MUMBAI, India, Jan. 23 -- Intellectual Property India has published a patent application (202511127223 A) filed by Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh, on Dec. 15, 2025, for 'hybrid deep learning system for stock market prediction and working method thereof.'
Inventor(s) include Aditya Singh; Abhishek Kumar; Divyanshi Priya; Akshat Srivastava; and Anuj Kumar.
The application for the patent was published on Jan. 23, under issue no. 04/2026.
According to the abstract released by the Intellectual Property India: "The present invention discloses a hybrid deep learning system for stock market prediction and a working method thereof, integrating multi-source financial data comprising real-time market data, technical indicators, fundamental financial information, and sentiment extracted from financial textual content. The system incorporates a feature-engineering pipeline, a transformer-based sentiment analysis model, and a hybrid neural architecture consisting of convolutional neural networks (CNN), bidirectional long short-term memory (Bi-LSTM) networks, and an attention mechanism to generate enhanced predictive outputs. Temporally aligned multi-modal data are fused into tensorized representations processed by the hybrid deep learning engine to produce buy, sell, or hold signals through a decision-support module. The method enables improved accuracy, adaptability, and real-time applicability, offering a technologically advanced solution for financial forecasting."
Disclaimer: Curated by HT Syndication.
