Using Online Data in Predicting Stock Price Movements: Methodological and Practical Aspects
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F19%3A43913765" target="_blank" >RIV/62156489:43110/19:43913765 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.4018/978-1-5225-5586-5.ch006" target="_blank" >https://doi.org/10.4018/978-1-5225-5586-5.ch006</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4018/978-1-5225-5586-5.ch006" target="_blank" >10.4018/978-1-5225-5586-5.ch006</a>
Alternative languages
Result language
angličtina
Original language name
Using Online Data in Predicting Stock Price Movements: Methodological and Practical Aspects
Original language description
A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital markets where the information contained in online environments is quite topical. The presented experiments were designed to reveal the association between online texts (from Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies. As the method for quantifying the association, machine learning-based classification was chosen. The experiments showed that the data preparation procedure had a substantial impact on the results. Thus, different stock price smoothing, the lags between the release of documents and related stock price changes, levels of a minimal stock price change, different weighting schemes for structured document representation, and classifiers were studied. The chapter also shows how to use currently available open source technologies to implement a system for accomplishing the task.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
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
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Techno-Social Systems for Modern Economical and Governmental Infrastructures
ISBN
978-1-5225-5586-5
Number of pages of the result
35
Pages from-to
125-159
Number of pages of the book
351
Publisher name
IGI Global
Place of publication
Hershey
UT code for WoS chapter
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