We find that forecast revisions by analysts with more favorable surnames elicit stronger market reactions. The effect is stronger among firms with lower institutional ownership and for analysts with non-American first names. Following the 9/11 terrorist attacks, and France and Germany's...

This study examines whether sell-side equity analysts help the market assimilate information contained in global climate change. Using a new measure of firm sensitivity to climate change, we show that analysts located in states where firms exhibit greater sensitivity to abnormal temperature...

This paper examines whether sell-side equity analysts use labor market information, as reflected in job postings and corporate layoffs, to improve the quality of their earnings forecasts. We posit that labor market activities contain useful incremental information about the related firm and the...

Using the economic setting of sell-side equity analysts, we demonstrate that racial/ethnic diversity does not always help minority groups. Race/ethnicity of analysts influences their forecasting style and accuracy, where these accuracy differences primarily reflect the effects of brokerage...

Using machine learning methods, we develop a new measure of aggregate analyst sentiment. We first train analyst-specific neural network (NN) models that capture each analyst's common biases across firms. Using NN model outputs, we decompose the forecast errors of individual analysts into...

Using Bloomberg’s daily Twitter Sentiment data for S&P500 firms, we show that Twitter information reduces forecast optimism and improves forecast accuracy of sell-side equity analysts. Negative Twitter information is more influential, and this effect is distinct from the impact of news. Using...