of earnings change persistence is at least partly attributable to managers’ unintentional information processing bias.

This study contributes to the voluntary disclosure literature by demonstrating the limitation in the informational value of management forecasts. The findings indicate that the effectiveness of voluntary disclosure in mitigating market mispricing is inherently limited by the inefficiency in management forecasts. This study can help market participants to better use management forecasts to form more accurate earnings expectations. Moreover, our evidence suggests a managerial information processing bias with respect to past earnings changes, which may affect managers' operational, investment or financing decisions.

The purpose of this paper is to examine whether financial analysts are sensitive to voluntary earning disclosures.

The paper is based on a literature review of the relationship between analysts' behaviour and corporate disclosures. It is assumed first that analyst coverage both influences and is influenced by voluntary earning disclosures, and that second, French managers are expected to make voluntary disclosures in order to reduce market uncertainty. To test these hypotheses, a simultaneous equation model and an ordinary least square regression framework were estimated on a sample of 154 French‐listed firms between 1998 and 2001.

The results show that voluntary earning disclosures positively influence analyst coverage decision. They also show that voluntary disclosures improve the accuracy of analyst forecasts and reduce market uncertainty.

The paper does not cover all forms of corporate voluntary disclosures.

The findings suggest that corporate disclosure policy is likely to change financial analysts' behaviour. The results are useful to both managers, wishing to meet market expectations and, to investors wishing to invest in richer informational environment firms.

This paper provides original results about the role of analysts in France as information intermediaries. These analysts pay little attention to French firms with a poor information environment in which minority shareholders are less inclined to ask for costly analyst coverage.

Whisper numbers have captured the attention of both the investment community and the financial media. They have heightened the drama of companies’ earnings releases and have been played up as explanations for stock prices’ reactions to actual earnings announcement. I examine the accuracy, the predictive performance and the informational value of these whispers. Gathering my sample from an on‐line source of whisper information, I compare the whispers performance to that of traditional investment analyst forecasts. I find that whispers, while unbiased, are not more accurate than the analysts’ consensus. There is mixed evidence that the market partially reflects the whispers information into price. In fact, I find that a strategy of shorting stocks for which whispers forecasts predict that stocks will outperform is profitable. In summary, whispers are not as accurate as generally portrayed. They are only a fair predictor of stock prices’ movement and do not represent the market’s true earnings expectations.

This paper attempts to shed light on the issue whether investors' earnings expectations completely align with analysts' forecasts. I find that current price level is not significantly correlated with one‐year‐out realized earnings, but, it is significantly correlated with two‐year‐out, three‐year‐out, four‐year‐out and five‐year‐out realized earnings after I control for analysts' forecasts (and current earnings). Current price is found to be useful in improving the accuracy of long‐term analyst consensus forecasts. My findings are consistent with the notion that the market's near term expectation closely follows analyst forecasts while the market's long‐term expectation contains more information than analyst consensus forecasts.

The purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.

By inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.

Using novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.

Taken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

Both the SEC (Securities and Exchange Commission) and the popular press have routinely criticized firms for the complexity of their financial disclosures. This study aims to investigate how financial analysts respond to the tone complexity of firm disclosures.

Using approximately 20,000 earnings conference call transcripts of S&P 1,500 firms between 2005 and 2015, the authors first calculate the abnormal negative tone, the measure of tone complexity; then use such tone measure in econometric models to examine analyst forecast behavior. The authors also test the robustness of the results under different model specifications, tone word lists and alternative tone measure calculations.

Consistent with the notion that analysts respond to the information demand from investors and incur more costs and effort to analyze firm disclosure when the tone is more complex, the authors find that higher tone complexity is positively and significantly associated with more analyst following, longer report duration, more forecast revisions, larger forecast error and larger forecast dispersion. In addition, the authors find that tone complexity has a long-term impact on analyst following but has a limited long-term impact on analyst report duration, analyst revision, forecast error and dispersion.

