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IJSTR >> Volume 9 - Issue 1, January 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

A Hybrid Approach To Evaluate Stock Returns Using Data Mining Techniques

[Full Text]



Sweta Bhattacharya, Rajeswari C, Saugata De



Classification; Data mining; Feature Selection; Stock return forecasting



The key to success in the field of stock trading depends on the ability of buying and selling stocks at the correct time where decision making skills and predictions play a major role. The objective is to “Sell high and buy low” which sounds easy but is difficult to achieve and errors in assumption can lead to extensive loss of money. Data mining is a popularly used technique which has helped to resolve decision making issues in this field this increasing accuracy in accuracy of predictions in stock trading. In this paper, a comparative analysis of the use of various classification algorithms namely SVM, Naïve Bayes classifier, CART and LAD are explored which have been a popular choice of algorithms in stock exchange data. Finally, a hybrid model is developed considering the pros and cons of Naïve Bayes classifier and SVM algorithm which has been successful in producing enhances accuracy in comparison to the existing approaches.



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