Stock market price prediction analysis (LSTM vs EMA)

Stock market prediction and its analysis is a growing topic and is a field to research in today’s world. Even though the analysis is quite tough there are large number of data sets that have been available for the prediction to be done. In order to increase the quality of the output, this project seeks to forecast the stock market utilizing financial news, analyst opinions, and quotes. It suggests a cutting-edge technique for forecasting the closing price of the stock market. Several researchers have made various contributions in this field of chaotic forecast. The conventional methods up until now have been fundamental and technical analyses. This project’s goal is to assess the viability and effectiveness of LSTM and Exponential Moving average for stock market forecasting. EMA works on with regression model and LSTM works in form of 0 and 1 where 0 denotes no input is taken and 1 denotes all the input have taken. In this paper, we have taken datasets of 4 different companies i.e. UniquLo, Netflix, Apple and Amazon with graphical analysis for more clarity. Our paper presents that Moving average method of predicting stock market is more accurate than LSTM with an accuracy difference of 7.76%. The accuracy of MA was 92% and for LSTM was 84.24%.