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 study provides large-scale descriptive evidence on the timing and nature of corporate financial tweeting. Using an unsupervised machine learning approach to analyze 24 million tweets posted by S&P 1500 firms from 2012 to 2020, we find that firms are more likely to tweet financial information around significantly negative or positive news events, such as earnings announcements and the filing of financial statements. This convex U-shaped relation between the likelihood of posting financial tweets and the materiality of accounting events becomes stronger over time. Whereas research based on early samples concludes that firms are less likely to disseminate financial information on Twitter when the news is bad and material, the symmetric dissemination behavior we find suggests that these conclusions should be revised. We also show that a machine learning algorithm (Twitter-Latent Dirichlet Allocation) is superior to a dictionary approach in classifying short messages like tweets.

We examine the impact of beauty on the academic career success of tenure-track accounting professors at top business schools in America and show that beauty plays a significant role. Specifically, after controlling for gender, ethnicity, publication history, work experience, and quality of alma mater, more attractive professors obtain better first school placements post-PhD and are granted tenure in a shorter period of time. These findings are broadly consistent with behavioral theory which predicts that facial attractiveness irrationally affects the perception of performance characteristics. Interestingly, there is no incremental benefit of attractiveness for the career progression from associate to full professor. This finding is consistent with the notion that the role played by beauty in promotion diminishes when the individual's ability and competency become apparent over time.

We study financial reporting and disclosure practices in China using survey methods similar to prior studies of U.S. firms (i.e., Graham et al., 2005; Dichev et al., 2013). Comparing earnings features, motives to manage and smooth earnings, and voluntary disclosure practices between the two countries, we reveal three major differences. First, Chinese firms exhibit a stronger preference for predictive, relative to verifiable, attributes of earnings that can signal stable firm performance to their stakeholders. Second, smooth earnings are desired by various stakeholders and can be achieved through coordination among connected stakeholders, which is conceptually different from earnings management. Third, Chinese firms consider public disclosure as less relevant in the reduction of the cost of capital. In addition, Chinese firms do not have a bias towards conservative reporting. We explain and reconcile these differences as resulting from some unique institutional features of China. Our study provides novel field evidence that contributes to, expands, and directly corroborates existing empirical studies. 0 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This study examines firms' global supply chain strategies following the staggered introduction of mandatory ESG disclosure in different countries. We find that mandatory ESG disclosure is associated with migration of suppliers to countries with opaque ESG-related corporate information environments and that such migration results in improvement of firms' perceived ESG profile. These findings suggest that mandated ESG disclosures motivate firms to appear de jure compliant with the mandates, but de facto ignorant about their real ESG-related responsibilities of their suppliers. Our findings also show that such effects are mitigated if the disclosure mandates include more targeted demands on supply chain due diligence processes. Further results indicate that supply chain composition changes in response to mandated ESG disclosure are less pronounced for firms located in countries with higher ESG-related social awareness, and firms subject to stronger external governance mechanisms such as monitoring of analysts and institutional investors. Our study informs policymakers and regulators on the global supply chain consequences stemming from the implementation of sustainability reporting guidelines.

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 investigates the effects of financial analysts’ technical and social skills on their performance and career advancement. Using financial analysts’ LinkedIn profiles, we find that analysts with strong technical skills endorsed by LinkedIn connections generate more accurate earnings forecasts and more profitable stock recommendations. Analysts with better social skills, proxied by the number of LinkedIn connections, have better communications with corporate management during conference calls and also produce more accurate earnings forecasts. Their stock recommendations are not more profitable but receive stronger market reactions. Further, these sociable analysts are more likely to be voted as All-Star Analysts and to move to high-status brokerage firms when they change jobs. These findings provide the first large-sample evidence on the different roles of technical and social skills in the financial industry.

This article uses transaction-level fund trading data from the United States to study the information advantage of institutional investors. Our research design follows a two-step procedure. In the first step, we identify funds that sell shares in firms before their unexpected revelation of stock option backdating (BD) investigations, and thus establish fund–firm pairs of interest. In the second step, we focus on trading that takes place at other times and find that the funds are more likely to make correct trades before the earnings announcements of their paired firms and that their trading performance for paired firms is better in general. This superior performance, however, is more evident in the pre-BD-announcement period and for firms whose BD investigations are initiated internally. The results imply that although institutions have access to private information on certain firms, this advantage disappears after the BD revelation, possibly due to reduced information leakage.

