Stock Market Price Prediction Using Artificial Neural Network

Abstract

This report represents the Artificial Neural Networks approach to predict stock market price. Stock market prices are actually time-series data and Artificial Neural Networks (ANNs) have the ability to find non-linear correlations between time-series data which makes it the best approach to predict stock market prices. Historical data from Dhaka Stock Exchange is used to train and predict the price by using ANN. The Artificial Neural Network (ANN) is implemented using multi-layer Feed-forward Backpropagation algorithm. To predict the specific result the model has been trained in different category of networks based on time period. Three different time period data have been chosen as one year data, six months data and three months data. Each categorized data has been trained by and tested Feed-forward Backpropagation algorithm. After the training and testing process the predicted values are compared with the real data to find the accuracy. The trained network with the highest accuracy rate will able to predict the best possible price of the stock market.