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OverviewMichael 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. Full Product DetailsAuthor: Michael NoferPublisher: Springer Fachmedien Wiesbaden Imprint: Springer Vieweg Edition: 2015 ed. Dimensions: Width: 14.80cm , Height: 0.90cm , Length: 21.00cm Weight: 2.006kg ISBN: 9783658095079ISBN 10: 3658095075 Pages: 128 Publication Date: 05 May 2015 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction.- 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.ReviewsAuthor InformationMichael Nofer wrote his dissertation at the Chair of Information Systems | Electronic Markets at TU Darmstadt, Germany. Tab Content 6Author Website:Countries AvailableAll regions |
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