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The Value of Social Media for Predicting Stock Returns - Preconditions, Instruments and Performance Analysis

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  • Nofer, Michael

Abstract

The cumulative dissertation of Michael Nofer examines whether Social Media platforms can be used to predict stock returns. Market-relevant information is available on various platforms on the Internet, which consist largely 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 extract opinions on certain stocks. Taking Social Media platforms as examples, the dissertation examines the forecasting quality of user generated content on the Internet.

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  • Nofer, Michael, 2014. "The Value of Social Media for Predicting Stock Returns - Preconditions, Instruments and Performance Analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 69259, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:69259
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/69259/
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