Arbeitspapier
Predicting Stock Price Volatility by Analyzing Semantic Content in Media
Current models for predicting volatility do not incorporate information flow and are solely based on historical volatilities. We suggest a method to quantify the semantic content of words in news articles about a company and use this as a predictor of its stock volatility. The results show that future stock volatility is better predicted by our method than the conventional models. We also analyze the functional role of text in media either as a passive documentation of past information flow or as an active source for new information influencing future volatility. Our data suggest that semantic content may take both roles.
- Language
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Englisch
- Bibliographic citation
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Series: Working Paper ; No. 2014:38
- Classification
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Wirtschaft
General Financial Markets: Other
- Subject
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volatility
information flow
latent semantic analysis
GARCH
- Event
-
Geistige Schöpfung
- (who)
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Asgharian, Hossein
Sikström, Sverker
- Event
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Veröffentlichung
- (who)
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Lund University, School of Economics and Management, Department of Economics
- (where)
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Lund
- (when)
-
2014
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Asgharian, Hossein
- Sikström, Sverker
- Lund University, School of Economics and Management, Department of Economics
Time of origin
- 2014
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