Abstract

Stock market predictions are one of the challenging tasks for financial investors across the globe. This challenge is due to the uncertainty and volatility of the stock prices in the market. Due to technology and globalization of business and financial markets it is important to predict the stock prices more quickly and accurately. Last few years there has been much improvement in the field of Neural Network (NN) applications in business and financial markets. Artificial Neural Network (ANN) methods are mostly implemented and play a vital role in decision making for stock market predictions. Multi Layer Perceptron (MLP) architecture with back propagation algorithm has the ability to predict with greater accuracy than other neural network algorithms. In this research, neural works predict tools are used to predict the future stock prices and their performance statistics will be evaluated. This would help the investor to analyze better in business decisions such as buy or sell a stock.