Impact of Artificial Intelligence in Stock Price Prediction Resulting Wealth Accumulation Consequences

Abstract

The stock market is an area where the prices are not constant; but dynamic, nonlinear and volatile in nature. The price forecasting is a challenging task with the factors including financial performance of the organization impact of government policies unexpected natural and man-made causes, and worldwide economic conditions. In concern to these issues, several analytical techniques already developed by researchers, financial analysts, and data scientists for predicting the nature of stock market trends. Forecasting accurate predictions of stock market analysis remains a persistent challenge due to the ever-shifting and volatile nature of market trends. Recent advancements with machine learning techniques mitigate some uncertainties of stock market forecasting. In this research paper we have to discuss the various ML techniques which will perform good forecast as compare to the previous existing methods. We will prove it by some results provided by above set techniques.