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The Value of Social Media for Predicting Stock Returns

Preconditions, Instruments and Performance Analysis

  • Michael Nofer

Table of contents

About this book

Introduction

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.  

Keywords

Big Data Predictive Analytics Social Media platforms Stock Prediction Community Twitter Wisdom of Crowds

Authors and affiliations

  • Michael Nofer
    • 1
  1. 1.Lehrstuhl für WirtschaftsinformatikTechnical University DarmstadtDarmstadtGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-658-09508-6
  • Copyright Information Springer Fachmedien Wiesbaden 2015
  • Publisher Name Springer Vieweg, Wiesbaden
  • eBook Packages Computer Science
  • Print ISBN 978-3-658-09507-9
  • Online ISBN 978-3-658-09508-6
  • Buy this book on publisher's site
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