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...

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

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...

Reliable estimates of variances and covariances are crucial for portfolio management and risk controlling. This paper investigates alternative methods to estimate time varying variance-covariance matrices: ordinary estimates and exponentially weighted moving averages in comparison to Markov...

We document that investors can actually profit from the contemporaneous link between earnings accuracy and recommendation profitability (Loh and Mian (2006)). Differentiating between "able" and "lucky" analysts we suggest an implementable, i.e. look-ahead bias free, trading strategy that yields...

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...