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Web Trade Analytics

Jaydeep Patidar ^[1], Raj Parmar ^[2], Shlok Kumar Jain ^[3], Vishesh Shrivastava ^[4], Sumeet Dhillon ^[5]

Department of Computer Science and Engineering,

Samrat Ashok Technological Institute,

Vidisha, 464001, India

Abstract— This research introduces an innovative web application developed using the MERN (MongoDB, Express.js, React, Node.js) stack, enhanced with fundamental machine learning algorithms, designed to address the complexities of stock market analysis. The central focus is on creating a user-customizable dashboard, allowing investors to select specific stocks for real-time analysis, sentiment tracking, and future price prediction.

The methodology integrates historical stock data with sentiment analysis sourced from news and social media. The machine learning algorithms leverage this data to generate buy or sell recommendations and forecast future price trends. Our findings underscore the practicality of this approach, enhancing investors' abilities to navigate the unpredictable stock market landscape and make informed decisions with an eye on the future.

Keywords— Stock Market, MERN Stack, Predictive Analysis, Future Forecasting

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