International Journal of Research and Scientific Innovation (IJRSI)
Stock Price Prediction and Investment Recommendations through Machine Learning Analysis
Published October 7, 2025 • Vol. 12, Issue 9, pp. 3318–3328Open Access
DOI: 10.51244/IJRSI.2025.120800301
Abstract
We’re researching how our thesis can help guess stock prices and suggest smart investment moves. We start by checking if the current stock prices are right, looking at both the percent- age and money differences. We also predict the prices tomorrow, showing the real-time and guessed numbers and explaining how much they differ. After that, we give practical advice in three categories: Sell, Hold, and Buy, so people can make smart choices. We also look at what happens if the stock prices are guessed wrong and how it affects people’s investment portfolios.
Keywords: Stock Price, Prediction, Investment, Machine Learning, Analysis
| Journal | International Journal of Research and Scientific Innovation (IJRSI) |
|---|---|
| ISSN | 2321-2705 |
| Volume / Issue | Volume 12, Issue 9 |
| Pages | 3318–3328 |
| Publication date | October 7, 2025 |
| DOI | 10.51244/IJRSI.2025.120800301 |
| Publisher | RSIS International |
| License | Open Access |
How to cite this article
Hasibul Islam, Wary Hossain Rabby, Sadia Khanum, Md. Emran Sikder, A. S. S. M. Q-E-Elahy, Gias Uddin, & MD Rafiqul Islam (2025). Stock Price Prediction and Investment Recommendations through Machine Learning Analysis. International Journal of Research and Scientific Innovation (IJRSI), 12(9), 3318-3328. https://doi.org/10.51244/IJRSI.2025.120800301
BibTeX
@article{Hasibul2025,
title = {Stock Price Prediction and Investment Recommendations through Machine Learning Analysis},
author = {Hasibul Islam and Wary Hossain Rabby and Sadia Khanum and Md. Emran Sikder and A. S. S. M. Q-E-Elahy and Gias Uddin and MD Rafiqul Islam},
journal = {International Journal of Research and Scientific Innovation (IJRSI)},
volume = {12},
number = {9},
pages = {3318--3328},
year = {2025},
doi = {10.51244/IJRSI.2025.120800301},
publisher = {RSIS International}
}