In limit order book markets, traders face the problem whether to display or hide their orders. While hiding reduces exposure impact, exposing can increase execution priority. Based on order flow dynamics, we develop a structural model that captures this trade-off. A central aspect of this work...

We take advantage of a unique data set, NASDAQ ModelView, to empirically analyze the determinants and the impact of hidden liquidity on public exchanges. Our findings are as follows. First, the cross-sectional presence of hidden liquidity is well explained by observable and readily available...

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...

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...

SFB 649 Discussion Paper 2007-052 Capturing Common Components in High- Frequency Financial Time Series: A Multivariate Stochastic Multiplicative Error Model Nikolaus Hautsch* * Humboldt-Universität zu Berlin, Germany This research was supported by the Deutsche...