This paper investigates the determinants of six different lottery-like stock return definitions that have been analyzed separately in prior literature. While we focus on information uncertainty as captured by accounting information, mispricing, institutional ownership and default risk as main...

This study shows how venture capital investors can identify potential biases in multi-year management forecasts before an investment decision and derive significantly more accurate failure predictions. By advancing a cross-sectional projection method developed by prior research and using...

We predict and find that revisions are driven by the same determinants as forecast errors. In addition to the intuitive impact of news on revisions, we show that a second major driver of revisions is the change in analyst incentives to systematically bias their earnings forecasts. Taken...

We introduce a new way to measure the forecast effort that analysts devote to their earnings forecasts by measuring the analyst's general effort for all covered firms. While the commonly applied effort measure is based on analyst behavior for one firm, our measure considers analyst behavior for...

We develop a model to predict bankruptcies, exploiting that negative book equity is a strong indicator of financial distress. Accordingly, our key predictor of bankruptcy is the probability that future losses will deplete a firm's book equity. To calculate this probability, we use earnings...

We analyze three different mechanical models to forecast earnings and compare their forecasts with those of analysts. Moreover, we evaluate implied cost of capital (ICC) estimates that are based on these forecasts. With our analyses we answer three open questions in the literature. 1) Do model...

We substantially improve cross-sectional earnings forecast models, such as Hou, van Dijk, and Zhang (2012), by enriching their information sets by an interim earnings growth measure extracted from quarterly reports. This yields significantly more accurate out-of-sample earnings forecasts and...