Stock Market Prediction Analysis Using Machine Learning Transformer Model

Stock market is one of the foundations that supports a nation's economy. People have been investing in the stock market for many years in an effort to maximize the return on their capital. Therefore, having a prediction model that can correctly forecast future stock prices is essential. It is not an impossible task with the aid of machine learning, as the different machine learning techniques if properly modeled, may be able to produce the best prediction values. The investors would then be free to choose whether to buy, sell, or hold the share. The purpose of this article is to more accurately forecast the future of a company's financial stocks using a transformer model and suggests utilizing sentiment and historical data to predict stock analysis effectively. The movement of stock prices and the release of news stories have been found to be strongly correlated, according to an analysis of the sentiment analysis literature. To more properly predict the stock analysis, we have combined these criteria into this paper.