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We explore the impact of corporate social responsibility (CSR) ratings on sell-side analysts' assessments of firms' future financial performance. We suggest that when analysts perceive CSR as an agency cost they produce pessimistic recommendations for firms with high CSR ratings. Moreover, we theorize that, over time, the emergence of a stakeholder focus shifts the analysts' perceptions of CSR. Using a large sample of publicly traded U.S. firms over 15 years, we confirm that, in the early 1990s, analysts issue more pessimistic recommendations for firms with high CSR ratings. However, analysts progressively assess these firms more optimistically over time. Furthermore, we find that analysts of highest status are the first to shift the relation between CSR ratings and investment recommendation optimism.

Our objective is to penetrate the \"black box\" of sell-side financial analysts by providing new insights into the inputs analysts use and the incentives they face. We survey 365 analysts and conduct 18 follow-up interviews covering a wide range of topics, including the inputs to analysts' earnings forecasts and stock recommendations, the value of their industry knowledge, the determinants of their compensation, the career benefits of Institutional Investor All-Star status, and the factors they consider indicative of high-quality earnings. One important finding is that private communication with management is a more useful input to analysts' earnings forecasts and stock recommendations than their own primary research, recent earnings performance, and recent 10-K and 10-Q reports. Another notable finding is that issuing earnings forecasts and stock recommendations that are well below the consensus often leads to an increase in analysts' credibility with their investing clients. We conduct cross-sectional analyses that highlight the impact of analyst and brokerage characteristics on analysts' inputs and incentives. Our findings are relevant to investors, managers, analysts, and academic researchers.

Companies' earnings conference calls are perceived to be venues for sell-side equity analysts to ask management questions. In this study, we examine another important conference call participant—the buy-side analyst—that has been underexplored in the literature due to data limitations. Using a large sample of transcripts, we identify 3,834 buy-side analysts from 701 institutional investment firms who participated (i.e., asked a question) in 13,332 conference calls to examine the determinants and implications of their participation. Buy-side analysts are more likely to participate when sell-side analyst coverage is low and dispersion in sell-side earnings forecasts is high, consistent with buy-side analysts participating when a company's information environment is poor. Institutional investors trade more of a company's stock in the quarters in which their buy-side analysts participate in the call. Finally, we find evidence that buy-side analyst participation is associated with company-level absolute changes in future stock price, trading volume, institutional ownership, and short interest.

We identify analysts’ information acquisition patterns by linking EDGAR (Electronic Data Gathering, Analysis, and Retrieval) server activity to analysts’ brokerage houses. Analysts rely on EDGAR in 24% of their estimate updates with an average of eight filings viewed. We document that analysts’ attention to public information is driven by the demand for information and the analysts’ incentives and career concerns. We find that information acquisition via EDGAR is associated with a significant reduction in analysts’ forecasting error relative to their peers. This relationship is likewise present when we focus on the intensity of analyst research. Attention to public information further enables analysts to provide forecasts for more time periods and more financial metrics. Informed recommendation updates are associated with substantial and persistent abnormal returns, even when the analyst accesses historical filings. Analysts’ use of EDGAR is associated with longer and more informative analysis within recommendation reports. This paper was accepted by Shiva Rajgopal, accounting.

Purpose: This study examines the role of analysts as information intermediaries in detecting misreporting at the time it occurs, focusing on income-increasing misreporting cases identified by the Securities and Exchange Commission (SEC). Design/methodology/approach: Using a propensity-score matched sample and various econometric approaches, we analyze dynamic changes in analysts' earnings forecast bias for misreporting firms relative to non-misreporting counterfactuals with similar ex ante misreporting probabilities, particularly around the first year of misreporting. Findings: Our results indicate that analysts issue more conservative (i.e., less optimistic) earnings forecasts for misreporting firms than for non-misreporting counterfactuals. This suggests that analysts can discern manipulated earnings, supporting the rational forecasting view. Research limitations/implications: Despite our attempt to address potential endogeneity between corporate misreporting and analysts' earnings forecasts, causal inference remains subject to assumptions inherent in our econometric approaches. Nevertheless, the consistency and robustness of our findings across various methods reinforce the credibility of our conclusions. Our results suggest that analysts can identify misreporting early and issue preemptive warnings. Originality/value: This study provides novel evidence that analysts can discern overstated earnings at the time of misreporting. Its findings deepen our understanding of analysts' role as information intermediaries in financial markets.

