ABSTRACT
In the monetary market, the equity market plays a significant role and has always attracted the interest of many analysts and experts in the financial market. Stock market forecasting is an exigent problem due to the fact that it is immensely complex, chaotic, dynamic, and has a number of different variables that are involved. Many studies have emerged in the past several years exploring historical data of stock, sentimental, fundamental, and technical analysis using statistical, data mining, expert systems, and deep learning techniques for the better analysis or prediction of stock trading. However, there is a need for research that consolidates this available information pertaining to the different analysis used in statistical data mining, expert systems, and deep learning techniques. The key objective of this paper is to systematize and summarize extensive research that has contributed to the area of the financial market for analysis and forecasting of the stock market. This paper attempts to explore the existing literature on fundamental, technical, and sentimental analysis approaches used for stock market forecasting. This paper also deals with challenges and opportunities for research in this area.
