Published April 30, 2024 | Version CC-BY-NC-ND 4.0
Journal article Open

Exploring the Future of Stock Market Prediction through Machine Learning: An Extensive Review and Outlook

Creators

  • 1. Associate Professor, Department of Computer Science and Engineering, IES Group of Institutions Bhopal (M.P), India.

Contributors

Contact person:

  • 1. Associate Professor, Department of Computer Science and Engineering, IES Group of Institutions Bhopal (M.P), India.
  • 2. Research Scholar, Department of Computer Science and Engineering, Eklavya University, Damoh (M.P), India.
  • 3. Professor, Department of Computer Science and Engineering, Eklavya University, Damoh (M.P), India.
  • 4. Professor, Department of Computer Science and Engineering, Eklvya University, Damoh (M.P), India.

Description

Abstract: A thorough analysis of trends and future directions reveals how machine learning is revolutionizing stock market forecasting. The most recent research on machine learning applications for stock market prediction during the previous 20 years is methodically reviewed in this article. Artificial neural networks, support vector machines, genetic algorithms in conjunction with other methodologies, and hybrid or alternative AI approaches were the categories used to group journal articles. Every category was examined to identify trends, distinct perspectives, constraints, and areas that needed more research. The results provide insightful analysis and suggestions for further study in this developing topic.

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Additional details

Identifiers

DOI
10.35940/ijisme.E9837.12040424
EISSN
2319-6386

Dates

Accepted
2024-04-15
Manuscript received on 06 March 2024 | Revised Manuscript received on 05 April 2024 | Manuscript Accepted on 15 April 2024 | Manuscript published on 30 April 2024.

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