Stock Price Prediction based on Stock-Specific and Sub-Industry-Specific News Articles

Yauheniya Shynkevich, TM McGinnity, SA Coleman, Ammar Belatreche

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Citations (Scopus)


Accurate forecasting of upcoming trends in the capital markets is extremely important for algorithmic trading and investment management. Before making a trading decision, investors estimate the probability that a certain news item will influence the market based on the available information. Speculation among traders is often caused by the release of a breaking news article and results in price movements. Publications of news articles influence the market state that makes them a powerful source of data in financial forecasting. Recently, researchers have developed trend and price prediction models based on information extracted from news articles. However, to date no previous research that investigates the advantages of using news articles with different levels of relevance to the target stock has been conducted. This research study uses the multiple kernel learning technique to effectively combine information extracted from stock-specific and sub-industry-specific news articles for prediction of an upcoming price movement. News articles are divided into these two categories based on their relevance to a targeted stock and analyzed by separate kernels. The experimental results show that utilizing two categories of news improves the prediction accuracy in comparison with methods based on a single news category.
Original languageEnglish
Title of host publicationUnknown Host Publication
Number of pages8
Publication statusPublished (in print/issue) - 12 Jul 2015
Event2015 International Joint Conference on Neural Networks (IJCNN), - Killarney
Duration: 12 Jul 2015 → …


Conference2015 International Joint Conference on Neural Networks (IJCNN),
Period12/07/15 → …


  • multiple kernel learning
  • stock price prediction
  • text mining
  • financial news


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