Stock Market Movement Prediction using Disparate Text Features with Machine Learning

Salah Bouktif, Ali Fiaz, Mamoun Awad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Forecasting stock market movement is a widely researched topic both in academia and industry. Accurate forecast of stock direction can help investors to acquire opportunities for gaining profit in the stock exchange. Predicting stock market due to its dynamic, non-linear and complex nature is inherently difficult. One of the weaknesses of existing stock movement prediction research is that using only sentiment-based features extracted from social media do not completely harness underlying stock behaviour.Finding out which factors are the most significant presents a monumental challenge. Thus, in this research, we will integrate several factors that can affect the stock prices by integrating sentiment analysis with important textual features with relevant lags with the aim to construct more reliable and realistic sentiment representation. To evaluate the performance of our approach, we present a case study based on the AMZN NASDAQ stocks. The experiment results show that random forest model with important features was able to predict the AMZN stock movement direction and to outperform other prediction methods.

Original languageEnglish
Title of host publication2019 3rd International Conference on Intelligent Computing in Data Sciences, ICDS 2019
EditorsPlamen Angelov, Jaouad Boumhidi, Hani Hagras, El Habib Nfaoui, Youness Oubenaalla, Chakir Loqman, Mohammed Mestari, Hajar Mousannif
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728100036
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes
Event3rd International Conference on Intelligent Computing in Data Sciences, ICDS 2019 - Marrakech, Morocco
Duration: Oct 28 2019Oct 30 2019

Publication series

Name2019 3rd International Conference on Intelligent Computing in Data Sciences, ICDS 2019

Conference

Conference3rd International Conference on Intelligent Computing in Data Sciences, ICDS 2019
Country/TerritoryMorocco
CityMarrakech
Period10/28/1910/30/19

Keywords

  • data mining
  • prediction
  • sentiment analysis
  • stock market direction
  • text feature

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Modelling and Simulation
  • Control and Optimization

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