This paper examines the effect of the All‐Star award on the performance of Chinese financial analysts. Leveraging unique voting data from 2007 to 2016 and a regression discontinuity design (RDD), we find that the All‐Star award significantly enhances recipients' fundamental analysis. Awarded analysts issue more accurate earnings forecasts, and their stock recommendations convey greater information content for firms with higher information asymmetry. RDD results also indicate that award recipients gain increased resources and greater flexibility in reallocating time and effort. Post award, analysts concentrate on fewer industries, cover more firms within each industry, issue forecasts more frequently, expand their teams, and conduct more site visits. Surveys of analysts and institutional investors corroborate these findings, highlighting increases in site visits and roadshows following the award. Overall, the results suggest that the All‐Star award boosts analyst performance by fostering more concentrated coverage and improving access to both internal and external resources.

The many management guidance withdrawals during the COVID-19 pandemic have attracted considerable attention from the media, investors, and regulators. This study analyzes the determinants and consequences of these withdrawals. We find that guidance withdrawals are due to economic uncertainty, resulting from firms’ exposure to the COVID-19 pandemic rather than poor financial performance. Also, the effect of COVID-19 exposure on guidance withdrawals is stronger when firms face higher litigation risk. Further, guidance withdrawals result in abnormally large trading volumes and high analyst forecast dispersion but do not harm stock prices or the level of analyst earnings forecasts. Overall we believe the findings have implications for understanding corporate disclosure practices during periods with heightened economic uncertainty.

Social skills are important but difficult to measure. So far, few empirical studies have examined the effect of social skills on the performance of professionals. Using the number of LinkedIn connections as a proxy for social skills, we investigate the effect of financial analysts' social skills on their performance. We use multiple ways to validate the measure of social skills and show that analysts with better social skills produce more accurate earnings forecasts and that their stock recommendations elicit stronger market reactions. Furthermore, these socially skilled analysts are more likely to be voted as All‐Star Analysts. This study provides the first large‐sample evidence highlighting the importance of social skills on financial analysts' performance.

This paper examines whether the negative association between aggregate earnings and returns is explained by the monetary policy news in aggregate earnings. Using Federal funds futures data to construct a measure of policy news, we find that aggregate earnings convey information about the Fed׳s policy actions. Additionally, the negative aggregate earnings-returns association is muted when we control for policy surprises. This result is more pronounced in periods with negative policy surprises, which tend to trigger a more significant market reaction. Taken together, these results suggest that aggregate earnings convey policy news and the market reacts negatively to policy surprises, which drives the negative aggregate earnings-returns association.

We examine how gender and beauty affect the likelihood of being voted as an All-Star in the financial analyst profession in both the United States and China. We find that female analysts are more likely to be voted as All-Star analysts in the United States, but good-looking female U.S. analysts are less likely to be voted as All-Stars. The conclusion is the opposite for Chinese analysts. We find that female analysts in China are less likely to be voted as All-Stars, but the likelihood increases with their facial attractiveness. These findings implicate a beauty penalty for female analysts in the United States and gender discrimination against female analysts in China. This career path evidence from a competitive financial industry suggests that gender and beauty biases may be rooted deeply in culture and the legal environment and should not be treated homogenously.

We examine the macroeconomic information content of aggregate earnings from the labor market's perspective. We use insights from the labor economics literature to characterize the information contained in aggregate GAAP earnings and its components that is relevant for predicting aggregate job creation and destruction. Our results suggest that not only does aggregate earnings news convey information about future labor market aggregates, but its information content is incremental to other macroeconomic variables at near-term horizons. Further, the source of this information stems primarily from two earnings components: aggregate core earnings and special items. Shocks to core earnings signal persistent changes in economy-wide profitability that predict aggregate job creation up to four quarters ahead, while shocks to special items predict job destruction up to one quarter. Taken together, our results suggest that aggregate earnings contain useful information about future labor market conditions, with the nature of such information varying across earnings components.

We examine whether corporate financing activities (CFA) in aggregate convey information about the macroeconomy. Using statement of cash flow information to construct a bottom-up measure of CFA, we find that it has significant predictive power for future economic activity when we exclude a small set of firms whose external financing is largely insulated from macroeconomic conditions. This CFA index has predictive power beyond that of the Gilchrist-Zakrajsek credit spread, aggregate earnings, and other macroeconomic indicators in predicting future GDP in both in-sample and out-of-sample forecasting tests. Impulse responses from a structural vector autoregression show that unexpected decreases in this CFA index lead to a large and persistent contraction in economic activity for up to four quarters. Our results suggest that a simple portfolio-based CFA measure helps capture supply-of-capital effects from the financial accelerator mechanism and hence has significant incremental predictive power for real economic activity. Data Availability: Data are available from the public sources cited in the text.