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The purpose of this paper is to investigate whether analysts’ optimism affects the stock crash risk.

The sample covers 49,246 firm-year observations for the period between 1995 and 2015. The authors use OLS regressions with firm and year fixed effects for analyses.

The study finds that there is a positive association between analysts’ optimism and stock crash risk. Such a positive impact is more pronounced for firms with opaque information environment and for analysts who are considered ex ante credible.

The results indicate that analysts’ optimism can be an important source of stock crash risk.

The findings can be useful for informational users of analyst reports. Given that information provided by analysts might have negative consequences, the empirical results can be useful in assessing future stock return behaviors.

This paper has the potential to shed light on the large literature of crash risk. Prior studies suggest that crash is driven by the agency tension between shareholders and managers. It remains possible that crashes could be caused by overpriced stocks in the absence of bad news hoarding. The paper investigates crash from a perspective, financial analysts, that is underexplored.

Prior literature has found that as uncertainty in a firms information environment increases, optimism increases in equity analysts’ earnings forecasts. The studies suggest an economic incentive explanation, commonly called the management‐relations hypothesis. However, there is conflicting evidence that managers would prefer pessimistic forecasts and encourage analysts to “walk‐down” their forecasts to prevent negative earnings surprises. To test these contradictory findings, this study uses an experimental setting to remove economic incentives from the analyst’s decision process and isolate the cause of observed bias in analysts’ reports. The results of the experiment show that an increase in the perceived uncertainty of the forecasting task results in significantly lower relative optimism in analysts’ earnings forecasts. This finding is consistent with a negativity hypothesis and the managementrelations hypothesis extolled in the empirical research. The findings also show that relative forecast optimism bias is positively related to the level of analysts’ buy/sell recommendations consistent with more recent findings that suggest that analysts use motivated reasoning (the tendency to process information in a manner that supports one’s goal) in their judgments of forecasted earnings and recommendations. Together, these results suggest that analysts consider and use financial information differently depending on their decision goal.

This paper aims to document the impact of Ramadan on the optimism of analysts’ recommendations taking as a sample the countries of the MENA region during the period between 2004 and 2015. The choice of these countries can be explained by the fact that their population is predominantly of a Muslim faith (The Future of World Religions: Population Growth Projections, 2010-2050, 2015).

The authors used univariate and multivariate regression models to highlight the existence of the Ramadan effect on the optimism of analysts. They have found that pre-holiday optimism is significantly lower than post-holiday optimism.

This paper also documented the effect of analysts’ experience and information uncertainty on the analysts’ optimism level that allowed us to infer that low experience enhances optimism, while environment with low information uncertainty tends to decrease the level of optimism.

Previous research on this topic has investigated the effect of months of the year, turns of the month and days-of-the-week on the behavior of stock exchanges. Another strand of the literature also analyzed the effect of holidays on the latter. However, this is the first attempt to investigate this effect on analysts’ recommendations optimism when the holiday period is related to Islam.

The study examines the effect of increased Economic Policy uncertainty on analyst optimism in the Indian market. The study also explores whether the SEBI Research Analyst Regulation, 2014, has effectively contained the optimistic nature of analysts.

The study is based on firms in the Indian market. The sample period is 2003–2020. It runs a linear panel regression to measure the impact of Economic Policy uncertainty on the optimism level of analysts' forecasts and recommendations, controlling for firm fixed effects. Further, the impact of the SEBI Research Analyst Regulation, 2014, has been assessed with the help of the difference-in-difference approach.

The Economic Policy uncertainty is significantly and positively related to the analyst optimism, reflected in the forecast bias and recommendation in the Indian context. The experience of analysts and the age of the firm positively drive optimism. However, introducing the Research Analyst Regulation by SEBI led to a decline in analyst optimism. The regulation decoupled the analysts' compensation from brokerage service transactions. Thus, the results suggest that the regulation has effectively curbed the incentive to produce optimistic output.

This is the first study in the Indian market to assess the impact of uncertainty on analyst output. It also investigates the effectiveness of the first analyst-specific regulation in India, i.e. The Research Analyst Regulation, 2014.

