Stock Market Prediction with various Technical Indicators using Neural Network Technique
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
Prediction of a financial market is more challenging due to non linearity and uncertainty of the system. Due to many drawbacks of traditional techniques for developing predictive model for stock market, intelligent techniques are widely used. This research work presents use of Artificial Neural Network (ANN) using various technical indicators suggested by researchers. The stock Index data with Open, High, Low and Close are used to extract features and then features are selected based on many existing rank based feature selection techniques and a new Index data with reduced feature subset is supplied to ANN for future value prediction. An empirical result show that feature extraction and then feature selection may play crucial role in terms of efficiency of the ANN model. Ten years historical daily Indian stock data were used for the experimental purpose from which a total of 16 features were extracted and then 7 features are selected for stock market prediction. The MAPE found with these seven features is 5.48.
Authors and Affiliations
Richa Handa, H. S. Hota, S. R. Tandan
Keywords
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