International Journal of Scientific Research and Engineering Development

The Stock Recommendation System was created to help investors make data-driven, well-informed stock market decisions. Manual stock data analysis is frequently laborious and error-prone due to the intricacy and volatility of financial markets. In order to overcome these difficulties, this system analyzes market trends and forecasts stock performance using machine learning algorithms, technical indicators, and historical stock data. Large amounts of financial data are processed by the system, which then uses predictive models and patterns to produce recommendations like buy, sell, or hold. It lowers investment risks, increases decision accuracy, and lessens human labor. The suggested approach is effective, scalable, and appropriate for both novice and seasoned investors. The system helps create smarter systems by utilizing automation and intelligent analysis investment techniques and improved financial results.

Samarth.S.Gajbar, Bhargav.D.Gote, Rihan.F.Pathan, Siddharth.A.Mhetar, Miss.Soniya.R.Ghatage,"Stock Recommendation System" International Journal of Scientific Research and Engineering Development, V9(2): Page(1946-1949) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.