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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.

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 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.

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.

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 authors examine how financial analysts respond to online investor sentiment when updating recommendations for specific stocks in South Africa. The aim is to establish whether online sentiment contains significant information that can influence analyst recommendations. The authors follow up the above by examining when online investor sentiment is most associated with analyst recommendation changes.

For online investor sentiment proxies, the authors make use of the social media sentiment and news media sentiment scores provided by Bloomberg Inc. The sample size includes all companies listed on the Johannesburg Stock Exchange All Share Index. The study uses traditional ordinary least squares to examine the relation at the mean and quantile regression to identify the scope of the relationship across the distribution of the dependent variable.

The authors find evidence that pre-event news sentiment significantly influences analyst recommendation changes while no significant relationship is found with the Twitter sentiment. Further analysis shows that news sentiment is more influential when the recommendation changes are moderate (in the middle of the conditional distribution of the recommendation changes).

The study is the one of the first to examine the association between online sentiment and analyst recommendation changes in an emerging market using high frequency data. The authors also make a direct comparison between social media sentiment and news media sentiment, some of the most used contemporary investor sentiment proxies.

This paper documents the effect of different types of information on the value of financial analysts.

The authors use the pooled OLS regression and the data of nonfinancial firms from France to test our hypotheses. The data covers the period between 1997 and 2019.

The results show that analysts are more likely to cover those firms that incorporated greater proportion of market-wide information in their prices. Consistent with the economies of scale view, the authors argue that analysts specialize in the interpretation market-wide information. By doing so, they are able to cover relatively large number of firms simultaneously. The results also show that the value of analyst coverage (measured as the impact of analyst coverage on firm value, probability of stock price crash and probability of stock price jump) is a function of the extent to which different types of information are incorporated in prices. The authors’ results suggest that the impact of analyst coverage on firm value and on probability of crash is less pronounced in firms that incorporate greater proportion of market-wide information. In case of probability of jump, the results show that the impact of analyst coverage is more pronounced firms that incorporate greater proportion of market-wide information.

The major contribution of this paper is to document the impact of different types of information on the extent of analyst coverage. Furthermore, this paper also uses various measures (the impact of analyst coverage on firm value, probability of stock price crash and probability of stock price jump) to show how different types of information affects the value of analyst coverage.

A number of U.S. studies have documented an optimistic bias in analysts’ forecasts of earnings. This study investigates whether the optimistic bias and asymmetric behavior of forecast errors found in most U.S. studies exists in Japan. We find that for firms reporting profits, Japanese analysts’ forecasts have much greater accuracy and exhibit a small pessimistic bias in comparison to firms reporting losses, where analysts’ forecasts exhibit extremely poor accuracy and an extremely significant optimistic bias. The lack of ability to forecast losses is due to their transitory nature and not due to earnings management. Forecast accuracy and bias are not related to firm size, but are related to the magnitude of reported lossess and profits.

The purpose of this paper is to investigate whether there is any difference across individual investors, domestic and foreign institutional investors in trading volume responses to analyst reports. The authors also examine the determinants of trading volume responses using firm as well as forecast characteristics.

The authors use trading data from the Korean equity market. The authors divide investors into three classes of investors; namely, individual investors, domestic institutional investors, and foreign institutional investors. The authors then examine whether the trading responses to analyst reports vary across investor types, and how firm characteristics and characteristics of analyst reports influence the trading activities on the release dates across investor types.

Individual investors are the most responsive investor group, being responsive to analyst reports on small, neglected firms with large inside ownership as well as to analyst reports with optimistic forecasts. Domestic institutional investors are responsive to reports on neglected firms with high return volatility while foreign institutional investors show least responses.

There are few studies that investigate whether the trading responses to analyst reports vary across investor types and how firm characteristics and characteristics of analyst reports influence the trading activities on the release dates across investor types. Taking advantage of the trading volume data for the three main investor types in the Korean stock market, the authors study the trading volume responses for each investor type and make comparisons across investor types.

