Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/207669
Authors: 
Selimi, Mubarek
Besimi, Adrian
Year of Publication: 
2019
Citation: 
[Editor:] Milković, Marin [Editor:] Seljan, Sanja [Editor:] Pejić Bach, Mirjana [Editor:] Peković, Sanja [Editor:] Perovic, Djurdjica [Title:] Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019 [ISSN:] 1849-7950 [Pages:] 100-107
Abstract: 
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.
Subjects: 
text mining
finance
news
crawling
stock
prices
prediction
naïve bayes
JEL: 
C89
Document Type: 
Conference Paper

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