The Value of Social Media for Predicting Stock Returns

Preconditions, Instruments and Performance Analysis
2015
ISBN: 978-3-658-09507-9
Verlag: Springer

Buch, Englisch, 128 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 2006 g

Michael Nofer examines whether and to what extent Social Media can be used to predict stock returns. Market-relevant information is available on various platforms on the Internet, which largely consist of user generated content. For instance, emotions can be extracted in order to identify the investors' risk appetite and in turn the willingness to invest in stocks. Discussion forums also provide an opportunity to identify opinions on certain companies. Taking Social Media platforms as examples, the author examines the forecasting quality of user generated content on the Internet.

Zielgruppe

- Scientists and students in the field of IT, finance and business
- Private investors, institutional investors

Autoren/Hrsg.

Nofer, Michael

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Social Media, Semantic Web, Web 2.0
• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Börse, Rohstoffe
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management

Inhaltsverzeichnis

Introduction.- Market Anomalies on Two-Sided Auction Platforms.- Are Crowds on the Internet Wiser than Experts? – The Case of a Stock Prediction Community.- Using Twitter to Predict the Stock Market: Where is the Mood Effect?.- The Economic Impact of Privacy Violations and Security Breaches – A Laboratory Experiment.- Literature.

Über Autor(innen)

Michael Nofer wrote his dissertation at the Chair of Information Systems Electronic Markets at TU Darmstadt, Germany.