A proposed model for stock price prediction based on financial news

Mubarek Selimi, Adrian Besimi

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.

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Year of publication:	2019
Authors:	Selimi, Mubarek ; Besimi, Adrian
Published in:	Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (Online). - [Zagreb, Croatia] : [IRENET, Society for Advancing Innovation and Research in Economy], ISSN 2706-4735, ZDB-ID 3051947-0. - Vol. 5.2019, 1, p. 100-107
Subject:	text mining \| finance \| news \| crawling \| stock \| prices \| prediction \| naïve bayes \| Börsenkurs \| Share price \| Prognoseverfahren \| Forecasting model \| Ankündigungseffekt \| Announcement effect

Type of publication:	Article
Type of publication (narrower categories):	Konferenzbeitrag ; Conference paper ; Aufsatz im Buch ; Book section
Language:	English
Other identifiers:	hdl:10419/207669 [Handle]
Classification:	C89 - Data Collection and Data Estimation Methodology; Computer Programs. Other
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012227597