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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM44969

Harnessing Artificial Intelligence for Stock Market Forecasting: A Machine Learning Approach to Predicting Financial Trends

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM44969

Volume:

9 |

4 |

Apr 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM44969

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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Authors

AT

Adarsh Tiwari

AG

Aryan Goyal

AD

Anubhav Dubey

BA

Bhavesh Awasthy

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Abstract

Predicting the stock market has never been easy with its turbulent waves and complications. Traditional approaches lately did not even have the mark by providing any reasonably accurate prediction for the very huge amount of data and so many external influences around. We will analyze how AI/ML can help predict the stock markets better in this article. We use different algorithms that form the class of ML, namely linear regression, decision trees, random forests and neural networks, on historical market data with the goals of drawing trends and extrapolating prediction. When we demonstrate the potential of AI in improving the prediction of the stock market, we test and evaluate the model performance by using leading calculations such as average square errors, root agents square errors and prediction accuracy. In conclusion, this article aims to focus on how AI can be of great importance in the future of financial forecasts.

KEYWORDS

Prediction of stock market machine learning artificial intelligence economic forecasts neural networks regression market behavior.

Cite This Article

Adarsh Tiwari, Aryan Goyal, Anubhav Dubey, Bhavesh Awasthy, "Harnessing Artificial Intelligence for Stock Market Forecasting: A Machine Learning Approach to Predicting Financial Trends," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 4, Apr 2025. https://doi.org/10.55041/IJSREM44969

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Publication Date

4/18/2025

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Double-Blind Peer Review

Review Rounds: 2

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

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