Intellectual Property India Publishes Patent Application for 'Adaptive Deep Neural Network System For Stock Volatility Analysis' Filed by Vellore Institute Of Technology

MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541122251 A) filed by Vellore Institute Of Technology, Vellore, Tamil Nadu, on Dec. 4, 2025, for 'adaptive deep neural network system for stock volatility analysis.'

Inventor(s) include Dr. Ganesh Shamrao Khekare; Pranay Batta; and Chahak Gupta.

The application for the patent was published on Jan. 2, under issue no. 01/2026.

According to the abstract released by the Intellectual Property India: "The present disclosure provides an adaptive deep neural network system for stock volatility analysis. The system includes a data ingestion layer configured to collect social media sentiment data and historical stock market data, a preprocessing layer configured to process the data through separate pipelines, and an adaptive modeling layer. The adaptive modeling layer includes a sentiment-volatility network configured to generate sentiment-based volatility predictions and a price-volatility network configured to generate price-based volatility predictions. The system further includes a decision fusion layer configured to combine outputs from both networks to generate unified volatility predictions, and an automated retraining mechanism configured to update the networks when prediction accuracy degrades below a predetermined threshold."

Disclaimer: Curated by HT Syndication.