Application of Genetic Algorithm and Machine Learning Techniques for Stock Market P r e d i c t i o n

International Journal of Computer Trends and Technology (IJCTT)          
© 2016 by IJCTT Journal
Volume-36 Number-1
Year of Publication : 2016
Authors : Shibendu Mukherjee, S M Dilip Kumar


Shibendu Mukherjee, S M Dilip Kumar "Application of Genetic Algorithm and Machine Learning Techniques for Stock Market P r e d i c t i o n". International Journal of Computer Trends and Technology (IJCTT) V36(1):59-64, June 2016. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
In a financial research it is crucial to compute the expected momentum of the stocks. The objective is to reduce the risk involved in share investments and maximizing the returns of an investment. In this work, Genetic Algorithm (GA) is used to select high quality stocks with investment value from a vast pool of stocks. For the genetic algorithm to efficiently select the stocks a cogent fitness function is defined. Once defined, the elitist stock is determined. The resultant stock is clustered and a logistic regression model is built upon it. This gives a binary output for the user/customer whether to buy the stock or sell it. The experiments were conducted using RStudio and the results reveal that the proposed technique generates a higher accuracy for the prediction.

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Stock Market prediction, Machine Learning, Clustering, Genetic Algorithm, Logistic Regression.