An Investigation of Forecasting Tadawul All Share Index (TASI) Using Machine Learning

Galal M. Binmakhashen, Adnan Ameen Bakather, Ali Abdulqader Bin-Salem

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

Abstract

Stock markets are one of the most complex, and dynamic environments. To make predictions about the stock prices, we may require combining several sources of market information. Another possibility is to attempt to monitor and predict the stock index prices of a target market. In this study, we investigated several machine learning algorithms to predict the Saudi stock price index by utilizing Bloomberg's most used indicators. The collected data represents 26 years of Tadawul All Share Index(TASI) index prices. Several machine learning algorithms were investigated for forecasting midterm TASI index pricing. Two Recurrent Neural Network (RNN) architectures (deeper, and shallower architectures) were created, trained, tested, and their performances in forecasting TASI index prices are contrasted. Furthermore, several traditional machine learning methods such as Linear regression, decision trees, and random forests are also studied for index price prediction. The experiments suggested that with 26 years of TASI index transactions, simple machine learning(ML) models are generally suitable to make better midterm index price forecasting in comparison to more complex ML models.

Original languageEnglish
Title of host publicationProceedings - 2022 7th International Conference on Data Science and Machine Learning Applications, CDMA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages19-24
Number of pages6
ISBN (Electronic)9781665410144
DOIs
StatePublished - 2022

Publication series

NameProceedings - 2022 7th International Conference on Data Science and Machine Learning Applications, CDMA 2022

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Long and short-term memory network
  • Multivariate time series
  • Regression
  • Stock index price prediction

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Health Informatics

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