This study examines the relevance of financial and non-financial information for the valuation of venture-capital investments. Based on a hand-collected dataset on venture-backed start-ups in Germany, we investigate the internal due diligence documents of over 200 investment rounds. We document...

We investigate the co-movement of stock prices and intrinsic value estimates focusing on the estimation of risk. We apply risk measurements based on a) market and b) accounting data. We find that price and value co-move from 1983 to 2014 on an index-level using accounting-based risk measurement...

We analyze how markets adjust to new information when the reliability of news is uncertain and has to be estimated itself. We propose a Bayesian learning model where market participants receive fundamental information along with noisy estimates of news' precision. It is shown that the efficiency...

We analyze how markets adjust to new information when the reliability of news is uncertain and has to be estimated itself. We propose a Bayesian learning model where market participants receive fundamental information along with noisy estimates of news' precision. It is shown that the efficiency...

Bayesian learning provides the core concept of information processing in financial markets. Typically, it is assumed that market participants know perfectly the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning,...

Bayesian learning provides the core concept of processing noisy information. In standard Bayesian frameworks, assessing the price impact of information requires perfect knowledge of news’ precision. In practice, however, precision is rarely dis- closed. Therefore, we extend standard Bayesian...