Analyzing the relationship between differentiated online sentiment and company-specific stock prices
- PRACTITIONERS AND RESEARCHERS ALIKE INCREASINGLY USE SOCIAL MEDIA MESSAGES AS AN ADDITIONAL SOURCE OF INFORMATION WHEN DEALING WITH STOCKS. BASED ON EMOTION THEORY AND AN ESTABLISHED SENTIMENT LEXICON, WE DEVELOP AND APPLY AN OPEN SOURCE DICTIONARY FOR THE ANALYSIS OF SEVEN DIFFERENT EMOTIONS IN 5.5 MILLION TWITTER MESSAGES ON 33 S&P 100 COMPANIES. WE FIND VARYING EXPLANATORY POWER OF DIFFERENT EMOTIONS (ESP. HAPPINESS, AND DEPRESSION) FOR COMPANY-SPECIFIC STOCK PRICE MOVEMENTS OVER A PERIOD OF THREE MONTHS.
Author: | Marten Risius, Fabian Akolk, Roman Beck |
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URN: | urn:nbn:de:hebis:30:3-579817 |
ISSN: | 1866-1238 |
Parent Title (English): | EFL quarterly : an E-Finance Lab publication |
Publisher: | E-Finance Lab e.V. |
Place of publication: | Frankfurt am Main |
Document Type: | Article |
Language: | English |
Year of Completion: | 2015 |
Year of first Publication: | 2015 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2021/01/28 |
Volume: | 2015 |
Issue: | 3 |
Page Number: | 3 |
First Page: | 6 |
Last Page: | 8 |
HeBIS-PPN: | 477254357 |
Institutes: | Angeschlossene und kooperierende Institutionen / E-Finance Lab e.V. |
Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Sammlungen: | Universitätspublikationen |
Licence (German): | Deutsches Urheberrecht |