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A decision tree—rough set hybrid system for stock market trend prediction

Publication Type : Journal Article

Publisher : International Journal of Computer Applications, International Journal of Computer Applications

Source : International Journal of Computer Applications, International Journal of Computer Applications, 244 5 th Avenue,\# 1526, New York, NY 10001, USA India, Volume 6, Number 9, p.1–6 (2010)

Url : https://www.researchgate.net/profile/V_Mohandas/publication/46280096_A_Decision_Tree-_Rough_Set_Hybrid_System_for_Stock_Market_Trend_Prediction/links/0c96053a2cafcf166e000000.pdf

Keywords : Artificial neural networks, Decision Tree, Rough set, Rules., Stock market, Technical indicators

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication, Mechanical Engineering

Year : 2010

Abstract : Prediction of stock market trends has been an area of great interest both to those who wish to profit by trading stocks in the stock market and for researchers attempting to uncover the information hidden in the stock market data. Applications of data mining techniques for stock market prediction, is an area of research which has been receiving a lot of attention recently. This work presents the design and performance evaluation of a hybrid decision tree- rough set based system for predicting the next days‟ trend in the Bombay Stock Exchange (BSESENSEX). Technical indicators are used in the present study to extract features from the historical SENSEX data. C4.5 decision tree is then used to select the relevant features and a rough set based system is then used to induce rules from theextracted features. Performance of the hybrid rough set based system is compared to that of an artificial neural network based trend prediction system and a naive bayes based trend predictor. It is observed from the results that the proposed system outperforms both the neural network based system and the naive bayes based trend prediction system.

Cite this Research Publication : Dr. Binoy B. Nair, Mohandas, V. P., and Dr. Sakthivel N.R., “A decision tree—rough set hybrid system for stock market trend prediction”, International Journal of Computer Applications, vol. 6, pp. 1–6, 2010.

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