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Neural networks through stock market data prediction

In the proposed work, we presented an Artificial Neural Network approach to predict the stock market indices. We outlined the design of the Neural Network model with its salient features and customizable parameters. A number of the activation functions are implemented along with the options for the cross validation sets. We finally test our algorithm on the Nifty stock index dataset where we predict the values on the basis of values from the past days. We achieve a best case accuracy of 96% on the dataset.