A Comparison of various methodologies in AI and ML for stock market prediction

Abstract

Stock market projection patterns are becoming more successful and are regarded as an important activity. As a result, stock prices will provide large benefits for prudent decision-making. Due to old and unclear information, stock market estimates provide a considerable challenge for investors. As a result, forecasting the stock market is extremely difficult for investors seeking to maximize their return on investment. Stock market predictions are made utilizing mathematical approaches and study aids. This study article examines 30 articles to provide an understanding of the procedures involved in the stream as well as the bet calculating approach. ANN and NN algorithms are the most commonly employed to generate accurate stock market predictions. Despite considerable effort, the most recent stock market-related prediction system includes numerous flaws. In this study, it is assumed that stock market forecasting is a full process and that specific factors are more accurate.