The purpose of this study is to examine the effect of insider trading on analyst coverage and the properties of analyst earnings forecasts. Given the central role of analysts for information diffusion in stock markets, advancing understanding of the role insider trades may play in analyst coverage and forecasts, especially in the context of a changing legal environment (e.g. the implementation of Regulation Fair Disclosure [Reg FD]), should be a worthy goal.

To address the research questions, the authors run regressions in which the authors identify and control for as many possible determinants of analyst coverage and forecasts (e.g. firm size, information asymmetry and earnings performance) that are correlated with insider trades. To alleviate endogeneity concerns, the authors use three approaches. First, the authors extend the sample period to the post-Reg-FD period in which managers are not allowed to provide private information to financial analysts. Second, the authors measure analyst coverage in a window that is lagged by insider trades. Third, the authors employ firm-fixed-effects regressions in all the multivariate tests. Finally, following Larcker and Rusticus (2010), the authors conduct the impact threshold for a confounding variable test to assure that all regression analyses are indeed immune to the potential correlated-omitted-variable bias.

The authors find that the level of analyst coverage is positively related to the intensity of insider trades and that analyst coverage is more strongly associated with insider purchases than with insider sales. The authors also find that the positive association between analyst coverage and insider trades is less pronounced after the passage of Reg FD. Further investigations reveal that analysts revise their earnings forecasts upward following insider purchases, the informativeness of analyst forecast revisions significantly increases following insider purchases and optimistic bias in analyst forecast revisions is reduced as a result of insider purchases; the authors do not find similar evidence for insider sales.

A large body of insider trading literature (Johnson et al., 2009; Badertscher et al., 2011; Thevenot 2012; Skaife et al., 2013; Billings and Cedergren 2015; Dechow et al., 2016) provides evidence that insiders actively trade on their private information, such as their foreknowledge of price-relevant corporate events. This literature suggests that insider trades are potentially value-relevant and are informative about a firm’s future prospects. However, less research attention has been paid to investigating how insider trades might affect market participants’ (especially sophisticated participants’) behavior. This study contributes to understanding the role that insider trading may play in shaping analyst behavior.

Prior research (Frankel and Li, 2004; Lustgarten and Mande, 1995; Carpenter and Remmers, 2001; Seyhun, 1990) maintains that insider sales are less informative about a firm’s future prospects than are insider purchases because insider sales might take place for the liquidity and diversification purposes. By probing the stock price responses to insider selling activities, Lakonishok and Lee (2001), Jeng et al. (2003) and Fidrmuc et al. (2006) infer that insider selling is not informative about future firm performance. However, for such an inference, the authors cannot rule out the possibility that insider sales do convey value-relevant information, but the stock market does not react correctly to such trading information (Beneish and Vargus, 2002). Because the authors focus on examining analysts’ responses to insider sales, and analysts are supposed to be sophisticated in information processing, this study adds more compelling evidence for the notion that insider sales convey less information about a firm’s future prospects than do insider purchases.

There is an ongoing debate about the benefits and drawbacks of insider trading. Opponents of insider trading view insider trades as inequitable and immoral and assert that restricting insider trades curbs resource misallocation and benefits the whole society. Proponents contend that insider trading accelerates the price discovery process, increases market efficiency (Leland, 1992; Bernhardt et al., 1995; Choi et al., 2016) and may even play a role in rewarding and motivating executives (Roulstone, 2003; Denis and Xu, 2013). The authors add to this debate by documenting that insider trading increases the amount of information valuable to analyst research activities and helps enhance analyst services.

To the best of the authors’ knowledge, this study is the first to offer firm-level evidence of a positive association between insider trades and analyst coverage. By accounting for the post-Reg-FD regime, this paper is also the first to provide evidence on how analysts, in the absence of access to management’s private information because of the regime change by Reg FD, react to insider trades.