Knowledge that Transforms

With the advent of social media, individual public opinions about fi rms can be more easily accessed and aggregated, and recent research suggests that various platforms, such as Twitter, Seeking Alpha, and Estimize, provide information relevant in predicting future corporate disclosures. Rather than focusing on the general public's opinion, we examine a public platform designed to convey insider information - Glassdoor.com, where employees voluntarily share their opinions on a number of issues, including the company's near-term business outlook. Using a sample of approximately 150,000 employee reviews, we extract both employees' explicit assessments of outlook and a measure of their latent outlook derived from factor analysis. We then examine whether the opinions employees share on social media relate to future corporate disclosures. In particular, we fi nd evidence that employee opinions are useful in predicting growth in key income statement information, transitory reporting items (e.g., restructuring charges), earnings surprises, and management forecast news. While voluntary disclosures about fi rm performance have traditionally come from executives, our evidence suggests that rank-and-fi le employees are chipping away at upper-level management's exclusive control over that channel.

This paper investigates the usefulness of the real-time macroeconomic news-flow as a leading indicator of firm-level end-of-quarter realized earnings. Using recent advances in macroeconomics, I develop a nowcasting model for quarterly earnings and provide two main findings. First, I show that my model provides out-of-sample expectations that are as accurate as analysts’ forecasts. Second, macroeconomic news embedded in my nowcasts is not fully incorporated into investors’ earnings expectations and predicts future abnormal returns around earnings announcements. These findings have three main implications for capital markets research. First, real-time macroeconomic news can be used to update earnings expectations in real-time. Second, there are economic benefits of doing so, as evidenced by the magnitude of risk-adjusted returns around earnings announcements. Third, after three decades of almost nonexistent research on time-series models for quarterly earnings, the door is open again for fruitful research in this area.