@techreport{Gro-Klumann2009Quantifying,
abstract = {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. Information-implied reactions in returns, volatility as well as liquidity demand and supply are quantified by a high-frequency VAR model using 20 second intervals. Analyzing a cross-section of stocks traded at the London Stock Exchange (LSE), we find market-wide robust news-dependent responses in volatility and trading volume. However, this is only true if news items are classified as highly relevant. Liquidity supply reacts less distinctly due to a stronger influence of idiosyncratic noise. Furthermore, evidence for abnormal highfrequency returns after news in sentiments is shown.},
address = {Frankfurt, Main},
author = {Axel Gro\ss{}-Klu\ss{}mann and Nikolaus Hautsch},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {G14; C32; 330; Firm-specific News; News Sentiment; High-frequency Data; Volatility; Liquidity; Abnormal Returns; B\"{o}rsenkurs; Kapitalertrag; Volatilit\"{a}t; Ank\"{u}ndigungseffekt; Publizit\"{a}tspflicht; Informationseffizienz; Marktliquidit\"{a}t; Sch\"{a}tzung; Gro\ss{}britannien},
language = {eng},
number = {2009/31},
publisher = {Center for Financial Studies},
title = {Quantifying high-frequency market reactions to real-time news sentiment announcements},
type = {CFS Working Paper},
url = {http://hdl.handle.net/10419/43206},
year = {2009}
}
