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.
- 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
- Scientists and students in the field of IT, finance and business
- Private investors, institutional investors
About the Author
Michael Nofer wrote his dissertation at the Chair of Information Systems | Electronic Markets at TU Darmstadt, Germany.
- DOI https://doi.org/10.1007/978-3-658-09508-6
- Copyright Information Springer Fachmedien Wiesbaden 2015
- Publisher Name Springer Vieweg, Wiesbaden
- eBook Packages Computer Science
- Print ISBN 978-3-658-09507-9
- Online ISBN 978-3-658-09508-6
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