A Survey Study on Stock Market Prediction using Machine Learning

Registration ID: IJNRD_181389

Published ID: IJNRD2205213

DOI: Click Here to Get

Sonali Sonavne , Aniket Sonawane , Varad Deshmukh , Akanksha Malode , Astha Kalla

linear regression polynomial regression Decision tree long short-term memory (LSTM).

Prediction of stock prices is a challenging task these days, but with artificial intelligence, it can be made superior, the stock is unpredictable curve, prediction f stock market is covered with the complexity and instability. Stock prices are constantly changing every day. Estimating the stock market has a high demand for stock customers. Applying all extracted rules at any time is a major challenge to estimate the future stock price with high accuracy. The latest prediction techniques adopted for the stock market such as supervised learning, unsupervised learning, reinforcement learning, linear regression, polynomial regression, Decision tree, long short-term memory (LSTM) is studied and analyses in this framework work. This paper is about to discuss different techniques related to the prediction of the stock market.

Published Paper   E-Certificate

Sonali Sonavne, Aniket Sonawane, Varad Deshmukh, Akanksha Malode, & Astha Kalla (May-2022). A Survey Study on Stock Market Prediction using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(5), 1644-1649. https://ijnrd.org/papers/IJNRD2205213.pdf

Volume 7 Issue 5, May-2022

Pages : 1644-1649

Paper Reg. ID: IJNRD_181389

Published Paper Id: IJNRD2205213

Downloads: 000121989

Research Area: Information Technology 

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2205213.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2205213

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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