Application of Genetic Algorithm and Machine Learning Techniques for Stock Market P r e d i c t i o n
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2016 by IJCTT Journal | ||
| Volume-36 Number-1 |
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| Year of Publication : 2016 | ||
| Authors : Shibendu Mukherjee, S M Dilip Kumar | ||
| DOI : 10.14445/22312803/IJCTT-V36P110 |
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. www.ijcttjournal.org. 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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Keywords
Stock Market prediction, Machine Learning,
Clustering, Genetic Algorithm, Logistic Regression.