A new semiparametric proportional hazard rate model is proposed which extends standard models to include a dynamic specification. Two main problems are resolved in the course of this paper. First, the partial likelihood approach to estimate the components of a standard proportional hazard model...

We examine intraday market reactions to stock-specific news. Using pre-processed data from an automated news analytics tool based on linguistic pattern recognition we exploit information on the relevance and the direction of company-specific news. Concise news-implied reactions in returns,...

In this paper, we provide new empirical evidence on order submission activity and price impacts of limit orders at NASDAQ. Employing NASDAQ TotalView-ITCH data, we find that market participants dominantly submit limit orders with sizes equal to a round lot. Most limit orders are canceled almost...

Exploiting NASDAQ order book data and difference-in-differences methodology, we identify the distinct effects of trading pause mechanisms introduced on U.S. stock exchanges after May 2010. We show that the mere existence of such a regulation constitutes a safeguard which makes market...

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 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...

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. We decompose bid and ask returns into a common ("efficient return") factor and two market-side-specific components...

We examine intra-day market reactions to news in stock-specific sentiment disclosures. Using pre-processed data from an automated news analytics tool based on linguistic pattern recognition we extract information on the relevance as well as the direction of company-specific news....