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Stock Prediction using Machine Learning a Review Paper

by Nirbhey Singh Pahwa, Neeha Khalfay, Vidhi Soni, Deepali Vora
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 5
Year of Publication: 2017
Authors: Nirbhey Singh Pahwa, Neeha Khalfay, Vidhi Soni, Deepali Vora
10.5120/ijca2017913453

Nirbhey Singh Pahwa, Neeha Khalfay, Vidhi Soni, Deepali Vora . Stock Prediction using Machine Learning a Review Paper. International Journal of Computer Applications. 163, 5 ( Apr 2017), 36-43. DOI=10.5120/ijca2017913453

@article{ 10.5120/ijca2017913453,
author = { Nirbhey Singh Pahwa, Neeha Khalfay, Vidhi Soni, Deepali Vora },
title = { Stock Prediction using Machine Learning a Review Paper },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 5 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 36-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume163/number5/27395-2017913453/ },
doi = { 10.5120/ijca2017913453 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:09:24.018520+05:30
%A Nirbhey Singh Pahwa
%A Neeha Khalfay
%A Vidhi Soni
%A Deepali Vora
%T Stock Prediction using Machine Learning a Review Paper
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 5
%P 36-43
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Every day more than 5000 trade companies enlisted in Bombay stock Exchange (BSE) offer an average of 24,00,00,000+ stocks, making an approximate of 2000Cr+ Indian rupees in investments. Thus analyzing such a huge market will prove beneficial to all stakeholders of the system. An application which focuses on the patterns generated in this stock trade over the period of time, and extracting the knowledge from those patterns to predict future behavior of the BSE stock market is essential. An application representing the information in visual form for user interpretation to buy and to sell a specific company’s stock is a key requirement. Such an application based on machine learning algorithms is the right choice in current scenario. This paper surveys the machine learning algorithms suitable for such an application; as well it discusses what are the current tools and techniques appropriate for its implementation.

References
  1. Author: W. HuangResearch paper: Forecasting stock market movement direction with support vector machine.Journal: Computers & Operations Research
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  4. https://azure.microsoft.com/en-in/documentation/articles/machine-learning-algorithm-choice/
  5. Author: Yusuf Perwej, Asif PerwejResearch paper: Prediction of the Bombay Stock Exchange (BSE) Market Returns Using Artificial Neural Network and Genetic Algorithm.Journal: Scientific Research
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  7. Author: Zahid Iqbal, R. Ilyas, W. Shahzad, Z. Mahmood and J AnjumResearch paper: Efficient Machine Learning Techniques forStock Market PredictionJournal: Int. Journal of Engineering Research and Applications, ISSN: 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.855-867.
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Index Terms

Computer Science
Information Sciences

Keywords

Machine learning review paper stock prediction machine learning algorithms supervised learning unsupervised learning supervised learning algorithms regression classification regression algorithm Support Vector Machine (SVM) Support Vector Regression (SVR) classification linear regression logistic regression types of regression types of classification types of programming languages for machine learning types of libraries for machine learning types of libraries for graphing types of libraries for analysis.

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