This paper examines the impact of teamwork on sell-side analysts’ performance. Using a hand-collected sample of over 50,000 analyst research reports, we find that analyst teams issue more than 70% of annual earnings forecasts. In contrast, most research implicitly assumes that forecasts are issued by individual analysts. We document that analyst teams generate more accurate earnings forecasts than individual analysts and that the stock market reacts more strongly to forecast revisions issued by teams. Analyst teams also cover more firms, issue earnings forecasts more frequently, and issue less stale forecasts. Analysts working in teams are more likely to be voted as All-Star analysts in the future. Among analyst teams, we show that team size and team member ability are significantly associated with forecast accuracy. Moreover, using detailed analyst background information from LinkedIn, we find that forecast accuracy is positively associated with team diversity based on sell-side experience, educational background, and gender. Additional analyses suggest that analyst teams, especially more diverse ones, are more likely to issue cash-flow forecasts and use discounted cash-flow valuation models in their reports. These findings suggest that teamwork and team diversity play a crucial role in understanding sell-side analysts’ performance.

This paper provides early but broad empirical evidence on MiFID II, which requires investment firms to unbundle investment research from other costs they charge to clients. Employing difference-in-differences matched-sample research designs with firm fixed effects, we find a decrease in the number of sell-side analysts covering European firms after MiFID II implementation, particularly for firms that are less important to the sell-side. However, research quality improves; specifically, individual analyst forecasts are more accurate and stock recommendations garner greater market reactions. In addition, sell-side analysts seem to cater more to the buy-side after MiFID II by providing industry recommendations along with stock recommendations. Importantly, we predict and find evidence that buy-side investment firms turn to more in-house research after MiFID II implementation. Equally interesting, buy-side analysts increase their participation and engagement in earnings conference calls, compared to the control group. We find some evidence that stock-market liquidity decreases post MiFID II.

We examine how research posted by “social media analysts” (SMAs)—individuals posting equity research online via social media investment platforms—is related to research subsequently produced by professional sell-side equity analysts. Using data from Seeking Alpha, we find that the market reaction to sell-side analyst research is substantially reduced when the analyst research is preceded by the report of an SMA, and that this is particularly true of sell-side analysts’ earnings forecasts. We further find that this effect is more pronounced when SMA reports contain more decision-useful language, are produced by SMAs with greater expertise, and relate to firms with greater retail investor ownership. We also provide evidence that the attenuated response to sell-side research is most likely explained by SMA research preempting information in sell-side research and that analysts respond to SMA preemption with bolder and more disaggregated forecasts. Collectively, our results suggest that equity research posted online by SMAs provides investors with information that is similar to but arrives earlier than sell-side equity research, and speak to the connected and evolving roles of information intermediaries in capital markets.

Taking advantage of a recently established dataset that records financial analysts’ firm visits, this study examines the factors that determine the number of buy-side and sell-side analyst firm visits in a given year and how investors respond to these visits. Both buy-side and sell-side analysts seem motivated to visit firms when they are considering buying or recommending that investors buy shares rather than when they are considering selling or when they are recommending that investors sell shares. However, there are still significant differences in the firms that buy-side and sell-side analysts choose to visit. Using a binomial count model, this study shows that buy-side analyst firm visits are heavily focused on industry leaders—firms with a high share of the total revenue in their given industry—while sell-side analyst firm visits are not. By looking at the response of investors to buy-side or sell-side analyst firm visits, a regression analysis uncovers evidence that investors trust buy-side analysts, responding to firm visits by buy-side analysts by purchasing more shares in the firm. Investors do not have the same level of confidence in sell-side analysts. Investors respond to firm visits by sell-side analysts by selling more shares in the firm. This phenomenon is even more significant for firms that are outperforming the market. The results suggest that there is a significant cost to the conflict of interest inherent in sell-side analysts’ research. These costs increase when analysts recommend outperforming firms to the public.

Although macroeconomic news has a major impact on corporate earnings, anecdotal evidence suggests that financial analyst research is inefficient with respect to such news. Examining analysts' earnings research, we find that they underreact to negative macroeconomic news. Analysts are not all equal, though, as analysts employed at the same firm as an active macroeconomist underreact much less. We find that the benefit of analyst access to an economist is concentrated in firms that are high in cyclically relative to their industry, high in cyclically in general, and that are smaller in size. In addition, analysts who are exposed to more accurate or awardwinning in-house macroeconomists benefit more. Investors appear to recognize the advantage of access to macroeconomists, reacting more strongly to these analysts' forecast revisions. Overall, our results suggest that the presence of an active in-house macroeconomist improves the efficiency and credibility of analyst research.