In recent studies, the analysts' consensus forecasts are widely used as a proxy for the unobservable market's consensus expectation of future earnings. As prior studies indicate, the analysts' consensus forecasts measure the true underlying construct with errors and the errors may vary...

For a sample of commercial banks during 1994 – 2008, we find that accumulated fair value adjustments for interest-bearing investment securities are positively associated with future interest income and total realized income from these investments. Additional tests reveal that accumulated fair...

This paper examines the impact of expectations manipulation on the usefulness of analyst forecasts in the residual income valuation model. Recognizing that firms may guide down analyst forecast to either truthfully communicate information (legitimate guidance) or mislead analysts to produce...

This study examines whether the market reacts more strongly to earnings forecast revisions when financial analysts supplement their earnings forecasts with sales forecasts. I find that earnings forecast revisions supplemented with sales forecast revisions have a greater impact on security prices...

An earnings manipulation detection model based on forensic accounting principles (Beneish 1999) has substantial out-of-sample ability to predict cross-sectional returns. We show that the model correctly identified, ahead of time, 12 of the 17 highest profile fraud cases in the period 1998-2002....

This paper examines the real effects of weather on firm performance, using temperature as our proxy for weather. The relation between temperature and performance depends on season, industry, geographic location, and is often firm-specific. Therefore, to test this relation we adapt a measure of...

Jensen and Meckling (1976) claim that by facilitating monitoring of firms’ activities, security analysis by financial analysts can reduce agency costs between management and external capital providers, and thereby increase shareholder value. Additionally, boards are required to design...

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...

More than 650 U.S. public company executives predict the stock price response to their quarterly financial reports and share their prediction after under a nondisclosure agreement. Despite having full knowledge of the reports before their release, executives’ estimates differ from realized...

This paper examines the relation between firm-level implied volatility skew and the likelihood of extreme negative events, or crash risk. I show that volatility skew identifies which firms are likely to experience crashes, but only in short-window earnings announcement periods. The predictive...