Analysis of a Stock Exchange and Future Prediction Using LSTM

Stock Market Prediction (SMP) algorithms, main goal is to estimate the future trend of the market estimation of the monetary stocks of individual company. Machine learning and Deep learning technology have become the new trend for stock exchange prediction technologies, which make forecasts based on training on past trading data. To make predictions more accurate and simpler, Machine Learning itself uses various models. Machine learning and Deep learning technology have become the new trend for stock exchange prediction technologies, which make forecasts based on training on past trading data. To make predictions more accurate and simpler, Machine Learning itself uses various models. In this paper, we are using the Machine learning techniques to analyze the stock price over time, the daily return of the stock on average, the moving average of different stocks, risk in investing stocks at particular trends, and finally predict the future stock behavior using LSTM model. ML itself utilizes various models to make expectations simpler and genuine. This paper keen about the utilization of Regression and LSTMBased Machines figuring out how to anticipate stock qualities. To analyze the stock, we are choosing different sectors big players like from telecom sector "Verizon", from digital media "Netflix", from customer relationship management "Salesforce", and from ecommerce sector "Amazon" from these stock elements considered are close, open, high, low, and volume.