Analysis and Prediction of Stock Prices via Deep Learning

Abstract

It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consist of making computers perform tasks that normally requiring human intelligence is currently the dominant trend in scientific research. In stock market the decision on when buying or selling stock is important in order to achieve profit. There are number of techniques that can be used to help investors in order to make a decision for financial gain. In this project work I have proposed a prediction algorithm that will give the relation between the dependent factor like price and independent factors like opening price, closing price, high value of stock, low value of stock and volume of stocks bought. In this project, we have explained development of stock price prediction with the use of deep learning algorithm. In this work to use LSTM and RNN algorithms of deep learning architecture for the price prediction.