This study assesses the impact of the quality of bankruptcy data on the estimation and evaluation of bankruptcy prediction models. To meet this objective, we develop a systematic methodology to obtain bankruptcy information from corporate news releases and public sources. Then, applying this...

We analyze the quality of macroeconomic survey forecasts. Recent findings indicate that they are anchoring biased. This irrationality would challenge the results of a wide range of empirical studies, e.g., in asset pricing, volatility clustering or market liquidity, which rely on survey data to...

Standard equity valuation approaches (i.e., DDM, RIM, and DCF model) are derived under the assumption of ideal conditions, such as infinite payoffs and clean surplus accounting. Because these conditions are hardly ever met, we extend the standard approaches, based on the fundamental principle of...

We introduce a novel framework to predict the relative accuracy of sell-side analysts' annual earnings forecasts out-of-sample. Prior studies only evaluate forecasts shortly before the corresponding earnings release. In contrast, our study is the first to provide long-term predictions which are...

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...

Recent findings indicate that macroeconomic survey forecasts are anchoring biased and therefore are inefficient. However, despite highly significant test coefficients a bias adjustment does not improve forecasts' quality. We find that the cognitive bias is a statistical artifact because the...