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The Value of Social Media for Predicting Stock Returns
The Value of Social Media for Predicting Stock Returns
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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,…
  • Leidėjas:
  • Metai: 2015
  • Puslapiai: 128
  • ISBN-10: 3658095075
  • ISBN-13: 9783658095079
  • Formatas: 14.8 x 21 x 0.9 cm, minkšti viršeliai
  • Kalba: Anglų

The Value of Social Media for Predicting Stock Returns (el. knyga) (skaityta knyga) | knygos.lt

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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.

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  • Autorius: Michael Nofer
  • Leidėjas:
  • Metai: 2015
  • Puslapiai: 128
  • ISBN-10: 3658095075
  • ISBN-13: 9783658095079
  • Formatas: 14.8 x 21 x 0.9 cm, minkšti viršeliai
  • Kalba: Anglų

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.

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