We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects...

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 model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are...

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 the core concept of processing noisy information. In standard Bayesian frameworks, assessing the price impact of information requires perfect knowledge of news' precision. In practice, however, precision is rarely dis- closed. Therefore, we extend standard Bayesian...

This paper investigates the use of price intensities to estimate volatilities based on high-frequency data. We interpret the conditional probability for the occurence of a price event within a certain time horizon as a risk measure which allows us to obtain an estimator of the conditional...

In this paper, I model the intraday trading activity based on volume durations, i.e. the waiting time until a predetermined volume is absorbed by the market. Since this concept measures the trading volume per time it is strongly related to market liquidity. I focus on volumes measured...

This paper puts focus on the hazard function of inter-trade durations to characterize the intraday trading process. It sheds light on the time varying trade intensity and, thus, on the liquidity of an asset and the informations channels which propagate price signals among asymmetrically informed...

When making decisions, agents tend to make use of decisions others have made in similar situations. Ignoring this behavior in empirical models can be interpreted as a problem of omitted variables and may seriously bias parameter estimates and harm inference. We suggest a possibility of...

The recent availability of large data sets covering single transactions on financial markets has created a new branch of econometrics which has opened up a new door of looking at the microstructure of financial markets and its dynamics. The specific nature of transaction data such as the...