Call for Paper - January 2024 Edition
IJCA solicits original research papers for the January 2024 Edition. Last date of manuscript submission is December 20, 2023. Read More

Stock Prediction using Machine Learning a Review Paper

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Nirbhey Singh Pahwa, Neeha Khalfay, Vidhi Soni, Deepali Vora

Nirbhey Singh Pahwa, Neeha Khalfay, Vidhi Soni and Deepali Vora. Stock Prediction using Machine Learning a Review Paper. International Journal of Computer Applications 163(5):36-43, April 2017. BibTeX

	author = {Nirbhey Singh Pahwa and Neeha Khalfay and Vidhi Soni and Deepali Vora},
	title = {Stock Prediction using Machine Learning a Review Paper},
	journal = {International Journal of Computer Applications},
	issue_date = {April 2017},
	volume = {163},
	number = {5},
	month = {Apr},
	year = {2017},
	issn = {0975-8887},
	pages = {36-43},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2017913453},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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.


  1. Author: W. HuangResearch paper: Forecasting stock market movement direction with support vector machine.Journal: Computers & Operations Research
  2. Author: J. MoodyResearch paper: Learning to trade via direct reinforcement. Journal: IEEE Transactions on Neural Networks
  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
  6. Author: K. Senthamarai Kannan, P. Sailapathi Sekar,M.Mohamed Sathik and P. Arumugam Research paper: Financial Stock Market Forecast using Data MiningTechniquesJournal: International Multi-Conference of Engineers and Computer Scientists 2010 Vol I,IMECS 2010, March 17-19,2010, Hong Kong.ISSN:2078-0966
  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.
  8. Author: Marc-André MittermayeResearch paper: Forecasting Intraday Stock Price Trends with Text Mining TechniquesJournal: Hawaii International Conference on System Sciences –2004.
  9. Author: Prakash Ramani, Dr. P. D. MurarkaResearch paper: Stock Market Prediction Using Artificial Neural NetworkJournal: International Journal of Advanced Research in Computer Science and Software Engineering. ISSN: 2277-128x, Volume 3, Issue 4, April 2013


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.