【Topic】
Do Within-portfolio Commonalities in Human Capital Matter to Analyst Forecast Performance?
【Host】
Prof. AN Ran, assistant professor of Department of Finance, School of Management, Xiamen University
【Abstract】
We show that financial analysts covering cross-industry firms with similar human capital profiles issue more accurate earnings forecasts and investors recognize their better forecast performance. The results hold after controlling for the broker fixed effects, non-random matching of analysts to firms, and fundamentals of covered firms. Our inferences are also robust to several difference-in-differences designs. In addition, these analysts play a larger role in cross-industry information transfer and serve as more effective monitors of covered firms’ employee treatment. Further, the effects are more pronounced for covered firms whose prospects are more dependent on labor-related signals, that is, firms with higher labor intensity, higher labor productivity, higher unionization rates, and more complex human capital profiles. Overall, our findings suggest that commonalities in cross-industry firms’ human capital may constitute an information advantage for analysts covering these firms in their portfolios.
【Speaker】
Prof. HUANG Hong
Lawrence Huang obtained his Ph.D. in Accounting at The Chinese University of Hong Kong in 2019. He is currently an assistant professor at Deakin University in Melbourne. His main research areas include disclosure, political connections, M&A, and non-investor stakeholders. In particular, he examines how politician’s incentives and corporate political strategy affect shareholders and other stakeholders in the context of elections and economic regulations. Moreover, he studies how human capital issues such as employee quality and disclosures of labor-related information affect capital markets, corporate actions, and analyst forecasts.
