LSTM and CNN based Stock Price Prediction APP

Abstract

The Stock Market is one of the most important parts of today’s economy. The prices of the stock market represent the growth of the economy of that country. For many years researchers from various parts around the world have been studying various methods for predicting the next trends in the stock market. One such method for predicting stock prices is machine learning. Machine learning is quite effectively implemented in forecasting the prices of various Stocks. Stock market prediction is a difficult problem in machine learning. It can be extremely complex. In this project I will attempt to implement an LSTM model to analyze the stock market data accurately predictions about whether the stock prices are going to go up or if they are going down. LSTMs are extremely efficient in predicting the trends in stock prices because they’re able to store previous information. This is crucial because, the previous price of a stock is required in order to make the predictions on what the future price of that stock will be. The main purpose of this is to be able to make well educated and informed decisions about the investments in the stock market and ensure that a profit margin is maintained through trading various stocks.