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...

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...

Analysts who provide 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...

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...

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...

Trading under limited pre-trade transparency becomes increasingly popular on financial markets. We provide first evidence on traders' use of (completely) hidden orders which might be placed even inside of the (displayed) bid-ask spread. Employing TotalView-ITCH data on order messages at NASDAQ,...

We introduce a copula-based dynamic model for multivariate processes of (non-negative) high-frequency trading variables revealing time-varying conditional variances and correlations. Modeling the variables' conditional mean processes using a multiplicative error model we map the resulting...