Literature Review on Stock Price Predictions with reference to Machine Learning Approaches and Statistical Methods

Abstract

An Indian stock market is an open market where businesses and individuals can increase revenues. Organizations use the stock market to buy and sell shares. The interest rate and the supply of shares determine the cost of shares. Trading/exchanging refers to purchasing and selling shares. Only Listed Companies are permitted to do so. Vast sums of money have recently been traded on stock exchanges worldwide. National economies are intricately linked, and the performance of their stock exchanges has a significant impact. As a final outcome, they are connected with macroeconomic variables and have a more direct impact on everyday life. They form a mechanism with critical and urgent social consequences as a natural outcome. Investors who trade stocks must have access to timely information in order to make wise decisions. Additionally, stock price behavior is unpredictable and challenging to forecast. These factors make stock price forecasting a critical and hard process to find the value of a particular share. This paper highlights the various research aspects applied to stock price predictions of shocks using machine learning approaches and statistical methods.