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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Leveraging BERT for Enhanced Stock Market Prediction: A Comprehensive Review |
| Authors Name: | Yash A Patil , Rohan U Patil , Sarvesh S Reshimwale , Atharv J Chirmure |
| Download E-Certificate: | Download |
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IJNRD_208966
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| Published Paper Id: | IJNRD2311161 |
| Published In: | Volume 8 Issue 11, November-2023 |
| DOI: | |
| Abstract: | This comprehensive review paper extensively explores the transformative possibilities offered by BERT (Bidirectional Encoder Representations from Transformers) within the context of stock market prediction, emphasizing the incorporation of stock news titles and historical stock prices. Addressing the shortcomings of conventional models in their ability to predict stock movements accurately, the investigation highlights the pivotal role of sophisticated natural language processing models, with BERT taking center stage. The proposed methodology is intricate, involving the fine-tuning of BERT using news scores obtained from an API as ground truth. The central objective is to unravel and leverage the impact of news sentiment on stock prices, offering a nuanced understanding of the intricate interplay between language and financial data. This review meticulously examines key facets, including the intricacies of the research methodology, the architecture of the implemented system, and the consequential experimental results. Through a meticulous examination of each component, this paper adds to a thorough understanding of BERT's effectiveness in improving stock market prediction. In its concluding remarks, the review not only consolidates significant findings but also extrapolates insights into the future implications of leveraging BERT for stock market forecasting. The inclusion of index terms such as BERT, stock market prediction, natural language processing, sentiment analysis, and financial analytics provides a structure |
| Keywords: | BERT ,Sentiment analysis, API,Natural language processing |
| Cite Article: | "Leveraging BERT for Enhanced Stock Market Prediction: A Comprehensive Review", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.b489-b493, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311161.pdf |
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRD2311161 Registration ID: 208966 Published In: Volume 8 Issue 11, November-2023 DOI (Digital Object Identifier): Page No: b489-b493 Country: PUNE , MAHARASHTRA, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2311161 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2311161 |
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ISSN: 2456-4184
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