C ontrary to the common view that analysts are important information agents, intraday returns evidence shows that announcements of analysts' forecast revisions release little new information, on average. Further cross-sectional evidence from returns around the announcements confirms that revisions are virtually information free. Daily announcement returns used in the literature appear to overstate the analyst's role as information agent, because forecast announcements are often issued directly after reports of significant news about the followed firm. The evidence reveals a sequential relationship between events and news and forecast revisions indicative of analyst piggybacking, not prophecy. These new findings about the most sought-after analyst reports broaden significantly the evidence indicating that price reactions to analysts' reports reveal little new information.

The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb–Benford law (NBL) to gauge data accuracy. We run an OLS regression of an index constructed from developmental indicators (democracy level, gross domestic product per capita, healthcare expenditures, and universal healthcare coverage) on goodness-of-fit measures to the NBL. We find that countries with higher values of the developmental index are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests and for a sub-sample of countries with regional data. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.

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In this article I investigate the association between analysts’ ability to issue influential recommendations and their career outcomes. The fraction of recommendations that are defined as influential are linked to a higher probability of an analyst moving to a higher status brokerage house, and a lower probability of either being demoted to a lower status brokerage house or leaving the profession. Analysts who more often issue influential recommendations also have a higher chance of being ranked by Institutional Investor All‐America, having longer careers, and experiencing lower job turnover compared to peers.