Examining Stock Price Movements on Prague Stock Exchange Using Text Classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F17%3A43912416" target="_blank" >RIV/62156489:43110/17:43912416 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.17781/P002293" target="_blank" >http://dx.doi.org/10.17781/P002293</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17781/P002293" target="_blank" >10.17781/P002293</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Examining Stock Price Movements on Prague Stock Exchange Using Text Classification

Popis výsledku v původním jazyce

The goal of the article was to examine the relationship between the content of text documents published on the Internet and the direction of movement of stock prices on the Prague Stock Exchange. The relationship was modeled by text classification. As data were used news articles and discussion posts on Czech websites and the value of the PX stock index and stock price of company CEZ. Document&apos;s class (plus/minus/constant) was determined by the relative price change that happened between the publication date of a document and the next working day. We achieved a high accuracy of 75% for classification of discussion posts, however the classification accuracy for news articles was about 60%. We tried both Binary (documents with constant class were discarded) and ternary classification - the former was in all cases more successful.

Název v anglickém jazyce

Examining Stock Price Movements on Prague Stock Exchange Using Text Classification

Popis výsledku anglicky

The goal of the article was to examine the relationship between the content of text documents published on the Internet and the direction of movement of stock prices on the Prague Stock Exchange. The relationship was modeled by text classification. As data were used news articles and discussion posts on Czech websites and the value of the PX stock index and stock price of company CEZ. Document&apos;s class (plus/minus/constant) was determined by the relative price change that happened between the publication date of a document and the next working day. We achieved a high accuracy of 75% for classification of discussion posts, however the classification accuracy for news articles was about 60%. We tried both Binary (documents with constant class were discarded) and ternary classification - the former was in all cases more successful.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of New Computer Architectures and Their Applications

ISSN

2412-3587

e-ISSN

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Svazek periodika

7

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CN - Čínská lidová republika

Počet stran výsledku

6

Strana od-do

8-13

Kód UT WoS článku

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EID výsledku v databázi Scopus

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