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The Value of Social Media for Predicting Stock Returns

Preconditions, Instruments and Performance Analysis

  • Book
  • © 2015

Overview

Authors:
  1. Michael Nofer

    1. Lehrstuhl für Wirtschaftsinformatik, Technical University Darmstadt, Darmstadt, Germany

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  • Publication in the field of technical sciences
  • Includes supplementary material: sn.pub/extras

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Table of contents (5 chapters)

  1. Front Matter

    Pages I-XVII
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  2. Introduction

    • Michael Nofer
    Pages 1-10

  3. Market Anomalies on Two-Sided Auction Platforms

    • Michael Nofer
    Pages 11-26

  4. Are Crowds on the Internet Wiser than Experts? – The Case of a Stock Prediction Community

    • Michael Nofer
    Pages 27-61

  5. Using Twitter to Predict the Stock Market: Where is the Mood Effect?

    • Michael Nofer
    Pages 63-88

  6. The Economic Impact of Privacy Violations and Security Breaches – A Laboratory Experiment

    • Michael Nofer
    Pages 89-108

  7. Back Matter

    Pages 109-128
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Keywords

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.

Authors and Affiliations

  • Lehrstuhl für Wirtschaftsinformatik, Technical University Darmstadt, Darmstadt, Germany

    Michael Nofer

About the author

Michael Nofer wrote his dissertation at the Chair of Information Systems | Electronic Markets at TU Darmstadt, Germany.

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