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Publication: IIP Proceedings Year: 2022, Month: November Page No: 174-183, ISSN/ISBN: 978-93-95632-70-6, DOI/Link: https://rsquarel.org/assets/docupload/rsl20233E3C8413CD287E7.pdf
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING METHODS FOR PREDICTING THE STOCK MARKET
Area/Stream: Artificial Intelligence, Authors: Subrat Chetia Keywords: SVM, KNN, ANN, XGB, SMA, RSI, MACD, OBV Book Name /series: Futuristic Trends in Artificial Intelligence,Volume 2, Book 16, Chapter 17Publication: IIP Proceedings Year: 2022, Month: November Page No: 174-183, ISSN/ISBN: 978-93-95632-70-6, DOI/Link: https://rsquarel.org/assets/docupload/rsl20233E3C8413CD287E7.pdf
Abstract:
It is highly challenging to anticipate anything when there is a non-linear association between inputs and outputs. One of the most difficult tasks for financial analysts is to predicting the stock market values because of the environments' inherent noise and their high volatility in relation to market movements. The goal of this article is to demonstrate the use artificial intelligence and machine learning techniques to address the issue of stock market prediction. The two basic analysis that can be applied to model the estimation of the stock market are fundamental analysis and technical analysis. Regression algorithms are generally applied in the technical analysis to forecast the movement of the stock price at the closing of a business day based on past data. Contrarily, in the fundamental analysis, the public attitude is classified using a machine learning algorithm according to news and social media.
Cite this: Subrat Chetia,"ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING METHODS FOR PREDICTING THE STOCK MARKET", Futuristic Trends in Artificial Intelligence,Volume 2, Book 16, Chapter 17, November, 2022, 174-183, 978-93-95632-70-6, https://rsquarel.org/assets/docupload/rsl20233E3C8413CD287E7.pdf
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