Abstract :

Stock Market Prediction Plays A Vital Role In Financial Decision-making. Due To The Highly Volatile And Nonlinear Behavior Of Stock Prices, Traditional Prediction Models Often Fail To Provide Accurate Results In Real-time Environments. This Paper Presents A Real-time Stock Market Prediction System Using Long Short-Term Memory (LSTM), A Deep Learning Technique Capable Of Capturing Temporal Dependencies In Sequential Data. The Proposed System Integrates Historical And Live Stock Data Using Financial APIs, Processes The Data, And Generates Short-term Price Predictions. A User-friendly Dashboard Is Developed To Visualize Actual And Predicted Trends Dynamically. The System Aims To Assist Traders And Analysts By Providing Accurate, Real-time Insights For Better Decision-making.

Published:

10-4-1-2026

Issue:

Vol. 26 No. 4-1 (2026)

Page Nos:

283-288

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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