Prediction of Stock Market Using Artificial Intelligence

Abstract

Abstract—Stock market is place where people buy and sell shares of publicly listed companies. Every buyer and seller try to predict the stock market price movements to get maximum profits and minimum losses. Using cutting edge technology such as AI can improve prediction stock price. In the procedure of considering strategies and variables to be considered, we found ML algorithmics such as Random forest, LSTM, SVM, ANN was not fully utilized. In this model we will introduce and review more a possible way to predict stock movements with high accuracy. The first thing we considered is data of previous year's share market prices, historical prices of currency and commodity market and the historical news headlines. The datasets were pre-processed and prepared for actual analysis. Therefore, our model will also focus on preprocessing of datasets. Second, after processing the datasets earlier, we will review the use of major AI technique for that data and productive results. In addition, the proposed system evaluates the application of the forecast system to the real-world scenario and the problems associated with the accuracy of the total values provided. The high accuracy and profitability was achieved when results of all algorithms are combined and considered all factors affecting the stock prices. Successful valuation prediction of share price can become a big asset for stock market firms and provide real life solutions to the difficulties faced by stock market individual investors have.