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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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| Paper Title: | AI-Powered Multi-Modal Market Analysis and Real-Time Trading Recommendation System |
| Authors Name: | P.Shakthipriya |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_202507
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| Published Paper Id: | IJRTI2504210 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | |
| Abstract: | This paper presents a novel artificial intelligence-based financial market analysis and trading recommendation platform that unifies structured and unstructured data streams into a real-time, high-accuracy decision-support engine. At its core, the platform incorporates a transformer-based Natural Language Processing (NLP) engine, trained on a vast corpus of 2.7 million financial documents including analyst reports, regulatory filings, and news articles. Integrated with 15 years of historical trading data and real-time market feeds, the system performs high-frequency sentiment analysis and multi-modal data fusion to provide actionable trading signals. The proposed system achieves sub-50ms latency in parallel analysis of over 10,000 stock symbols and has demonstrated an 83.7% success rate in forecasting significant market movements across diverse sectors. The platform features a proprietary scoring mechanism that evaluates sentiment polarity, trading volume anomalies, and temporal relevance to generate composite buy/sell signals. A feedback loop powered by reinforcement learning enhances predictive accuracy through continuous model retraining. Results indicate a 12.3% outperformance over standard benchmarks in back testing scenarios. This invention addresses the growing demand for intelligent, scalable, and interpretable market analysis tools among institutional and retail investors. By democratizing access to institutional-grade analytics and integrating them with real-time pipelines, the system represents a paradigm shift in modern fintech infrastructure. |
| Keywords: | Multi-modal Financial Analysis, AI-Based Trading Recommendations, Sentiment Classification, Real-time Market Intelligence, Backtesting and Performance Evaluation |
| Cite Article: | "AI-Powered Multi-Modal Market Analysis and Real-Time Trading Recommendation System", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b886-b893, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504210.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2504210
Registration ID:202507
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: b886-b893 Country: Coimbatore, Tamil Nadu, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504210 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504210 |
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ISSN: 2456-3315
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