Association Between Online Texts and Stock Prices
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F17%3A43911768" target="_blank" >RIV/62156489:43110/17:43911768 - isvavai.cz</a>
Alternative codes found
RIV/26867184:_____/17:N0000010
Result on the web
<a href="http://mvso.cz/wp-content/uploads/2017/06/IDS_2017_Conference_Proceedings.pdf" target="_blank" >http://mvso.cz/wp-content/uploads/2017/06/IDS_2017_Conference_Proceedings.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Association Between Online Texts and Stock Prices
Original language description
The paper is focused on quantifying the strength of association between stock price movements and content of texts of corresponding companies. As the principal tool, machine learning based classification was used. Four different variable parameters of data preparation were used and six classifiers were applied to the data. It has been found that a classifier type and a smoothing method applied to stock price data were the most important factors. After the mentioned parameters were considered and investigated texts related to periods with significant stock price movements were separated with accuracy ranging from about 60 to 74% which demonstrates a nonrandom association between these two time series.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA16-26353S" target="_blank" >GA16-26353S: Sentiment and its impact on stock markets</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Scientific Conference: International Day of Science 2017. Economics, Management, Innovation
ISBN
978-80-7455-060-7
ISSN
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e-ISSN
neuvedeno
Number of pages
7
Pages from-to
23-29
Publisher name
Univerzita Palackého v Olomouci
Place of publication
Olomouc
Event location
Olomouc
Event date
Apr 25, 2017
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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