A modified BPN approach for stock market prediction
Fesal Mithani, Sahista Machchhar, Fernaz Jasdanwala · 2016
Predicting stock market accurately has always fascinated the market analysts. During the previous few decades assorted machine learning techniques (Regression, RBFN, SOM, BN and SVM) have been applied to examine the highly debatable nature of stock market by capturing and using repetitive patterns. Our main aim is to accurately predict value for the future and maximum amount of profit for a holder by using Back Propagation Neural Network. Here we gives brief information about assorted techniques used for prediction, so that it is easy for user to choose the share to buy or sale and predict the value which has minimum error.