Predicted stock issuers (PSIs) are firms with expected “high-investment and low-profit” (HILP) profiles that earn unusually low returns. We carefully document important features of PSI firms to provide insights on the economic mechanism behind the HILP phenomenon. Top-PSI firms are...

In this study, we examine the predictability of firm-specific stock price crashes using modern machine learning techniques and develop a crash prediction model that utilizes both financial ratios and textual data from the Management Discussion and Analysis (MD&A) of 10-K files. We show that...

This paper reviews research that uses big data and/or machine learning methods to provide insight relevant for equity valuation. Given the huge volume of research in this area, the review focuses on studies that either use or inform on accounting variables. The article concludes by providing...

This study proposes and validates “other information” in analysts' forecasts as a legitimate proxy for future cash flows, and examines its incremental role in explaining stock return volatility. We suggest that “other information” contains information about fundamentals beyond that...

This study uses U.S. closed-end funds to investigate whether the realized component of fair value earnings conveys information about future fund and benchmark market performance and whether the market impounds this predictive information into fund share prices. We find that the realized...

There is a logical bound on the time-series variability of analyst forecasts; when variability exceeds this bound it must be caused by something besides statistically rational forecasting. We document occurrences of excessively volatile analyst forecasts and show that they influence investment...