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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

Issue per Year : 12

Volume Published : 10

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Paper Title: AI-Powered Stock Investment Prediction: Buy, Hold, or Sell Based on LLM to Investment Analysis
Authors Name: Pranita Bobade , Aditya Sarade
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IJRTI_202615
Published Paper Id: IJRTI2504284
Published In: Volume 10 Issue 4, April-2025
DOI:
Abstract: The stock market is highly influenced by news events and public sentiment, making investment decisions complex and time sensitive. Traditional stock analysis methods often fail to capture the immediate impact of breaking news and market sentiment, leading to missed opportunities or misinformed investments. This study explores the power of AI-driven sentiment analysis in predicting whether a stock should be bought, held, or sold based on financial news and public reactions. Using advances in artificial intelligence, our approach aims to provide investors with timely and data-driven insights, reducing the reliance on subjective decision making. This research sets the foundation for a more intuitive and sentiment-aware investment strategy that aligns with market dynamics and investor confidence.
Keywords: Fintech, Artificial Intelligence, Stocks
Cite Article: "AI-Powered Stock Investment Prediction: Buy, Hold, or Sell Based on LLM to Investment Analysis", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c506-c511, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504284.pdf
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ISSN: 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
Publication Details: Published Paper ID: IJRTI2504284
Registration ID:202615
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: c506-c511
Country: Pune, Maharashtra, India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504284
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504284
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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