Artificial intelligence (AI)-driven predictive analytics system for stock market trend forecasting, has system housing that collects, processes, and analyzes real-time and historical stock market data using machine learning model
	PRABADEVI M N; KAILASH S R M; SADEESH J; KUMAR S N; VIJAYAKANTHAN; JEYAPRABHA B
	2025-04-02
专利权人	JEYAPRABHA B (JEYA-Individual)
申请日期	2025-04-02
专利号	IN202541032474-A
成果简介	NOVELTY - The system has system housing that collects, processes, and analyzes real-time and historical stock market data using machine learning models. A deep learning-based forecasting model integrates technical indicators, fundamental analysis, and sentiment data for accurate stock trend predictions. A dynamic risk assessment module evaluates market volatility and adjusts investment strategies using reinforcement learning techniques. A hybrid AI framework combines supervised, unsupervised, and reinforcement learning to optimize stock market forecasting accuracy. A data-driven decision-making system visualizes Al-generated market insights through an interactive and real-time user interface. An adaptive stock prediction method continuously refines the forecasting model by integrating evolving market trends and macroeconomic factors. USE - Artificial intelligence (AI)-driven predictive analytics system for stock market trend forecasting. ADVANTAGE - The Al-driven predictive analytics system is designed to enhance stock market trend forecasting by leveraging advanced artificial intelligence techniques. The system integrates a hybrid Al framework that combines deep learning, reinforcement learning, and sentiment analysis to generate highly accurate and reliable stock market predictions. The system employs an adaptive learning mechanism that continuously refines the predictive models based on evolving market conditions, thus ensuring improved accuracy with minimal human intervention. The system has an ability to synthesize structured financial data, unstructured textual data from news and social media, and macroeconomic indicators into a unified forecasting framework. The system incorporates an explainability module, allowing investors and financial analysts to understand the rationale behind the predictions, thus increasing transparency and trust in Al-driven decision-making. The risk-aware forecasting module is integrated to assess real-time market volatility, investor sentiment fluctuations, and geopolitical events, enabling proactive risk management strategies. The system presents an innovative solution for investors, financial institutions, and market analysts seeking reliable insights for informed decision-making in complex financial markets. DESCRIPTION OF DRAWING(S) - The drawing shows a flow diagram illustrating the operation of the AI-based predictive analytics for stock trends.
IPC 分类号	G06N-020/00 ; G06N-005/045 ; G06Q-040/00 ; G06Q-040/04 ; G06Q-040/06
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/13227
专题	中国科学院新疆生态与地理研究所
作者单位	JEYAPRABHA B (JEYA-Individual)
推荐引用方式 GB/T 7714	PRABADEVI M N,KAILASH S R M,SADEESH J,et al. Artificial intelligence (AI)-driven predictive analytics system for stock market trend forecasting, has system housing that collects, processes, and analyzes real-time and historical stock market data using machine learning model. IN202541032474-A[P]. 2025.

条目包含的文件
条目无相关文件。

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。