Stock Market Prediction using Deep Learning

Abstract

Abstract: Stock market is very uncertain and highly volatile as the prices of stocks keep fluctuating due to several factors that make prediction of stocks a very difficult and complicated task. In the finance and trading world stock analysis and trading is a method for investors and traders to make buying and selling decisions. Investors and traders try to gain an edge in the markets by taking informed decisions by studying and evaluating past and current data. Stock market prediction has always been an important research topic in the financial and trading field [2]. Prediction of stock market is the act of trying to determine the future value of a company stock (nifty & sensex) or other financial instrument traded on an exchange. Our project explains the prediction of a stock using Machine Learning, which itself employs different models to make prediction easier and authentic. The paper focuses on the use of Recurrent Neural Networks (RNN) called Long Short Term Memory (LSTM) to predict stock values. This will help us provide more accurate results when compared to existing stock price prediction algorithms. The eminent analysis of the stock will be an asset for the stock market investors and will provide real-life solutions to the problems and also yield significant profit. Keywords: Stock Price Prediction, Machine Learning, Long Short-Term Memory, Recurrent Neural Networks