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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM49385
Volume:
9 |
6 |
Jun 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.
This study applies linear regression to forecast stock prices of ten Nifty 50 companies using historical data from 2024 to early 2025. Utilizing Microsoft Excel and VBA, a scalable, accessible framework was developed, with time and trading volume as key variables. Models were evaluated using R-squared and Mean Absolute Error (MAE). Results showed that linear regression effectively captured long-term trends, especially in stable stocks, but struggled with high volatility. The approach is valuable for educational and preliminary financial analysis, and future research should explore hybrid models for improved accuracy in dynamic markets
KEYWORDS
Publication Date
6/2/2025
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.
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