Quantifying high-frequency market reactions to real-time news sentiment announcements
- 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. JEL-Classification: G14, C32
Verfasserangaben: | Axel Groß-Klußmann, Nikolaus HautschORCiDGND |
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URN: | urn:nbn:de:hebis:30-73618 |
Titel des übergeordneten Werkes (Deutsch): | Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2009,31 |
Schriftenreihe (Bandnummer): | CFS working paper series (2009, 31) |
Dokumentart: | Arbeitspapier |
Sprache: | Englisch |
Jahr der Fertigstellung: | 2009 |
Jahr der Erstveröffentlichung: | 2009 |
Veröffentlichende Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Datum der Freischaltung: | 13.01.2010 |
Freies Schlagwort / Tag: | Abnormal Returns; Firm-specific News; High-frequency Data; Liquidity; News Sentiment; Volatility |
GND-Schlagwort: | Tagesgeschäft; Volatilität; Value at Risk |
HeBIS-PPN: | 220677433 |
Institute: | Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS) |
DDC-Klassifikation: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Lizenz (Deutsch): | Deutsches Urheberrecht |