56 p. ; Includes bibliographical references (pp. 35-38). ; June 29, 2019. The authors wish to gratefully helpful comments from workshop participants at Tsinghua University, Singapore Management University, and conference delegates at the European Accounting Association and Canadian Academic Accounting Association annual meetings. They also acknowledge the financial support from the CPA/DeGroote Centre for Promotion of Accounting Education and Research at McMaster University.

Using a machine learning approach to process 11 million tweets posted by S&P 1500 firms from 2011 through 2016, we find that poor corporate social responsibility (CSR) performance firms tweet more about CSR activities and use tweets that are shorter, and with more passive voice and extreme tone. Good CSR performance firms tweet less about CSR, yet gain twice more followers per CSR tweet than poor CSR performance firms. Good CSR performance firms also experience a greater decrease in institutional ownership along with higher increases in bid-ask spread and stock return volatility after joining Twitter than do poor CSR performance firms. Our findings suggest that poor CSR performance firms play a greenwashing strategy, but this strategy is not effective in leading to capital market consequences.

Online Appendix to the Paper Guan, Yuyan and Li, Congcong and Lu, Hai and Wong, M.H. Franco, Regulations and Brain Drain: Evidence from Wall Street Star Analysts’ Career Choices (July 30, 2018). Available at: https://ssrn.com/abstract=3243135.

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We examine the impact of beauty on the academic career success of tenure-track accounting professors at top business schools in America, and show that beauty plays a significant role. Specifically, after controlling for gender, ethnicity, publication history, work experience, and quality of alma mater, more attractive professors obtain better first school placements post-PhD and are granted tenure in a shorter period of time. These findings are broadly consistent with behavioural theory which predicts that facial attractiveness irrationally affects the perception of performance characteristics. Interestingly, there is no incremental benefit of attractiveness for the career progression from associate to full professor. This finding is consistent with the notion that the role played by beauty in promotion diminishes when the individual’s ability and competency become apparent over time.

The Global Settlement, along with related regulations in the early 2000s, prohibits the use of investment banking revenue to fund equity research and compensate equity analysts. We find that all-star analysts from investment banks are more likely to exit the profession or move to the buy side after the regulations. The departed star analysts’ earnings revisions and stock recommendations are more informative than those of the remaining analysts who followed the same companies. To the extent that star analysts are superior to their nonstar counterparts in terms of research ability and ability to inform the market, the exit of star analysts represents a brain drain in the sell-side equity research industry. These results are consistent with the view that the regulations introduced to protect equity investors have unintended adverse effects on the investors due to a brain drain in investment banks. This paper was accepted by Suraj Srinivasan, accounting.

Practitioners have long criticized risk-factor disclosures in the 10-K as generic and boilerplate. In response, regulators emphasize the importance of being specific. By using a computing algorithm, this paper establishes a new measure (Specificity) to quantify the level of specificity of firms' qualitative risk-factor disclosures. We first examine determinants of variations in Specificity and document that firms with high proprietary costs provide less specific risk-factor disclosures. More importantly, we find that, controlling for numerous determinants, the market reaction to the 10-K filing is positively and significantly associated with Specificity. In addition, our results suggest that analysts are better able to assess fundamental risk when firms' risk-factor disclosures are more specific. Together, these findings suggest that more specific risk-factor disclosures benefit users of financial statements.

Our study documents a “Lemons” market failure of Chinese firms listed in the US in 2011 and a subsequent rebound by 2013. Our tests reveal that there was little difference in ex ante observable characteristics of fraudulent and non-fraudulent Chinese firms listed in the US prior to 2011 while entrepreneurs appear to have known their type. We document substantial costs of dishonesty and the failure of traditional market signaling mechanisms such as auditor or underwriter quality. We also show a return of Chinese firms after US and Chinese regulatory intervention in 2013 although this intervention was insufficient to fundamentally change the character of this market. Importantly, we find that factors capturing ex post settling up costs such as North America sales and CEO’s US education reduced the probability of financial fraud. Our results support the importance of legal and regulatory institutions as a necessary condition for properly functioning capital markets.