MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202621110024 A) filed by Dr. Prajakta Ratiram Patil; Mrs. P. R. Madhu Shree; Dr. Roopa Balasaheb Kurne; Dr. Priti Singh; Rajvardhan Ajitrao Jagtap; Dr. Kartik Chandra Das; Ashwini D P; Meenakshi S; Mrs. Harshini H P; and Dr. Manju Patil on September 14, 2026, for A System And Method For Ai Driven Algorithmic Trading Framework Using Real Time Sentiment Market Analysis.
Inventors include Dr. Prajakta Ratiram Patil; Mrs. P. R. Madhu Shree; Dr. Roopa Balasaheb Kurne; Dr. Priti Singh; Rajvardhan Ajitrao Jagtap; Dr. Kartik Chandra Das; Ashwini D P; Meenakshi S; Mrs. Harshini H P; and Dr. Manju Patil.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: ABSTRACT A SYSTEM AND METHOD FOR AI DRIVEN ALGORITHMIC TRADING FRAMEWORK USING REAL TIME SENTIMENT MARKET ANALYSIS The present invention relates to an artificial intelligence-driven algorithmic trading framework that integrates real-time sentiment market analysis for enhanced decision-making and risk management. The system comprises a data acquisition layer that collects both structured market data and unstructured sentiment data from social media, financial news, and analyst reports. A preprocessing and normalization module standardizes these inputs for analysis. The core sentiment analysis engine employs transformer-based natural language processing and machine learning models trained on financial corpora to detect sentiment polarity, intensity, and contextual relevance. Generated sentiment indices are dynamically fused with quantitative trading signals within a decision integration layer, enabling adaptive trading strategies responsive to market psychology. A trading execution and risk management module executes trades through latency-optimized pipelines and applies sentiment-driven risk controls to mitigate volatility. The framework supports cross-asset applicability, continuous learning, and explainable AI interfaces, providing transparency and regulatory compliance. This invention bridges quantitative analytics with qualitative sentiment insights, improving trading accuracy and profitability.
Disclaimer: Curated by HT Syndication.
