International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Stock Price Predictor: An ML-Based System for Real-Time Financial Analysis and Forecasting |
|---|---|
| ABSTRACT | Stock market analysis is a complex task that requires access to real-time data, technical indicators, and predictive models. This paper presents a Stock Price Predictor system that integrates data aggregation, technical analysis, and machine learning-based forecasting into a unified platform. The system collects financial data from multiple APIs and processes it to generate insights such as moving averages, volatility, and risk metrics. A Linear Regression model is used to predict future stock prices based on historical patterns. Additionally, an AI-based symbol correction mechanism enhances usability by mapping user inputs to correct stock tickers. The application is developed using Python and Streamlit, providing an interactive and user-friendly interface. Experimental results demonstrate that the system provides accurate predictions, efficient visualization, and reliable financial insights, making it suitable for traders, investors, and learners. |
| AUTHOR | JADHAV N.S., OM MEGHRAJ MALSHETTI, PRASHANT SHANKAR TUPPONI, SHRAVANI MAHESH CHINCHURE, DIKSHA RAHUL JANKAR Project Guide, Department of Computer Engineering, A.G. Patil Polytechnic Institute, Solapur, Maharashtra, India Student, Department of Computer Engineering, A.G. Patil Polytechnic Institute, Solapur, Maharashtra, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404009 |
| pdf/9_Stock Price Predictor An ML-Based System for Real-Time Financial Analysis and Forecasting.pdf | |
| KEYWORDS | |
| References | [1] J. Brownlee, “Introduction to Time Series Forecasting with Python,” Machine Learning Mastery, 2018. [2] F. Chollet, Deep Learning with Python, Manning Publications, 2017. [3] T. Mikolov et al., “Efficient Estimation of Word Representations in Vector Space,” Proc. ICLR, 2013. [4] Scikit-learn Documentation, “Machine Learning in Python,” Available: https://scikit-learn.org [5] Yahoo Finance API Documentation, Available: https://finance.yahoo.com [6] Plotly Technologies Inc., “Interactive Data Visualization Library,” Available: https://plotly.com [7] Google, “Gemini AI API Documentation,” Available: https://ai.google.dev. |
