000			01844nam a2200253 a 4500
999			_c27008 _d27008
001			61023
020			_a978-3658095079
082			_a332.632220112 NO VA
100			_aNofer, Michael _949107
245	1	4	_aThe value of social media for predicting stock returns : _bpreconditions, instruments and performance analysis _cMichael Nofer; with a foreword by Oliver Hinz
260			_aWiesbaden : _bSpringer Vieweg, _cc2015.
300			_axvi, 128 p. : _bill. ; _c21 cm.
490	1		_aResearch
505	0		_aIntroduction.- 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.
520			_aMichael 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.
650		7	_aSpeculation _948855
650		7	_aStock price forecasting _949035
650		7	_aOnline social networks _xEconomic aspects _916774
650		7	_aSocial media _xEconomic aspects _912004
650		7	_aBusiness & Economics _xFinance _96426
700			_aHinz, Oliver, _eForeword by _949108
856			_uhttps://uowd.box.com/s/erf8ef475rmvuebm5wn6m7gtbp6wws1g _zLocation Map
942			_cREGULAR _2ddc