Paper Key : IRJ************397
Author: Shreesh Gururaj Kulkarni
Date Published: 01 Jan 2025
Abstract
This paper presents the development and implementation of a Stock Analysis Web Application that addresses the challenges of accessing, analyzing, and visualizing stock market data. Leveraging Python libraries such as yfinance, pandas, NumPy, matplotlib, seaborn, and Streamlit, the application enables real-time data retrieval, statistical computations, and interactive visualizations. Designed for investors and financial analysts, it simplifies complex analyses through an intuitive interface, providing actionable insights for informed decision-making. The modular architecture ensures scalability and extensibility for future enhancements. This work contributes to the intersection of financial technology and computational finance by bridging raw data with meaningful investment insights.
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