Stock Price Prediction using Machine Learning and Sentiment Analysis

The stock market is a very dynamic market where nothing is as stable as a rock but as the technology is upgrading there are many ways and methods one can try to learn this dynamic change and be prepared accordingly. This paper focuses on such different methods of dynamically learning the market and its trends. We have used three different models for this paper and have also performed sentiment analysis on the tweets regarding the company or the stock, the model with the least error is the ideal and the most preferred method for prediction. The results of this classification have given a clear and insightful idea about the random ups and downs of the market and also a new approach for investors so that they know where they can bet their money. The ARIMA model is giving the best accuracy for every stock.