Nofer, Michael
The value of social media for predicting stock returns : preconditions, instruments and performance analysis Michael Nofer; with a foreword by Oliver Hinz - Wiesbaden : Springer Vieweg, c2015. - xvi, 128 p. : ill. ; 21 cm. - Research .
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 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.
978-3658095079
Speculation
Stock price forecasting
Online social networks--Economic aspects
Social media--Economic aspects
Business & Economics--Finance
332.632220112 NO VA
The value of social media for predicting stock returns : preconditions, instruments and performance analysis Michael Nofer; with a foreword by Oliver Hinz - Wiesbaden : Springer Vieweg, c2015. - xvi, 128 p. : ill. ; 21 cm. - Research .
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 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.
978-3658095079
Speculation
Stock price forecasting
Online social networks--Economic aspects
Social media--Economic aspects
Business & Economics--Finance
332.632220112 NO VA