We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ('efficient return') factor and two market-side-specific components...

Until October 2004 corporate insiders in Germany were required to report trades in the shares of their firm 'without delay'. In practice substantial reporting delays were common. We show that the delays are systematically related to the characteristics of the firm. Delays are longer in...

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,...

In the pre-Sarbanes-Oxley era corporate insiders were required to report trades in shares of their firm until the 10th of the month following the trade. This gave them considerable flexibility to time their trades and reports strategically, e.g., by executing a sequence of trades and reporting...

Regulations in the pre-Sarbanes-Oxley era allowed corporate insiders considerable flexibility in strategically timing their trades and SEC filings, for example, by executing several trades and reporting them jointly after the last trade. We document that even these lax reporting requirements...

We analyze transactions by corporate insiders in Germany. We find that insider trades are associated with significant abnormal returns. Insider trades that occur prior to an earnings announcement have a larger impact on prices. This result provides a rationale for the UK regulation that...

We analyze the decision to announce an open market share repurchase and the share price reaction to the announcement. We use a conditional estimation approach which takes into account that the repurchase decision is made rationally and that, consequently, there is a potential selection bias....

An important claim of Bayesian learning and a standard assumption in price discovery models is that the strength of the price impact of unanticipated information depends on the precision of the news. In this paper, we test for this assumption by analyzing intra-day price responses of CBOT T-bond...

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...