國立虎尾科技大學 |

The Value of Social Media for Predicting Stock Returns = Preconditions, Instruments and Performance Analysis /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The Value of Social Media for Predicting Stock Returns/ by Michael Nofer.
其他題名:	Preconditions, Instruments and Performance Analysis /
作者:	Nofer, Michael.
面頁冊數:	XVII, 128 p. 10 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Data mining. -
電子資源:	https://doi.org/10.1007/978-3-658-09508-6
ISBN:	9783658095086

The Value of Social Media for Predicting Stock Returns = Preconditions, Instruments and Performance Analysis /
Nofer, Michael.

The Value of Social Media for Predicting Stock ReturnsPreconditions, Instruments and Performance Analysis /[electronic resource] :by Michael Nofer. - 1st ed. 2015. - XVII, 128 p. 10 illus.online resource.

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. 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. .

ISBN: 9783658095086

Standard No.: 10.1007/978-3-658-09508-6doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

The Value of Social Media for Predicting Stock Returns = Preconditions, Instruments and Performance Analysis /
LDR:02867nam a22003975i 4500 001 963109
003 DE-He213
005 20200705121031.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783658095086 $9 978-3-658-09508-6
024 7 $a 10.1007/978-3-658-09508-6 $2 doi
035 $a 978-3-658-09508-6
050 4 $a QA76.9.D343
072 7 $a UNF $2 bicssc
072 7 $a COM021030 $2 bisacsh
072 7 $a UNF $2 thema
072 7 $a UYQE $2 thema
082 0 4 $a 006.312 $2 23
100 1 $a Nofer, Michael. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1258050
245 1 4 $a The Value of Social Media for Predicting Stock Returns $h [electronic resource] : $b Preconditions, Instruments and Performance Analysis / $c by Michael Nofer.
250 $a 1st ed. 2015.
264 1 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Vieweg, $c 2015.
300 $a XVII, 128 p. 10 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a 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.
520 $a 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. .
650 0 $a Data mining. $3 528622
650 0 $a Macroeconomics. $3 554837
650 0 $a Information technology. $3 559429
650 0 $a Business—Data processing. $3 1253699
650 1 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Macroeconomics/Monetary Economics//Financial Economics. $3 1069052
650 2 4 $a IT in Business. $3 1064965
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783658095079
776 0 8 $i Printed edition: $z 9783658095093
856 4 0 $u https://doi.org/10.1007/978-3-658-09508-6
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)