The Value of Social Media for Predicting Stock Returns, 2015 Preconditions, Instruments and Performance Analysis
Langue : Anglais
Auteur : Nofer Michael
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.
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.
Michael Nofer wrote his dissertation at the Chair of Information Systems | Electronic Markets at TU Darmstadt, Germany.
Publication in the field of technical sciences
Includes supplementary material: sn.pub/extras
Date de parution : 05-2015
Ouvrage de 128 p.
14.8x21 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 52,74 €
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