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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 3 | Month- March 2026
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Published Paper Details:
Paper Title
AI-Driven Investment Strategies: Transforming Stock Market Analysis and Decision-Making
Authors
Dr.R.Poorvadevi, Ch.Bhavana Priya, Davu Manasa
Keywords
Machine Learning, Stock Market Prediction, Neural Networks, Investment Strategies
Abstract
Stocks of public companies are open for purchase and sale, giving investors ownership stakes and crucial data about the financial performance of the companies. This study examines how machine learning affects stock market price predictions, a subject that is frequently unstable and subject to a number of factors. We demonstrate how cutting-edge techniques, such neural networks and linear regression, beat conventional methods in identifying patterns and forecasting future events. According to our research, machine learning algorithms may be able to provide accurate and reliable forecasts, which might assist investors make better choices. In the end, this study shows how these cutting-edge technologies could improve investment techniques, providing traders with an edge over others and a better understanding of the market
IJCRT's Publication Details
Unique Identification Number - IJCRT2502804
Paper ID - 278030
Page Number(s) - g848-g852
Pubished in - Volume 13 | Issue 2 | February 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Dr.R.Poorvadevi, Ch.Bhavana Priya, Davu Manasa, "AI-Driven Investment Strategies: Transforming Stock Market Analysis and Decision-Making", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 2, pp.g848-g852, February 2025, Available at :http://www.ijcrt.org/papers/IJCRT2502804.pdf
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Volume 14 | Issue 3
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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