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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM48232
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
With the widespread availability of internet access, participation in the stock market has become increasingly accessible, enabling individuals from diverse backgrounds to engage in trading and investment activities. This project aims to harness the power of machine learning techniques to forecast stock prices, thereby facilitating informed decision-making for company growth and investment strategies. By leveraging historical stock data and employing predictive models, the project seeks to enhance the accuracy and reliability of predicting future stock movements. Through rigorous analysis of historical trends and patterns, the project aims to provide valuable insights that can inform strategic planning and investment decisions in the dynamic financial markets. Ultimately, the project endeavors to empower stakeholders with actionable intelligence derived from advanced machine learning methodologies, thereby contributing to informed decision-making and fostering growth in the stock market landscape.
KEYWORDS
Publication Date
5/17/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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