A Study on the Prediction of Infosys Stock Price using Artificial Neural Network (ANN)

Stock markets tend to be stock trading institutions where stocks and shares (equity) as well as other financial instruments for instance bonds are offered intended for trade. With regard to stocks, the marketplace generally operates any kind of ‘willing buyer, willing-seller’ trade, wherever buyers and sellers price tags are matched for the fit. Predicting has long been within the domain of linear statistics. An artificial neural network (ANN) is a large-scale, nonlinear compelling technique that is capable of executing extremely nonlinear functions, self-learning, and self-organizing. ANN is considered as more desirable pertaining to stock market forecasting than any other techniques given, it will be able to identify and find out patterns or even relationships through the data itself. For the study, simulation have been used as a way of predicting the stock price. The two efficiency measures, Mean Square Error (MSE), and Sum Squared Error (SSE) are applied to evaluate the actual performances for the model designed. The results produced will help the investors to take decision in a wise manner.