A Technical Analysis Based Prediction of Stock Market Trading Strategies Using Deep Learning and Machine Learning Algorithms



Stock Market; Technical Analysis; Machine Learning; Deep Learning; Prediction


Stock market movement follows the random walk nature. The technical analysis incorporates the use of various technical indicators. Technical analysis is well suited for short term predictions. In this research work, Machine learning algorithms - Decision Tree, Support Vector Machine, Naïve Bayes and Deep Learning algorithms- Convolutional Neural Networks and Generative Adversarial Networks are used for the stock market prediction problem. Datasets of three companies- Maruti Suzuki, HDFC and Infosys belonging to Automobile, Banking and IT sector listed on National Stock Exchange (NSE) - Indian stock market over the period of 6 years (June 2014-June 2020) are considered. Performance of the above algorithms is measured in terms of how accurately they predict the stock movements. For the construction of learning models cross validation as well as training-testing percentage split are used. From the results, it is clear that deep learning algorithms show better prediction accuracy as compared to machine learning models.


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Transformation of input space to feature space




How to Cite

Nitin Nandkumar Sakhare and Dr. S. Sagar Imambi, “A Technical Analysis Based Prediction of Stock Market Trading Strategies Using Deep Learning and Machine Learning Algorithms”, Int J Intell Syst Appl Eng, vol. 10, no. 3, pp. 411–422, Oct. 2022.



Research Article