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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM49316

Financial Analytics & Investment – Machine Learning in Stock Market Prediction

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM49316

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem49316

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.

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Digamber Prof. Dr. Shilpa Bahl

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Abstract

Objective: This paper aims to understand how machine learning can be used to predict stock market trends and improve investment decisions. The main goal is to analyze how financial data, when combined with smart computer models, can help investors make better choices. The study compares traditional forecasting methods with modern machine learning techniques to see which is more accurate and useful. It also looks at the challenges, such as market risks and data quality, and explores future possibilities in using artificial intelligence for stock market prediction.

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Cite This Article

Digamber Prof. Dr. Shilpa Bahl, "Financial Analytics & Investment – Machine Learning in Stock Market Prediction," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025. https://doi.org/10.55041/ijsrem49316

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Publication Date

6/2/2025

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Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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