Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/207669 
Erscheinungsjahr: 
2019
Quellenangabe: 
[Title:] Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019 [Publisher:] IRENET - Society for Advancing Innovation and Research in Economy [Place:] Zagreb [Year:] 2019 [Pages:] 100-107
Verlag: 
IRENET - Society for Advancing Innovation and Research in Economy, Zagreb
Zusammenfassung: 
In this paper we will propose a model and needed steps that one should undertake in order to try and predict potential stock price fluctuation solely based on financial news from relevant sources. The paper will start with providing background information on the problem and text mining in general, furthermore supporting the idea with relevant research papers needed to focus on the problem we are researching. Our model relies on existing text-mining techniques used for sentiment analysis, combined with historical data from relevant news sources as well as stock data.
Schlagwörter: 
text mining
finance
news
crawling
stock
prices
prediction
naïve bayes
JEL: 
C89
Creative-Commons-Lizenz: 
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Dokumentart: 
Conference Paper

Datei(en):
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