Stock Price Trend Analysis and Prediction using Machine Learning

Author(s)	Prasthuth Gowda, Surya Prakash, Lavanya A, Prof. Ashwini Tuppad
Country	India
Abstract	Stock price prediction and trend analysis are crucial aspects of financial markets, presenting complex challenges due to their dynamic nature . This research delves into the application of machine learning algorithms in addressing these challenges, focusing on popular models such as linear regression, Long Short-Term Memory (LSTM), and Convolutional Neural Network (CNN). By leveraging machine learning capabilities, this study aims to enhance predictive accuracy and understand stock market dynamics more comprehensively. The investigation involves a detailed examination and comparison of these algorithms, with linear regression providing a foundational benchmark against advanced techniques like LSTM and CNN, tailored for time series and complex pattern recognition, respectively
Keywords	Keywords— Linear regression, LSTM, CNN, Investors, Financial analysts
Field	Computer
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-23
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.20284

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research