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Research Article | Open Access
Volume 15 2023 | None
STOCKMARKET PRICE PREDICTION AND TREND ANALYSIS USING MACHINE LEARNING ALGORITHMS
Mrs. V. SWATHI, Y. PRATHAM KALYAN, FARHEEN, S. ARUN, P. NEHA GOUD
Pages: 716-720
Abstract
Machine learning has significant applications in the stock price prediction. Our project revolves around stock market price prediction and trend analysis, employing cutting-edge machine learning techniques and harnessing the extensive data from Yahoo Finance. By combining historical stock data, day trading strategies, moving average analysis, and support and resistance techniques, our model aims to provide accurate and actionable insights for investors. Through rigorous training and testing of the machine learning algorithms, our project endeavors to forecast future price movements with improved precision. Investors can leverage these predictions to make informed decisions, enhancing their day trading strategies and optimizing their investment choices. The inclusion of moving average analysis and support and resistance techniques adds further depth to our model’s predictive capabilities. By identifying key price levels and potential turning points, our project aids investors in understanding market trends and potential areas of support and resistance. Our objective is to empower investors with a comprehensive toolset for informed decision-making in the volatile stock market. By utilizing advanced machine learning and integrating various technical analysis methods, our project aspires to enhance investors’ understanding of market dynamics, bolster day trading strategies, and ultimately improve overall investment performance. With a focus on accuracy and reliability, this project represents a valuable resource for traders seeking to navigate the complexities of the stock market with confidence.
Keywords
Machine learning has significant applications in the stock price prediction.
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