STOCK PRICE PREDICTION AND ANALYSIS USING 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.