Overview
- Publication in the field of technical sciences
- Includes supplementary material: sn.pub/extras
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
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.
Similar content being viewed by others
Keywords
Table of contents (5 chapters)
-
Front Matter
-
Back Matter
Authors and Affiliations
About the author
Michael Nofer wrote his dissertation at the Chair of Information Systems | Electronic Markets at TU Darmstadt, Germany.
Bibliographic Information
Book Title: The Value of Social Media for Predicting Stock Returns
Book Subtitle: Preconditions, Instruments and Performance Analysis
Authors: Michael Nofer
DOI: https://doi.org/10.1007/978-3-658-09508-6
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Fachmedien Wiesbaden 2015
Softcover ISBN: 978-3-658-09507-9Published: 05 May 2015
eBook ISBN: 978-3-658-09508-6Published: 21 April 2015
Edition Number: 1
Number of Pages: XVII, 128
Number of Illustrations: 10 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Macroeconomics/Monetary Economics//Financial Economics, IT in Business