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...

This paper delineates the simultaneous impact of non-anticipated information on mean and variance of the intraday return process by including appropriate variables accounting for the news flow into both the mean and the variance function. This allows us to differentiate between the consistent...

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...

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...

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...

We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven...

There is strong evidence that macroeconomic releases influence prices in financial markets. However, why do markets react to some announcements while they ignore others with a similar content? Based on a Bayesian learning model, we show that market impact is mainly determined by information...

Der Finanzplatz Deutschland ist im internationalen Wettbewerb einem starken Druck ausgesetzt. Die Diskussionsteilnehmer erörtern den Status quo des strukturellen Umfelds sowie mögliche Entwicklungstendenzen. So spielt die Bankenlandschaft eine ebenso bestimmende Rolle wie die finanzielle...

Analysts providing more accurate earnings forecasts also issue more profitable recommendations. We demonstrate how investors can profit from this contemporaneous link by differentiating between able and lucky analysts. In line with previous studies, we find that past track records alone are not...