The Value of Social Media for Predicting Stock Returns (Record no. 56081)
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fixed length control field | 03158nam a22004935i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-658-09508-6 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200421111851.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 150421s2015 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783658095086 |
-- | 978-3-658-09508-6 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.312 |
100 1# - AUTHOR NAME | |
Author | Nofer, Michael. |
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Title | The Value of Social Media for Predicting Stock Returns |
Sub Title | Preconditions, Instruments and Performance Analysis / |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XVII, 128 p. 10 illus. |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | 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 ## - SUMMARY, ETC. | |
Summary, etc | 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. . |
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General subdivision | Data processing. |
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Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-658-09508-6 |
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Koha item type | eBooks |
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-- | Wiesbaden : |
-- | Springer Fachmedien Wiesbaden : |
-- | Imprint: Springer Vieweg, |
-- | 2015. |
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-- | online resource |
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-- | text file |
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-- | Computer science. |
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-- | Information technology. |
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-- | Business |
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-- | Data mining. |
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-- | Macroeconomics. |
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-- | Computer Science. |
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-- | Data Mining and Knowledge Discovery. |
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-- | Macroeconomics/Monetary Economics//Financial Economics. |
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-- | IT in Business. |
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-- | ZDB-2-SCS |
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