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Goethe-Universität Frankfurt am Main >
Center for Financial Studies (CFS), Universität Frankfurt a. M. >
CFS Working Paper Series, Universität Frankfurt a. M. >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/43206
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Full metadata record
| DC Field | | Value | | Language |
| dc.contributor.author | | Groß-Klußmann, Axel | | en_US |
| dc.contributor.author | | Hautsch, Nikolaus | | en_US |
| dc.date.accessioned | | 2010-03-29 | | en_US |
| dc.date.accessioned | | 2010-12-15T09:21:43Z | | - |
| dc.date.available | | 2010-12-15T09:21:43Z | | - |
| dc.date.issued | | 2009 | | en_US |
| dc.identifier.uri | | http://hdl.handle.net/10419/43206 | | - |
| dc.description.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. | | en_US |
| dc.language.iso | | eng | | en_US |
| dc.publisher | | Center for Financial Studies Frankfurt, Main | | en_US |
| dc.relation.ispartofseries | | CFS Working Paper 2009/31 | | en_US |
| dc.subject.jel | | G14 | | en_US |
| dc.subject.jel | | C32 | | en_US |
| dc.subject.ddc | | 330 | | en_US |
| dc.subject.keyword | | Firm-specific News | | en_US |
| dc.subject.keyword | | News Sentiment | | en_US |
| dc.subject.keyword | | High-frequency Data | | en_US |
| dc.subject.keyword | | Volatility | | en_US |
| dc.subject.keyword | | Liquidity | | en_US |
| dc.subject.keyword | | Abnormal Returns | | en_US |
| dc.subject.stw | | Börsenkurs | | en_US |
| dc.subject.stw | | Kapitalertrag | | en_US |
| dc.subject.stw | | Volatilität | | en_US |
| dc.subject.stw | | Ankündigungseffekt | | en_US |
| dc.subject.stw | | Publizitätspflicht | | en_US |
| dc.subject.stw | | Informationseffizienz | | en_US |
| dc.subject.stw | | Marktliquidität | | en_US |
| dc.subject.stw | | Schätzung | | en_US |
| dc.subject.stw | | Großbritannien | | en_US |
| dc.title | | Quantifying high-frequency market reactions to real-time news sentiment announcements | | en_US |
| dc.type | | Working Paper | | en_US |
| dc.identifier.ppn | | 622759442 | | en_US |
| dc.rights | | http://www.econstor.eu/dspace/Nutzungsbedingungen | | en_US |
| dc.identifier.repec | | RePEc:zbw:cfswop:200931 | | - |
| Appears in Collections: | | CFS Working Paper Series, Universität Frankfurt a. M.
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