The Value of Social Media for Predicting Stock Returns
Preconditions, Instruments and Performance Analysis
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Beschreibung
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.
Contents
- 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
Target Groups
- 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.
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.
Publication in the field of technical sciences Includes supplementary material: sn.pub/extras
Autor*in
Michael Nofer
Themen in »The Value of Social Media for Predicting Stock Returns«
Big Data Predictive Analytics Social Media platforms Stock Prediction Community Twitter Wisdom of Crowds