Prediction of Stock Market Prices using Prediction algorithm and Sentiment Analysis

Stock market has fascinated thousands of investors’ hearts from entire globe. Prediction of the stock exchange data is main monetary subject which has involvement of supposition that, there is some predictive relation between past and future stock returns. An every indusial should know that stock market is one of the vital things with respect to economy of country. People who are keen towards computers and trading communal are interested in forecasting of stocks. Forecasting can be done using past data values as well as understanding the bulletin and data in Digital Media. Unobtainability or erroneous predictions because of varying patterns. Predictions of Stocks are interesting not only for the trading community only but also for a computer enthusiastic public. When we think about prediction, it can happen in two ways: we can predict using previous data values and the other way is to look and understand the news and data in the Digital Media. In the previous case there is a problem with the unavailability of the data or some data which is available but we might get inaccurate predictions because of changing patterns. Our system predicts the stock prices for the next trading day and for the specific date. Moving average technique is used to get improved prediction from the model. The Moving Average is the best widespread techniques procedure amongst every marker. The point of this investigation is done to give an appearance whether the moving normal pointer is unconditionally valuing the case by financial supporters and examiners. The theme of this tool is to provide opportunities and recognize whether future security worth developing. The contextual mining of text with recognizing and deriving subjective information from the source material is known as Sentiment analysis. Opinion about the particular company can be identified by user by Real time sentiment analysis of the stock prices. Users can easily identify the opinion of people whether tweets are positive, neutral or negative by using graphs by our carried-out sentiment analysis of tweets. The prediction accuracy is assessed and gives a percentage of accurate result. The accuracy and the prediction is combined to give user to acknowledge them the trend of the target stock with known accuracy. Also, the future price of each company can be checked by user