The aim of this paper is to analyze the impact of corporate governance (focused on some key mechanisms as board size, board independence, managerial ownership, institutional ownership, and chief executive officer duality) on financial analysts’ behavior in US. Results from panel data analysis for 294 US listed firms observed from 2007 to 2014 show that several attributes of the board of directors and audit committee have no effects on the number of analysts who are following the firm and the properties of analysts’ earnings forecasts. Findings also suggest that firms with independent and large boards and blockholders ownership benefit of more analyst following. In addition, it is proven that analysts’ earnings forecasts are optimistic and more accurate for companies where blockholder ownership, either by managers or external entities have larger quoted spreads but of lower quality for the ones which have greater independent board members and institutional investor’s holding.

The purpose of this paper is to examine how family firms affect analyst forecast dispersion, accuracy and optimism and how earnings smoothness as the moderating factor, affects these relationships in an emerging market context.

This paper uses the population sample of firms listed on the Taiwan Stock Exchange from 2009 to 2010 as the research sample, which includes 963 firm-year observations.

The findings show that analysts following family firms are more likely to have more dispersed, less accurate and more optimism biased forecasts than those following nonfamily firms. Earning smoothness is mainly used by nonfamily firms as a signaling strategy to improve analyst forecast quality. In contrast, earnings smoothness is mainly used by families as a garbling strategy, stimulating forecast optimism. Only earnings smoothness in family firms with a high level of family ownership concentration is likely to be signaling-oriented to improve analyst forecast accuracy and mitigate analyst optimism biases.

Emerging markets are not only featured by prevailing principal-principal conflicts but also have multiple levels of agency conflicts among large shareholders, minority shareholders and professionally hired managers. This research reveals the multiple governance roles of family owners in affecting analyst forecast quality, including their entrenchment role in extracting private benefits of control through opaque environments and market discipline distortion role in aligning interests between managers and families without prioritizing meeting or beating analyst forecasts, both at the cost of minority shareholders. This research further disentangles the intertwined signaling oriented and garbiling oriented incentives associated with earnings smoothness under family governance.

The purpose of this paper is to assess whether there is an association between CEO age and analysts forecast properties (particularly forecast accuracy and bias/optimism). CEOs, having the central role in managing firms, can significantly influence the financial and non-financial decisions in an organisation. Furthermore, having been identified as key culprits in past major accounting scandals, it is also important to identify the CEO characteristics that affect financial reporting decisions.

This study adopts the upper echelon theory on the relationship between CEO age and analysts forecast properties. The authors use a sample of 2,730 Australian firm-year observations for the period 2004–2013 drawn from IBES, Connect 4 and SIRCA databases.

The authors find that analyst forecast accuracy increases and bias (optimism) reduces with the CEO age. The authors conclude that earnings and related information provided to analysts improves with the CEO age, which increases the forecast accuracy and reduces bias (optimism). Additional results suggest that the positive (negative) effect of CEO age on forecast accuracy (bias) remains until the CEOs reach the age of their retirement age (65 years). The results remain consistent with a number of sensitivity tests and provide implication for stakeholders such as firms, analysts, auditors, financial statements users and regulators.

The authors demonstrate that the relationship between CEO age and analyst forecast properties is not linear but is, in fact, curvilinear substantiating concerns that CEOs that are much younger or much older do not help increase the quality of the information environment. Consequently, firms hiring CEOs in the right age bracket also benefit by having higher-quality information environment leading possibly to reduce costs such as those relating to debt and/or equity ultimately increasing firm value.

Empirical studies on the association between CEO age and analysts earnings properties in Australia are scarce and this paper contributes to the determinants of the analysts forecast accuracy and bias (optimism) and the CEO age literature.

This article analyzes the hypothesis that analysts issue higher long-term earnings growth (LTG) forecasts following a market-wide investor sentiment.

This study analyzed 193 publicly traded Brazilian firms listed on B3 (Brasil, Bolsa, Balcão), totaling 2,291 observations. To address the potential selection bias resulting from analysts' preference for more liquid firms, this study used the Heckman model in the analysis with samples with only one analyst and the entire sample. The study also applied other robustness tests to ensure the reliability of the findings.

The results suggest that market-wide investor sentiment influences LTG when the firm's stocks are difficult to value. Market optimism did not reflect five-year profit growth after the forecast issue, suggesting lower forecast accuracy during high investor sentiment values.

Volatile-earnings firms have relevant implications in LTG forecasts during bullish moments. According to the study’s evidence, investors' decisions and policymakers' and regulators' rules should consider analysts' expertise as independent information when considering LTG as input for valuation models, even under market optimism.

