A Proposed Model for Stock Price Prediction Based on Financial News
Keywords:
text mining, finance, news, crawling, stock, prices, prediction, naïve bayesAbstract
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.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
Aase, K. G. (2011), “Text Mining of News Articles for stock Price Prediction”, Master's thesis, Institutt for datateknikk og informasjonsvitenskap.
Falinouss, P. (2007), “Stock Trend Preidction Using News Articles: A Text Mining Approach”, Master’s Thesis.
Hagenau, M., Liebmann, M. Neumann, D. (2013), “Automated news reading: Stock prices prediction based on financial news using context-capturing features”, Decision Support Systems, Vol. 55, No. 3, pp. 685-697.
Joshi, K., Rao, J., Bharathi, H. N. (2016), “Stock Trend Prediction Using News Sentiment Analysis”, International Journal of Computer Science & Information Technology (IJCSIT), Vol. 8, No. 3, pp. 67-76.
Kaya, M. Y., Karsligil, M. E. (2010), “Stock price prediction using financial news articles”, in the Proceedings of the 2nd International Conference on Information and Financial Engineering, Chongqing, China, IEEE, pp. 478-482.
Khedr, A. E., Yaseen, N. (2017), “Predicting stock market behavior using data mining technique and news sentiment analysis”, International Journal of Intelligent Systems and Applications, Vol. 9, No. 7, pp. 22-30.
Kim, Y., Jeong, S. R., Ghani, I. (2014), “Text opinion mining to analyze news for stock market prediction”, International Journal of Advances in Soft Computing and its Application, Vol. 6, No. 1.
Nikfarjam, A., Emadzadeh, E., Muthaiyah, S. (2010), “Text mining approaches for stock market prediction”, in the Proceedings of the 2nd International Conference on Computer and Automation Engineering (ICCAE), Singapore, Singapore, IEEE, pp. 256-260.
Vale, M. N. d. (2018), “Dow Jones Index Change Prediction Using Text Mining”, Instituto Alberto Luiz Coimbra De Pós-Graduação E Pesquisa De Engenharia, Rio de Janeiro, Brazil.
Yip, J. (2018), “Algorithmic Trading using Sentiment Analysis on News Articles”, available at: https://towardsdatascience.com/https-towardsdatascience-com-algorithmic-trading-using-sentiment-analysis-on-news-articles-83db77966704 (15 May 2019).