This study complements existing literature by highlighting the information role of financial analysts and by providing evidence that analysts incorporate the management tone disclosed during conference calls to adjust their forecasting behaviors. The results can be used by policymakers as evidence and support for further improving firm communication from a new dimension of disclosure tone.

This study examines the role of intellectual capital disclosure (ICD) on earnings forecasting by analysts in the pharmaceutical industry in emerging countries, particularly in Indonesia, Malaysia and Thailand. This study specifically examines the role of each component of the ICD on analysts' forecasts, which consists of errors of forecasted earnings, the standard deviation of forecasted earnings and analyst recommendations.

Panel data analysis is conducted using a sample of 17 companies from pharmaceuticals industries in Indonesia, Malaysia, Thailand – Growth Triangle (IMT-GT), which are listed in the Indonesia Stock Exchange (IDX), Malaysia Stock Exchange (MYX) and Stock Exchange of Thailand (SET) from 2010 to 2017. Secondary data is obtained from Bloomberg and Annual report, where they are being analyzed to measure the ICD and gather the control variables.

The results indicate that the three components of ICD, namely human capital disclosure (HCD), structural capital disclosure (SCD) and relational capital disclosure (RCD), insignificantly influence average analysts' consensus recommendation and analysts' earnings forecast dispersion. However, the findings show a significant negative influence of relational capital disclosure (RCD) on analysts' earnings forecast error. In contrast, HCD and SCD have an insignificant impact.

Transparency in disclosing activities related to external parties is essential for the pharmaceutical industry. It is found that relational capital disclosure is the only ICD indicator that can strengthen analysts' profit predictions. Transparency about company activities in maintaining customer satisfaction and activities related to strategic alliances with other organizations are two critical things that can accommodate the accuracy of earnings forecasting from analysts in pharmaceutical companies.

This study contributes to ICD-related research by discussing the financial analyst's response to this voluntary disclosure in the pharmaceutical industry, particularly in Indonesia, Malaysia and Thailand. The selected observation period is seven years, starting one year after the global financial crisis. The results showed that the disclosure of IC is not an exciting thing for financial analysts. In forecasting current earnings, financial analysts are more interested in errors than the previous year's estimates.

The purpose of this paper is to detect quantitatively the existence of anchoring bias among financial analysts on the Tunisian stock market. Both non-parametric and parametric methods are used.

Two studies have been conducted over the period 2010–2014. A first analysis is non-parametric, based on observations of the sign taking by the surprise of result announcement according to the evolution of earning per share (EPS). A second analysis uses simple and multiple linear regression methods to quantify the anchor bias.

Non-parametric results show that in the majority of cases, the earning per share variations are followed by unexpected earnings surprises of the same direction, which verify the hypothesis of an anchoring bias of financial analysts to the past benefits. Parametric results confirm these first findings by testing different psychological anchors’ variables. Financial analysts are found to remain anchored to the previous benefits and carry out insufficient adjustments following the announcement of the results by the companies. There is also a tendency for an over/under-reaction in changes in forecasts. Analysts’ behavior is asymmetrical depending on the sign of the forecast changes: an over-reaction for positive prediction changes and a negative reaction for negative prediction changes.

The evidence provided in this paper largely validates the assumptions derived from the behavioral theory particularly the lessons learned by Kaestner (2005) and Amir and Ganzach (1998). The authors conclude that financial analysts on the Tunisian stock market suffer from anchoring, optimism, over and under-reaction biases when announcing the earnings.

Are some analysts ‘superstars’? Financial press coverage of analysts' performance suggests that there are superior financial analysts. One example of this coverage is the Institutional Investor ‘All American Research Team’, based on surveys of money managers, who nominate and rank analysts. In this paper, I explore the question of individual superiority by examining one aspect of analysts' services: earnings forecasting. Forecasts of future earnings are of interest to investors, as inputs to investment decisions, and also to researchers, as data on earnings expectations.