This paper contributes to the literature on the influence of investor sentiment on analysts' forecasts by incorporating two crucial elements in the discussion: the scenario free from herding behavior, as usually only one analyst issues LGT forecast for Brazilian firms, and the analysis of research hypotheses incorporates the difficulty of pricing a firm given the uncertainty of its earnings as an explanation to bullish forecast.

The purpose of this paper is to revisit the question of whether analysts anticipate accruals’ predicted reversals (or persistence) of future earnings. Prior evidence documents that analysts who provide information to investors are over optimistic about firms with high working capital (WC) accruals. The authors propose that empirical models using WC accruals alone may be incomplete and hence not entirely appropriate to assess the level of analysts’ understanding of accruals. The authors argue that analysts’ optimism about WC accruals might not be due to their lack of sophistication, but rather driven by incomplete accrual information embedded in forecast accuracy tests.

The authors use non-financial US firms for the period between 1976 and 2013. The authors define earnings forecast errors as the analysts’ consensus earnings forecasts minus the actual earnings provided by IBES deflated by share price from CRSP. The authors carry out forecast error regressions on individual accrual components by decomposing total accruals into categories. The authors perform the tests across 12 months starting from the initial analysts’ forecasts, which are generally issued in the first month after the prior period earnings announcement date. The final sample contains 48,142 firm–year observations per month.

The empirical tests show no correlation between analysts’ forecast errors and revised total accruals. The findings are robust to different samples, periods, model specifications, decile ranked accruals, high accruals, absolute forecast errors, controlling for cash flows (CF) and high accounting conservatism. The findings imply that if analysts are to achieve more accurate forecasts, they should be considering all rather than some accrual components. The authors interpret this evidence as an indication of analysts’ relative sophistication with respect to accruals.

The authors recognise that analysts’ correct anticipation of accruals’ persistence does not mean that their earnings forecasts are entirely free of bias. Analysts can make forecast errors for various reasons including strategic biases. For instance, the tests show pessimistic forecast errors with respect to CF, which is in line with similar findings in prior research (Drake and Myers, 2011). Hence, the authors suggest that future research examine this correlation in greater depth as CF components are with the highest level of persistence, and hence should be predicted most accurately.

The results imply that the argument about analysts’ lack of sophistication with respect to accruals’ persistence is not warranted. The results imply that forecasts appear to contribute to market efficiency. Another implication is that analysts seem to utilise all relevant accrual information in their forecasts, hence traditional accrual definition should be revised in future studies. Key inferences of the paper imply that the growing use of analysts’ reports by institutional investors and money managers in their decision-making processes is justified despite the debate in the prior literature on the role and the reputation of analysts as surrogates of market expectations.

The research sheds a new light on the question whether sell-side security analysts are able to anticipate the persistence of accruals in future earnings.

Corporate investment behavior increases the uncertainty of a company’s operation and performance. The purpose of this paper is to investigate how analyst recommendations respond to corporate uncertainty caused by investment behavior and what motivates analysts to react as they do.

The authors test two motivation hypotheses: the hypothesis that analysts are currying favor with management to obtain private information and the hypothesis that analysts have conflicts of interest due to connections. Using Chinese analyst-level data from 2007 to 2015, the authors find that overall investment levels, R&D investment and M&A events are significantly positively correlated with analyst recommendations, suggesting that analysts tend to react optimistically to corporate investment behavior.

Analysts are only optimistic about companies with low information transparency, suggesting that analysts may be trying to curry favor with management to gain access to private information. The authors find that analysts with stronger recommendations have more private information and analysts with more private information publish more accurate earnings forecasts, which supports the hypothesis that analysts curry favor with management through optimistic recommendations to obtain more private information. This is consistent with the logic that the difficulty of earnings forecasting increases under uncertain conditions, increasing the demand for private information. The authors then group the analysts according to their underwriting connections, securities company’s proprietary connections and fund connections, and find that the positive correlation between corporate investment behavior and analyst recommendations exists only in the unconnected groups. This is evidence against the hypothesis that analysts have conflicts of interest due to their connections.

First, the authors link the optimism of analysts with the uncertainty of analysts’ information inputs to partially unpack the black box of analysts’ analyses. Second, the authors test the two hypotheses mentioned. There is a lack of comparative studies on the influence of different motivations on the behavior of analysts.