Year: 2025
Type: article
Abstract: In today’s fast-evolving financial ecosystem, investors often struggle to navigate "fragmented market data" and make timely, informed decisions. To address this, we developed Investor Guidance and Predictive Analytics, a comprehensive "web-based platform" that brings together real-time market monitoring, stock fundamentals, financial analytics, news aggregation, and predictive modeling into a single, user-friendly system. The platform simplifies investment decision-making by providing a clear overview of major market indices, individual stock performance, and historical trends. The application ensures secure access with "hashed passwords" and session-based authentication, allowing users to explore personalized dashboards. Investors can search for stocks, view detailed company overviews, and analyze financial statements alongside historical price data. Integrated "Google News feeds" deliver the latest market updates, keeping users informed about market-moving developments, while the interface organizes all information intuitively for quick and effective analysis. At its core, the system emphasizes both "real-time tracking" and in-depth financial insights. Major indices like Nifty 50 and Sensex are updated automatically, while individual stocks display key metrics such as P/E ratio, market capitalization, revenue, profit margins, and growth indicators. Historical OHLC price data enables technical analysis, and annual and quarterly financial reports provide a comprehensive view of company performance. Built on Python with the Flask framework and a front end using HTML, CSS, and JavaScript, the platform leverages "Yahoo Finance" for data and supports future AI-driven predictions, empowering investors to make smarter, data-driven decisions. Keywords- Machine Learning, Stock, Overview, Fundamentals, News, Stock Price Prediction,
DOI: 10.55041/ijsrem52272
Authors: Ashwini C, B Vijaya Kumara
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4413854651