Artificial Neural Networks Based Indian Stock Market Price Prediction: Before and After Demonetization

摘要

In this paper, stock market price prediction ability of Artificial Neural Networks (ANN) is investigated before andafter demonetization in India. Demonetization is the act by government of stripping a currency unit of its status aslegal tender. Nine stocks and CNX NIFTY50 index are considered for future value prediction. Nine stocks aresubdivided in terms of volatility and capitalization. Dataset for training, testing and validation of each stock underconsideration is of at least eight years. Multilayered Neural networks are trained by Levenberg-Marquardt algorithm,hidden layer transfer function is tangent sigmoid, and output layer transfer function is pure linear. Several networksare made by varying the number of neurons to achieve minimum Mean Squared Error (MSE) for an optimumaccuracy. Regression values found during training state are 0.999 for all networks that depicts high efficiency ofNeural Network designed. Predicted values by the networks designed are validated with actual values before andafter demonetization in India.