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Reseach Article

Effectiveness of Artificial Intelligence in Stock Market Prediction based on Machine Learning

by Sohrab Mokhtari, Kang K. Yen, Jin Liu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 7
Year of Publication: 2021
Authors: Sohrab Mokhtari, Kang K. Yen, Jin Liu
10.5120/ijca2021921347

Sohrab Mokhtari, Kang K. Yen, Jin Liu . Effectiveness of Artificial Intelligence in Stock Market Prediction based on Machine Learning. International Journal of Computer Applications. 183, 7 ( Jun 2021), 1-8. DOI=10.5120/ijca2021921347

@article{ 10.5120/ijca2021921347,
author = { Sohrab Mokhtari, Kang K. Yen, Jin Liu },
title = { Effectiveness of Artificial Intelligence in Stock Market Prediction based on Machine Learning },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2021 },
volume = { 183 },
number = { 7 },
month = { Jun },
year = { 2021 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number7/31936-2021921347/ },
doi = { 10.5120/ijca2021921347 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:16:05.635114+05:30
%A Sohrab Mokhtari
%A Kang K. Yen
%A Jin Liu
%T Effectiveness of Artificial Intelligence in Stock Market Prediction based on Machine Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 7
%P 1-8
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper tries to address the problem of stock market prediction leveraging artificial intelligence (AI) strategies. The stock market prediction can be modeled based on two principal analyses called technical and fundamental. In the technical analysis approach, the regression machine learning (ML) algorithms are employed to predict the stock price trend at the end of a business day based on the historical price data. In contrast, in the fundamental analysis, the classification ML algorithms are applied to classify the public sentiment based on news and social media. In the technical analysis, the historical price data is exploited from Yahoo Finance, and in fundamental analysis, public tweets on Twitter associated with the stock market are investigated to assess the impact of sentiments on the stock market

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Index Terms

Computer Science
Information Sciences

Keywords

Machine Learning Time Series Prediction Technical Analysis Sentiment Embedding Financial Market